EUR/USD Forecast And Long Term Prediction (2020) Kagels ...

Trading economic news

The majority of this sub is focused on technical analysis. I regularly ridicule such "tea leaf readers" and advocate for trading based on fundamentals and economic news instead, so I figured I should take the time to write up something on how exactly you can trade economic news releases.
This post is long as balls so I won't be upset if you get bored and go back to your drooping dick patterns or whatever.

How economic news is released

First, it helps to know how economic news is compiled and released. Let's take Initial Jobless Claims, the number of initial claims for unemployment benefits around the United States from Sunday through Saturday. Initial in this context means the first claim for benefits made by an individual during a particular stretch of unemployment. The Initial Jobless Claims figure appears in the Department of Labor's Unemployment Insurance Weekly Claims Report, which compiles information from all of the per-state departments that report to the DOL during the week. A typical number is between 100k and 250k and it can vary quite significantly week-to-week.
The Unemployment Insurance Weekly Claims Report contains data that lags 5 days behind. For example, the Report issued on Thursday March 26th 2020 contained data about the week ending on Saturday March 21st 2020.
In the days leading up to the Report, financial companies will survey economists and run complicated mathematical models to forecast the upcoming Initial Jobless Claims figure. The results of surveyed experts is called the "consensus"; specific companies, experts, and websites will also provide their own forecasts. Different companies will release different consensuses. Usually they are pretty close (within 2-3k), but for last week's record-high Initial Jobless Claims the reported consensuses varied by up to 1M! In other words, there was essentially no consensus.
The Unemployment Insurance Weekly Claims Report is released each Thursday morning at exactly 8:30 AM ET. (On Thanksgiving the Report is released on Wednesday instead.) Media representatives gather at the Frances Perkins Building in Washington DC and are admitted to the "lockup" at 8:00 AM ET. In order to be admitted to the lockup you have to be a credentialed member of a media organization that has signed the DOL lockup agreement. The lockup room is small so there is a limited number of spots.
No phones are allowed. Reporters bring their laptops and connect to a local network; there is a master switch on the wall that prevents/enables Internet connectivity on this network. Once the doors are closed the Unemployment Insurance Weekly Claims Report is distributed, with a heading that announces it is "embargoed" (not to be released) prior to 8:30 AM. Reporters type up their analyses of the report, including extracting key figures like Initial Jobless Claims. They load their write-ups into their companies' software, which prepares to send it out as soon as Internet is enabled. At 8:30 AM the DOL representative in the room flips the wall switch and all of the laptops are connected to the Internet, releasing their write-ups to their companies and on to their companies' partners.
Many of those media companies have externally accessible APIs for distributing news. Media aggregators and squawk services (like RanSquawk and TradeTheNews) subscribe to all of these different APIs and then redistribute the key economic figures from the Report to their own subscribers within one second after Internet is enabled in the DOL lockup.
Some squawk services are text-based while others are audio-based. FinancialJuice.com provides a free audio squawk service; internally they have a paid subscription to a professional squawk service and they simply read out the latest headlines to their own listeners, subsidized by ads on the site. I've been using it for 4 months now and have been pretty happy. It usually lags behind the official release times by 1-2 seconds and occasionally they verbally flub the numbers or stutter and have to repeat, but you can't beat the price!
Important - I’m not affiliated with FinancialJuice and I’m not advocating that you use them over any other squawk. If you use them and they misspeak a number and you lose all your money don’t blame me. If anybody has any other free alternatives please share them!

How the news affects forex markets

Institutional forex traders subscribe to these squawk services and use custom software to consume the emerging data programmatically and then automatically initiate trades based on the perceived change to the fundamentals that the figures represent.
It's important to note that every institution will have "priced in" their own forecasted figures well in advance of an actual news release. Forecasts and consensuses all come out at different times in the days leading up to a news release, so by the time the news drops everybody is really only looking for an unexpected result. You can't really know what any given institution expects the value to be, but unless someone has inside information you can pretty much assume that the market has collectively priced in the experts' consensus. When the news comes out, institutions will trade based on the difference between the actual and their forecast.
Sometimes the news reflects a real change to the fundamentals with an economic effect that will change the demand for a currency, like an interest rate decision. However, in the case of the Initial Jobless Claims figure, which is a backwards-looking metric, trading is really just self-fulfilling speculation that market participants will buy dollars when unemployment is low and sell dollars when unemployment is high. Generally speaking, news that reflects a real economic shift has a bigger effect than news that only matters to speculators.
Massive and extremely fast news-based trades happen within tenths of a second on the ECNs on which institutional traders are participants. Over the next few seconds the resulting price changes trickle down to retail traders. Some economic news, like Non Farm Payroll Employment, has an effect that can last minutes to hours as "slow money" follows behind on the trend created by the "fast money". Other news, like Initial Jobless Claims, has a short impact that trails off within a couple minutes and is subsequently dwarfed by the usual pseudorandom movements in the market.
The bigger the difference between actual and consensus, the bigger the effect on any given currency pair. Since economic news releases generally relate to a single currency, the biggest and most easily predicted effects are seen on pairs where one currency is directly effected and the other is not affected at all. Personally I trade USD/JPY because the time difference between the US and Japan ensures that no news will be coming out of Japan at the same time that economic news is being released in the US.
Before deciding to trade any particular news release you should measure the historical correlation between the release (specifically, the difference between actual and consensus) and the resulting short-term change in the currency pair. Historical data for various news releases (along with historical consensus data) is readily available. You can pay to get it exported into Excel or whatever, or you can scroll through it for free on websites like TradingEconomics.com.
Let's look at two examples: Initial Jobless Claims and Non Farm Payroll Employment (NFP). I collected historical consensuses and actuals for these releases from January 2018 through the present, measured the "surprise" difference for each, and then correlated that to short-term changes in USD/JPY at the time of release using 5 second candles.
I omitted any releases that occurred simultaneously as another major release. For example, occasionally the monthly Initial Jobless Claims comes out at the exact same time as the monthly Balance of Trade figure, which is a more significant economic indicator and can be expected to dwarf the effect of the Unemployment Insurance Weekly Claims Report.
USD/JPY correlation with Initial Jobless Claims (2018 - present)
USD/JPY correlation with Non Farm Payrolls (2018 - present)
The horizontal axes on these charts is the duration (in seconds) after the news release over which correlation was calculated. The vertical axis is the Pearson correlation coefficient: +1 means that the change in USD/JPY over that duration was perfectly linearly correlated to the "surprise" in the releases; -1 means that the change in USD/JPY was perfectly linearly correlated but in the opposite direction, and 0 means that there is no correlation at all.
For Initial Jobless Claims you can see that for the first 30 seconds USD/JPY is strongly negatively correlated with the difference between consensus and actual jobless claims. That is, fewer-than-forecast jobless claims (fewer newly unemployed people than expected) strengthens the dollar and greater-than-forecast jobless claims (more newly unemployed people than expected) weakens the dollar. Correlation then trails off and changes to a moderate/weak positive correlation. I interpret this as algorithms "buying the dip" and vice versa, but I don't know for sure. From this chart it appears that you could profit by opening a trade for 15 seconds (duration with strongest correlation) that is long USD/JPY when Initial Jobless Claims is lower than the consensus and short USD/JPY when Initial Jobless Claims is higher than expected.
The chart for Non Farm Payroll looks very different. Correlation is positive (higher-than-expected payrolls strengthen the dollar and lower-than-expected payrolls weaken the dollar) and peaks at around 45 seconds, then slowly decreases as time goes on. This implies that price changes due to NFP are quite significant relative to background noise and "stick" even as normal fluctuations pick back up.
I wanted to show an example of what the USD/JPY S5 chart looks like when an "uncontested" (no other major simultaneously news release) Initial Jobless Claims and NFP drops, but unfortunately my broker's charts only go back a week. (I can pull historical data going back years through the API but to make it into a pretty chart would be a bit of work.) If anybody can get a 5-second chart of USD/JPY at March 19, 2020, UTC 12:30 and/or at February 7, 2020, UTC 13:30 let me know and I'll add it here.

Backtesting

So without too much effort we determined that (1) USD/JPY is strongly negatively correlated with the Initial Jobless Claims figure for the first 15 seconds after the release of the Unemployment Insurance Weekly Claims Report (when no other major news is being released) and also that (2) USD/JPY is strongly positively correlated with the Non Farms Payroll figure for the first 45 seconds after the release of the Employment Situation report.
Before you can assume you can profit off the news you have to backtest and consider three important parameters.
Entry speed: How quickly can you realistically enter the trade? The correlation performed above was measured from the exact moment the news was released, but realistically if you've got your finger on the trigger and your ear to the squawk it will take a few seconds to hit "Buy" or "Sell" and confirm. If 90% of the price move happens in the first second you're SOL. For back-testing purposes I assume a 5 second delay. In practice I use custom software that opens a trade with one click, and I can reliably enter a trade within 2-3 seconds after the news drops, using the FinancialJuice free squawk.
Minimum surprise: Should you trade every release or can you do better by only trading those with a big enough "surprise" factor? Backtesting will tell you whether being more selective is better long-term or not.
Hold time: The optimal time to hold the trade is not necessarily the same as the time of maximum correlation. That's a good starting point but it's not necessarily the best number. Backtesting each possible hold time will let you find the best one.
The spread: When you're only holding a position open for 30 seconds, the spread will kill you. The correlations performed above used the midpoint price, but in reality you have to buy at the ask and sell at the bid. Brokers aren't stupid and the moment volume on the ECN jumps they will widen the spread for their retail customers. The only way to determine if the news-driven price movements reliably overcome the spread is to backtest.
Stops: Personally I don't use stops, neither take-profit nor stop-loss, since I'm automatically closing the trade after a fixed (and very short) amount of time. Additionally, brokers have a minimum stop distance; the profits from scalping the news are so slim that even the nearest stops they allow will generally not get triggered.
I backtested trading these two news releases (since 2018), using a 5 second entry delay, real historical spreads, and no stops, cycling through different "surprise" thresholds and hold times to find the combination that returns the highest net profit. It's important to maximize net profit, not expected value per trade, so you don't over-optimize and reduce the total number of trades taken to one single profitable trade. If you want to get fancy you can set up a custom metric that combines number of trades, expected value, and drawdown into a single score to be maximized.
For the Initial Jobless Claims figure I found that the best combination is to hold trades open for 25 seconds (that is, open at 5 seconds elapsed and hold until 30 seconds elapsed) and only trade when the difference between consensus and actual is 7k or higher. That leads to 30 trades taken since 2018 and an expected return of... drumroll please... -0.0093 yen per unit per trade.
Yep, that's a loss of approx. $8.63 per lot.
Disappointing right? That's the spread and that's why you have to backtest. Even though the release of the Unemployment Insurance Weekly Claims Report has a strong correlation with movement in USD/JPY, it's simply not something that a retail trader can profit from.
Let's turn to the NFP. There I found that the best combination is to hold trades open for 75 seconds (that is, open at 5 seconds elapsed and hold until 80 seconds elapsed) and trade every single NFP (no minimum "surprise" threshold). That leads to 20 trades taken since 2018 and an expected return of... drumroll please... +0.1306 yen per unit per trade.
That's a profit of approx. $121.25 per lot. Not bad for 75 seconds of work! That's a +6% ROI at 50x leverage.

Make it real

If you want to do this for realsies, you need to run these numbers for all of the major economic news releases. Markit Manufacturing PMI, Factory Orders MoM, Trade Balance, PPI MoM, Export and Import Prices, Michigan Consumer Sentiment, Retail Sales MoM, Industrial Production MoM, you get the idea. You keep a list of all of the releases you want to trade, when they are released, and the ideal hold time and "surprise" threshold. A few minutes before the prescribed release time you open up your broker's software, turn on your squawk, maybe jot a few notes about consensuses and model forecasts, and get your finger on the button. At the moment you hear the release you open the trade in the correct direction, hold it (without looking at the chart!) for the required amount of time, then close it and go on with your day.
Some benefits of trading this way: * Most major economic releases come out at either 8:30 AM ET or 10:00 AM ET, and then you're done for the day. * It's easily backtestable. You can look back at the numbers and see exactly what to expect your return to be. * It's fun! Packing your trading into 30 seconds and knowing that institutions are moving billions of dollars around as fast as they can based on the exact same news you just read is thrilling. * You can wow your friends by saying things like "The St. Louis Fed had some interesting remarks on consumer spending in the latest Beige Book." * No crayons involved.
Some downsides: * It's tricky to be fast enough without writing custom software. Some broker software is very slow and requires multiple dialog boxes before a position is opened, which won't cut it. * The profits are very slim, you're not going to impress your instagram followers to join your expensive trade copying service with your 30-second twice-weekly trades. * Any friends you might wow with your boring-ass economic talking points are themselves the most boring people in the world.
I hope you enjoyed this long as fuck post and you give trading economic news a try!
submitted by thicc_dads_club to Forex [link] [comments]

Finding Trading Edges: Where to Get High R:R trades and Profit Potential of Them.

Finding Trading Edges: Where to Get High R:R trades and Profit Potential of Them.
TL;DR - I will try and flip an account from $50 or less to $1,000 over 2019. I will post all my account details so my strategy can be seen/copied. I will do this using only three or four trading setups. All of which are simple enough to learn. I will start trading on 10th January.
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As I see it there are two mains ways to understand how to make money in the markets. The first is to know what the biggest winners in the markets are doing and duplicating what they do. This is hard. Most of the biggest players will not publicly tell people what they are doing. You need to be able to kinda slide in with them and see if you can pick up some info. Not suitable for most people, takes a lot of networking and even then you have to be able to make the correct inferences.
Another way is to know the most common trades of losing traders and then be on the other side of their common mistakes. This is usually far easier, usually everyone knows the mind of a losing trader. I learned about what losing traders do every day by being one of them for many years. I noticed I had an some sort of affinity for buying at the very top of moves and selling at the very bottom. This sucked, however, is was obvious there was winning trades on the other side of what I was doing and the adjustments to be a good trader were small (albeit, tricky).
Thus began the study for entries and maximum risk:reward. See, there have been times I have bought aiming for a 10 pip scalps and hit 100 pips stops loss. Hell, there have been times I was going for 5 pips and hit 100 stop out. This can seem discouraging, but it does mean there must be 1:10 risk:reward pay-off on the other side of these mistakes, and they were mistakes.
If you repeatedly enter and exit at the wrong times, you are making mistakes and probably the same ones over and over again. The market is tricking you! There are specific ways in which price moves that compel people to make these mistakes (I won’t go into this in this post, because it takes too long and this is going to be a long post anyway, but a lot of this is FOMO).
Making mistakes is okay. In fact, as I see it, making mistakes is an essential part of becoming an expert. Making a mistake enough times to understand intrinsically why it is a mistake and then make the required adjustments. Understanding at a deep level why you trade the way you do and why others make the mistakes they do, is an important part of becoming an expert in your chosen area of focus.
I could talk more on these concepts, but to keep the length of the post down, I will crack on to actual examples of trades I look for. Here are my three main criteria. I am looking for tops/bottoms of moves (edge entries). I am looking for 1:3 RR or more potential pay-offs. My strategy assumes that retail trades will lose most of the time. This seems a fair enough assumption. Without meaning to sound too crass about it, smart money will beat dumb money most of the time if the game is base on money. They just will.
So to summarize, I am looking for the points newbies get trapped in bad positions entering into moves too late. From these areas, I am looking for high RR entries.
Setup Examples.
I call this one the “Lightning Bolt correction”, but it is most commonly referred to as a “two leg correction”. I call it a “Lightning Bolt correction” because it looks a bit like one, and it zaps you. If you get it wrong.

https://preview.redd.it/t4whwijse2721.png?width=1326&format=png&auto=webp&s=c9050529c6e2472a3ff9f8e7137bd4a3ee5554cc
Once I see price making the first sell-off move and then begin to rally towards the highs again, I am waiting for a washout spike low. The common trades mistakes I am trading against here is them being too eager to buy into the trend too early and for the to get stopped out/reverse position when it looks like it is making another bearish breakout. Right at that point they panic … literally one candle under there is where I want to be getting in. I want to be buying their stop loss, essentially. “Oh, you don’t want that ...okay, I will have that!”
I need a precise entry. I want to use tiny stops (for big RR) so I need to be cute with entries. For this, I need entry rules. Not just arbitrarily buying the spike out. There are a few moving parts to this that are outside the scope of this post but one of my mains ways is using a fibs extension and looking for reversals just after the 1.61% level. How to draw the fibs is something else that is outside the scope of this but for one simple rule, they can be drawn on the failed new high leg.

https://preview.redd.it/2cd682kve2721.png?width=536&format=png&auto=webp&s=f4d081c9faff49d0976f9ffab260aaed2b570309
I am looking for a few specific things for a prime setup. Firstly, I am looking for the false hope candles, the ones that look like they will reverse the market and let those buying too early get out break-even or even at profit. In this case, you can see the hammer and engulfing candle off the 127 level, then it spikes low in that “stop-hunt” sort of style.
Secondly I want to see it trading just past my entry level (161 ext). This rule has come from nothing other than sheer volume. The amount of times I’ve been stopped out by 1 pip by that little sly final low has gave birth to this rule. I am looking for the market to trade under support in a manner that looks like a new strong breakout. When I see this, I am looking to get in with tiny stops, right under the lows. I will also be using smaller charts at this time and looking for reversal clusters of candles. Things like dojis, inverted hammers etc. These are great for sticking stops under.
Important note, when the lightning bolt correction fails to be a good entry, I expect to see another two legs down. I may look to sell into this area sometimes, and also be looking for buying on another couple legs down. It is important to note, though, when this does not work out, I expect there to be continued momentum that is enough to stop out and reasonable stop level for my entry. Which is why I want to cut quick. If a 10 pips stop will hit, usually a 30 pips stop will too. Bin it and look for the next opportunity at better RR.

https://preview.redd.it/mhkgy35ze2721.png?width=1155&format=png&auto=webp&s=a18278b85b10278603e5c9c80eb98df3e6878232
Another setup I am watching for is harmonic patterns, and I am using these as a multi-purpose indicator. When I see potentially harmonic patterns forming, I am using their completion level as take profits, I do not want to try and run though reversal patterns I can see forming hours ahead of time. I also use them for entering (similar rules of looking for specific entry criteria for small stops). Finally, I use them as a continuation pattern. If the harmonic pattern runs past the area it may have reversed from, there is a high probability that the market will continue to trend and very basic trend following strategies work well. I learned this from being too stubborn sticking with what I thought were harmonic reversals only to be ran over by a trend (seriously, everything I know I know from how it used to make me lose).

https://preview.redd.it/1ytz2431f2721.png?width=1322&format=png&auto=webp&s=983a7f2a91f9195004ad8a2aa2bb9d4d6f128937
A method of spotting these sorts of M/W harmonics is they tend to form after a second spike out leg never formed. When this happens, it gives me a really good idea of where my profit targets should be and where my next big breakout level is. It is worth noting, larger harmonics using have small harmonics inside them (on lower time-frames) and this can be used for dialling in optimum entries. I also use harmonics far more extensively in ranging markets. Where they tend to have higher win rates.
Next setup is the good old fashioned double bottoms/double top/one tick trap sort of setup. This comes in when the market is highly over extended. It has a small sell-off and rallies back to the highs before having a much larger sell-off. This is a more risky trade in that it sells into what looks like trending momentum and can be stopped out more. However, it also pays a high RR when it works, allowing for it to be ran at reduced risk and still be highly profitable when it comes through.

https://preview.redd.it/1bx83776f2721.png?width=587&format=png&auto=webp&s=2c76c3085598ae70f4142d26c46c8d6e9b1c2881
From these sorts of moves, I am always looking for a follow up buy if it forms a lightning bolt sort of setup.
All of these setups always offer 1:3 or better RR. If they do not, you are doing it wrong (and it will be your stop placement that is wrong). This is not to say the target is always 1:3+, sometimes it is best to lock in profits with training stops. It just means that every time you enter, you can potentially have a trade that runs for many times more than you risked. 1:10 RR can be hit in these sorts of setups sometimes. Paying you 20% for 2% risked.
I want to really stress here that what I am doing is trading against small traders mistakes. I am not trying to “beat the market maker”. I am not trying to reverse engineer J.P Morgan’s black boxes. I do not think I am smart enough to gain a worthwhile edge over these traders. They have more money, they have more data, they have better softwares … they are stronger. Me trying to “beat the market maker” is like me trying to beat up Mike Tyson. I might be able to kick him in the balls and feel smug for a few seconds. However, when he gets up, he is still Tyson and I am still me. I am still going to be pummeled.
I’ve seen some people that were fairly bright people going into training courses and coming out dumb as shit. Thinking they somehow are now going to dominate Goldman Sachs because they learned a chart pattern. Get a grip. For real, get a fucking grip. These buzz phrases are marketeering. Realististically, if you want to win in the markets, you need to have an edge over somebody.
I don’t have edges on the banks. If I could find one, they’d take it away from me. Edges work on inefficiencies in what others do that you can spot and they can not. I do not expect to out-think a banks analysis team. I know for damn sure I can out-think a version of me from 5 years ago … and I know there are enough of them in the markets. I look to trade against them. I just look to protect myself from the larger players so they can only hurt me in limited ways. Rather than letting them corner me and beat me to a pulp (in the form of me watching $1,000 drop off my equity because I moved a stop or something), I just let them kick me in the butt as I run away. It hurts a little, but I will be over it soon.
I believe using these principles, these three simple enough edge entry setups, selectiveness (remembering you are trading against the areas people make mistakes, wait for they areas) and measured aggression a person can make impressive compounded gains over a year. I will attempt to demonstrate this by taking an account of under $100 to over $1,000 in a year. I will use max 10% on risk on a position, the risk will scale down as the account size increases. In most cases, 5% risk per trade will be used, so I will be going for 10-20% or so profits. I will be looking only for prime opportunities, so few trades but hard hitting ones when I take them.
I will start trading around the 10th January. Set remind me if you want to follow along. I will also post my investor login details, so you can see the trades in my account in real time. Letting you see when I place my orders and how I manage running positions.
I also think these same principles can be tweaked in such a way it is possible to flip $50 or so into $1,000 in under a month. I’ve done $10 to $1,000 in three days before. This is far more complex in trade management, though. Making it hard to explain/understand and un-viable for many people to copy (it hedges, does not comply with FIFO, needs 1:500 leverage and also needs spreads under half a pip on EURUSD - not everyone can access all they things). I see all too often people act as if this can’t be done and everyone saying it is lying to sell you something. I do not sell signals. I do not sell training. I have no dog in this fight, I am just saying it can be done. There are people who do it. If you dismiss it as impossible; you will never be one of them.
If I try this 10 times with $50, I probably am more likely to make $1,000 ($500 profit) in a couple months than standard ideas would double $500 - I think I have better RR, even though I may go bust 5 or more times. I may also try to demonstrate this, but it is kinda just show-boating, quite honestly. When it works, it looks cool. When it does not, I can go bust in a single day (see example https://www.fxblue.com/users/redditmicroflip).
So I may or may not try and demonstrate this. All this is, is just taking good basic concepts and applying accelerated risk tactics to them and hitting a winning streak (of far less trades than you may think). Once you have good entries and RR optimization in place - there really is no reason why you can not scale these up to do what may people call impossible (without even trying it).
I know there are a lot of people who do not think these things are possible and tend to just troll whenever people talk about these things. There used to be a time when I’d try to explain why I thought the way I did … before I noticed they only cared about telling me why they were right and discussion was pointless. Therefore, when it comes to replies, I will reply to all comments that ask me a question regarding why I think this can be done, or why I done something that I done. If you are commenting just to tell me all the reasons you think I am wrong and you are right, I will probably not reply. I may well consider your points if they are good ones. I just do not entering into discussions with people who already know everything; it serves no purpose.

Edit: Addition.

I want to talk a bit more about using higher percentage of risk than usual. Firstly, let me say that there are good reasons for risk caps that people often cite as “musts”. There are reasons why 2% is considered optimum for a lot of strategies and there are reasons drawing down too much is a really bad thing.
Please do not be ignorant of this. Please do not assume I am, either. In previous work I done, I was selecting trading strategies that could be used for investment. When doing this, my only concern was drawdown metrics. These are essential for professional money management and they are also essential for personal long-term success in trading.
So please do not think I have not thought of these sorts of things Many of the reasons people say these things can’t work are basic 101 stuff anyone even remotely committed to learning about trading learns in their first 6 months. Trust me, I have thought about these concepts. I just never stopped thinking when I found out what public consensus was.
While these 101 rules make a lot of sense, it does not take away from the fact there are other betting strategies, and if you can know the approximate win rate and pay-off of trades, you can have other ways of deriving optimal bet sizes (risk per trade). Using Kelly Criterion, for example, if the pay-off is 1:3 and there is a 75% chance of winning, the optimal bet size is 62.5%. It would be a viable (high risk) strategy to have extremely filtered conditions that looked for just one perfect set up a month, makingover 150% if it was successful.
Let’s do some math on if you can pull that off three months in a row (using 150% gain, for easy math). Start $100. Month two starts $250. Month three $625. Month three ends $1,562. You have won three trades. Can you win three trades in a row under these conditions? I don’t know … but don’t assume no-one can.
This is extremely high risk, let’s scale it down to meet somewhere in the middle of the extremes. Let’s look at 10%. Same thing, 10% risk looking for ideal opportunities. Maybe trading once every week or so. 30% pay-off is you win. Let’s be realistic here, a lot of strategies can drawdown 10% using low risk without actually having had that good a chance to generate 30% gains in the trades it took to do so. It could be argued that trading seldomly but taking 5* the risk your “supposed” to take can be more risk efficient than many strategies people are using.
I am not saying that you should be doing these things with tens of thousands of dollars. I am not saying you should do these things as long term strategies. What I am saying is do not dismiss things out of hand just because they buck the “common knowns”. There are ways you can use more aggressive trading tactics to turn small sums of money into they $1,000s of dollars accounts that you exercise they stringent money management tactics on.
With all the above being said, you do have to actually understand to what extent you have an edge doing what you are doing. To do this, you should be using standard sorts of risks. Get the basics in place, just do not think you have to always be basic. Once you have good basics in place and actually make a bit of money, you can section off profits for higher risk versions of strategies. The basic concepts of money management are golden. For longevity and large funds; learned them and use them! Just don’t forget to think for yourself once you have done that.

Update -

Okay, I have thought this through a bit more and decided I don't want to post my live account investor login, because it has my full name and I do not know who any of you are. Instead, for copying/observing, I will give demo account login (since I can choose any name for a demo).
I will also copy onto a live account and have that tracked via Myfxbook.
I will do two versions. One will be FIFO compliant. It will trade only single trade positions. The other will not be FIFO compliant, it will open trades in batches. I will link up live account in a week or so. For now, if anyone wants to do BETA testing with the copy trader, you can do so with the following details (this is the non-FIFO compliant version).

Account tracking/copying details.

Low-Medium risk.
IC Markets MT4
Account number: 10307003
Investor PW: lGdMaRe6
Server: Demo:01
(Not FIFO compliant)

Valid and Invalid Complaints.
There are a few things that can pop up in copy trading. I am not a n00b when it comes to this, so I can somewhat forecast what these will be. I can kinda predict what sort of comments there may be. Some of these are valid points that if you raise I should (and will) reply to. Some are things outside of the scope of things I can influence, and as such, there is no point in me replying to. I will just cover them all here the one time.

Valid complains are if I do something dumb or dramatically outside of the strategy I have laid out here. won't do these, if I do, you can pitchfork ----E

Examples;

“Oi, idiot! You opened a trade randomly on a news spike. I got slipped 20 pips and it was a shit entry”.
Perfectly valid complaint.

“Why did you open a trade during swaps hours when the spread was 30 pips?”
Also valid.

“You left huge trades open running into the weekend and now I have serious gap paranoia!”
Definitely valid.

These are examples of me doing dumb stuff. If I do dumb stuff, it is fair enough people say things amounting to “Yo, that was dumb stuff”.

Invalid Complains;

“You bought EURUSD when it was clearly a sell!!!!”
Okay … you sell. No-one is asking you to copy my trades. I am not trading your strategy. Different positions make a market.

“You opened a position too big and I lost X%”.
No. Na uh. You copied a position too big. If you are using a trade copier, you can set maximum risk. If you neglect to do this, you are taking 100% risk. You have no valid compliant for losing. The act of copying and setting the risk settings is you selecting your risk. I am not responsible for your risk. I accept absolutely no liability for any losses.
*Suggested fix. Refer to risk control in copy trading software

“You lost X trades in a row at X% so I lost too much”.
Nope. You copied. See above. Anything relating to losing too much in trades (placed in liquid/standard market conditions) is entirely you. I can lose my money. Only you can set it up so you can lose yours. I do not have access to your account. Only mine.
*Suggested fix. Refer to risk control in copy trading software

“Price keeps trading close to the pending limit orders but not filling. Your account shows profits, but mine is not getting them”.
This is brokerage. I have no control over this. I use a strategy that aims for precision, and that means a pip here and there in brokerage spreads can make a difference. I am trading to profit from my trading conditions. I do not know, so can not account for, yours.
* Suggested fix. Compare the spread on your broker with the spread on mine. Adjust your orders accordingly. Buy limit orders will need to move up a little. Sell limit orders should not need adjusted.

“I got stopped out right before the market turned, I have a loss but your account shows a profit”.
This is brokerage. I have no control over this. I use a strategy that aims for precision, and that means a pip here and there differences in brokerage spreads can make a difference. I am trading to profit from my trading conditions. I do not know, so can not account for, yours.
** Suggested fix. Compare the spread on your broker with the spread on mine. Adjust your orders accordingly. Stop losses on sell orders will need to move up a bit. Stops on buy orders will be fine.

“Your trade got stopped out right before the market turned, if it was one more pip in the stop, it would have been a winner!!!”
Yeah. This happens. This is where the “risk” part of “risk:reward” comes in.

“Price traded close to take profit, yours filled but mines never”.
This is brokerage. I have no control over this. I use a strategy that aims for precision, and that means a pip here and there differences in brokerage spreads can make a difference. I am trading to profit from my trading conditions. I do not know, so can not account for, yours.
(Side note, this should not be an issue since when my trade closes, it should ping your account to close, too. You might get a couple less pips).
*** Suggested fix. Compare the spread on your broker with the spread on mine. Adjust your orders accordingly. Take profits on buys will need to move up a bit. Sell take profits will be fine.

“My brokers spread jumped to 20 during the New York session so the open trade made a bigger loss than it should”.
Your broker might just suck if this happens. This is brokerage. I have no control over this. My trades are placed to profit from my brokerage conditions. I do not know, so can not account for yours. Also, if accounting for random spread spikes like this was something I had to do, this strategy would not be a thing. It only works with fair brokerage conditions.
*Suggested fix. Do a bit of Googling and find out if you have a horrific broker. If so, fix that! A good search phrase is; “(Broker name) FPA reviews”.

“Price hit the stop loss but was going really fast and my stop got slipped X pips”.
This is brokerage. I have no control over this. I use a strategy that aims for precision, and that means a pip here and there differences in brokerage spreads can make a difference. I am trading to profit from my trading conditions. I do not know, so can not account for, yours.
If my trade also got slipped on the stop, I was slipped using ECN conditions with excellent execution; sometimes slips just happen. I am doing the most I can to prevent them, but it is a fact of liquidity that sometimes we get slipped (slippage can also work in our favor, paying us more than the take profit would have been).

“Orders you placed failed to execute on my account because they were too large”.
This is brokerage. I have no control over this. Margin requirements vary. I have 1:500 leverage available. I will not always be using it, but I can. If you can’t, this will make a difference.

“Your account is making profits trading things my broker does not have”
I have a full range of assets to trade with the broker I use. Included Forex, indices, commodities and cryptocurrencies. I may or may not use the extent of these options. I can not account for your brokerage conditions.

I think I have covered most of the common ones here. There are some general rules of thumb, though. Basically, if I do something that is dumb and would have a high probability of losing on any broker traded on, this is a valid complain.

Anything that pertains to risk taken in standard trading conditions is under your control.

Also, anything at all that pertains to brokerage variance there is nothing I can do, other than fully brief you on what to expect up-front. Since I am taking the time to do this, I won’t be a punchbag for anything that happens later pertaining to this.

I am not using an elitist broker. You don’t need $50,000 to open an account, it is only $200. It is accessible to most people - brokerage conditions akin to what I am using are absolutely available to anyone in the UK/Europe/Asia (North America, I am not so up on, so can’t say). With the broker I use, and with others. If you do not take the time to make sure you are trading with a good broker, there is nothing I can do about how that affects your trades.

I am using an A book broker, if you are using B book; it will almost certainly be worse results. You have bad costs. You are essentially buying from reseller and paying a mark-up. (A/B book AKA ECN/Market maker; learn about this here). My EURUSD spread will typically be 0.02 pips or so, if yours is 1 pip, this is a huge difference.
These are typical spreads I am working on.

https://preview.redd.it/yc2c4jfpab721.png?width=597&format=png&auto=webp&s=c377686b2485e13171318c9861f42faf325437e1


Check the full range of spreads on Forex, commodities, indices and crypto.

Please understand I want nothing from you if you benefit from this, but I am also due you nothing if you lose. My only term of offering this is that people do not moan at me if they lose money.

I have been fully upfront saying this is geared towards higher risk. I have provided information and tools for you to take control over this. If I do lose people’s money and I know that, I honestly will feel a bit sad about it. However, if you complain about it, all I will say is “I told you that might happen”, because, I am telling you that might happen.

Make clear headed assessments of how much money you can afford to risk, and use these when making your decisions. They are yours to make, and not my responsibility.

Update.

Crazy Kelly Compounding: $100 - $11,000 in 6 Trades.

$100 to $11,000 in 6 trades? Is it a scam? Is it a gamble? … No, it’s maths.

Common sense risk disclaimer: Don’t be a dick! Don’t risk money you can’t afford to lose. Do not risk money doing these things until you can show a regular profit on low risk.
Let’s talk about Crazy Kelly Compounding (CKC). Kelly criterion is a method for selecting optimal bet sizes if the odds and win rate are known (in other words, once you have worked out how to create and assess your edge). You can Google to learn about it in detail. The formula for Kelly criterion is;
((odds-1) * (percentage estimate)) - (1-percent estimate) / (odds-1) X 100
Now let’s say you can filter down a strategy to have a 80% win rate. It trades very rarely, but it had a very high success rate when it does. Let’s say you get 1:2 RR on that trade. Kelly would give you an optimum bet size of about 60% here. So if you win, you win 120%. Losing three trades in a row will bust you. You can still recover from anything less than that, fairly easily with a couple winning trades.
This is where CKC comes in. What if you could string some of these wins together, compounding the gains (so you were risking 60% each time)? What if you could pull off 6 trades in a row doing this?
Here is the math;

https://preview.redd.it/u3u6teqd7c721.png?width=606&format=png&auto=webp&s=3b958747b37b68ec2a769a8368b5cbebfe0e97ff
This shows years, substitute years for trades. 6 trades returns $11,338! This can be done. The question really is if you are able to dial in good enough entries, filter out enough sub-par trades and have the guts to pull the trigger when the time is right. Obviously you need to be willing to take the hit, obviously that hit gets bigger each time you go for it, but the reward to risk ratio is pretty decent if you can afford to lose the money.
We could maybe set something up to do this on cent brokers. So people can do it literally risking a couple dollars. I’d have to check to see if there was suitable spreads etc offered on them, though. They can be kinda icky.
Now listen, I am serious … don’t be a dick. Don’t rush out next week trying to retire by the weekend. What I am showing you is the EXTRA rewards that come with being able to produce good solid results and being able to section off some money for high risk “all or nothing” attempts; using your proven strategies.
I am not saying anyone can open 6 trades and make $11,000 … that is rather improbable. What I am saying is once you can get the strategy side right, and you can know your numbers; then you can use the numbers to see where the limits actually are, how fast your strategy can really go.
This CKC concept is not intended to inspire you to be reckless in trading, it is intended to inspire you to put focus on learning the core skills I am telling you that are behind being able to do this.
submitted by inweedwetrust to Forex [link] [comments]

Shorting Noobs - Purpose of Posts and Consolidation of What We've Covered

Shorting Noobs - Purpose of Posts and Consolidation of What We've Covered
Part [1] [2] [3] [4] [5]
I wanted to take some time to explain my purpose in posting this "Shorting Noobs" series here. In the posts, specifically. I've explained my theory for doing the project itself enough in Q/A in comments.

First let's cover a few things I am not here to do;

1 - Cocaine. Nasty habit.

2 - Undermine, mock or disrespect people new or losing in Forex
I hope this is apparent from my general tone in posts and answering questions. I do not think I am better than you, I know statistically speaking I do this a lot more than most of you. There are things you will be amazing in that I am a noob, it's really only a matter of time and focus. I do not use it as any sort of slur.

3 - Undermine people offering copy trading services
To be honest, I kinda like them. To see how others trade, especially if they do is systematically is fascinating to me. Much can be learned. I value watching people trade higher than airy statements about trading ideals, it gives real information.

4 - Promote Excessive Risk
Although there have been big swings in the strategy, this has not been me trying to ram the virtues of reckless risk down your throat. I recommend it only as part of a balanced diet. The strategy takes a lot of risk because what it is doing (lots of trade data from many sources). Not what I am doing, or suggesting you do.

5 - Sell Anything
I am not marketing any of the strategies I document. You will not be able to get software from me. I do not sell training. Already many people have asked me for training in DMs, and will be able to vouch I have no sales pitch (usually not even a direct answer, just a nudge in the suitable direction).


Now let's talk about what it is about.

I'll do this by sharing a couple DMs I have got.


https://preview.redd.it/oof1l8hm4ci31.png?width=664&format=png&auto=webp&s=532e151f0e9d4d429e1e7e67815b2dd1aec73390

https://preview.redd.it/59k5ug1u4ci31.png?width=681&format=png&auto=webp&s=c0ab733afceab61614313e4379b9a3cac9c4ed12

Firstly, thank you to those who've sent these sorts of messages (if you've messaged me and not heard back in 2 days, please message me again - I'll reply, but keeping up with them is tricky). The fact that when I explain some logical things you can go and test independent of me and come to your own truth on the matter validates this is worth the time and effort. This is what I want you to do. Not believe me. Not buy my hype. Check your own trades against what I highlight.

I think the whole "should I short myself" topic is too long to be included in this post properly. Short answer I'd give is no. There's a far longer one. For brevity, what you should seek to do is understand the triggers for you making losing trades. The triggers for losing entries are also triggers for winning entries. Understand them and re-wire the way you think about the market.

I want to show you that mistakes people make are predictable. I think they are so predictable that I can reduce it to working out what strategy type Timmy is trading, and then "Activate Timmy" at a time I know that strategy is prone to loss, and rack up profits in his drawn down. I also want to show you that what I do does not "break" when there is a news event. It frequently compliments it and my qualifiers foreshadow it.

I want you to understand that as a way to offer you a form of empowerment in the markets. For as long as you believe we are at the whip and whim of these things we can never understand, you're driftwood in the waves. Where others find their excuses, I have found patterns. Where many of you have your frustrations is the root of my fortunes, and I am not smarter than you. I want to stress that. I'm average, but pedantic about precision and this is my job that I do every day.

I will now round up analysis and lessons from posts over the last week or so to consolidate a lesson for you that offers you the chance to instantly improve poor trading results. I'll show you how;

1 - How I explained the type of trading error theoretically.
2 - How I flagged up someone making the trading error in real time.
3 - How I profited from the other side of the trading error, and posted that forecast.

Mistake types:

https://preview.redd.it/cz8wcjna8ci31.png?width=722&format=png&auto=webp&s=55291f94a08c7c75fc240e2a4bbe145fffd6f34b
Full post

We are going to be looking at the area when downtrend turned to correction. We'll used GBPUSD as an example. My post is timestamped, you can see I posted these common mistakes we should look for longer before the GBPUSD price action I will reference. This is not retroactive curve fitting.
Someone posted a sell setup in here on GBPUSD. By up-vote court, trend continuation was the way to go. Unfortunately the poster later deleted their post, so I can not show you specifically the type of analysis they used. I'll say it was good analysis, 2/3 times. This was the 3.
My reply.

https://preview.redd.it/4rubru039ci31.png?width=729&format=png&auto=webp&s=2320150755da871be7bf506db9af34f686c00e3a
Trades

https://preview.redd.it/zzpznz979ci31.png?width=813&format=png&auto=webp&s=c961cc7d427b2753c25c03f345baecee4d9c88ba
Area they posted their sell analysis stating something to the effect the trend was down and there'd been a big correction. We can sell now, it might go up a little more but it's due a drop (I.e, Break&Re-test trade)

https://preview.redd.it/vbvt69lj9ci31.png?width=693&format=png&auto=webp&s=ece654e53d15e0f6412cdc71e71c2899fbc19ea2

I'd call this a foreseeable mistake, and good opportunity to trade the other way when you understand the mistake. That's what I'd describe the mid week action as.

However, word on the street is ...

https://preview.redd.it/h6kvwdknaci31.png?width=703&format=png&auto=webp&s=d7e07d060f714518781a9853be05a09fd41f3ea3
I sure didn't see that coming. Draw your own conclusions.

Following this move, I then posted this analysis. In the analysis I explained the 50/61.8 trap (see [2] [3])

Someone replied this (I'm not "calling out" this person. I hope they take this for what it is, and me just showing what people think vrs what happens, and how this can be 'known').


https://preview.redd.it/vcuftml3bci31.png?width=730&format=png&auto=webp&s=9e75b04752ae9f159dd63fce004d950c84d46fa3
As well as explaining the trap type, the moves to avoid, the scalp possible in the immediate term and sort of price action to expect in a reversal (all just stuff to explain not making selling mistakes on this known mistake area), I also used another strategy to post where the buy for the run to the 61.8 area where be.


https://preview.redd.it/0wmlr6nibci31.png?width=726&format=png&auto=webp&s=dc9af6aaf04028be190ec7abfe177038aac64fa3
Full post https://www.reddit.com/Forex/comments/cu8d23/strategy_to_make_50_100_a_year_trading_one_day_a/

Then I bought at that level, posted we should expect a big pull back and re-load for further swing highs.

https://preview.redd.it/cbi0s2ytbci31.png?width=995&format=png&auto=webp&s=a594c9f3563c235845c40e95ba6d122b29b0c869
Full post https://www.reddit.com/Forex/comments/cufic1/strat_for_50_100_a_year_more_details_first_trade/

I posted my further entries in real time.

https://preview.redd.it/33ymy0p6cci31.png?width=625&format=png&auto=webp&s=95659d006d9e501d0e31c80f0a7e02be68944dd6
Which were profitable.
https://preview.redd.it/4xogetkccci31.png?width=491&format=png&auto=webp&s=100dd5d7344e58f721c37278c29fce6fdb3f0afe
Full post https://www.reddit.com/Forex/comments/cujxgo/strat_for_50_100_a_year_common_points_example_of/

Through all of this, the market went about 10 pips against me in mid week trades, and then under 2 pips against me in all of my trades for today. When I entered, things just worked. Almost as if I 'knew' ... but there's no way that would be possible.
A person could not know on Tuesday what would happen the next days ...

https://preview.redd.it/ralxj9zscci31.png?width=813&format=png&auto=webp&s=33ec9f5fe6557b2e41d04114568043c6eeca55cf
A person could not tell you in the Asia session what to expect hour by hour in the coming trading day ...

https://preview.redd.it/gg09ufizcci31.png?width=742&format=png&auto=webp&s=dd56093469b6ef9c17ae73daf04b1aef7115b876
A person could not draw tomorrows chart ...

https://preview.redd.it/w32v079adci31.png?width=814&format=png&auto=webp&s=01077c65ffbce184f2759957e81343b200fcbf1e

https://preview.redd.it/ef23h3bedci31.png?width=530&format=png&auto=webp&s=3b396b20a18b612ea299bf993f928513cc93f7b7
Full post for all above

And of course, we know above all else ... No one can time the market.

https://preview.redd.it/gnt7wutqdci31.png?width=708&format=png&auto=webp&s=36c60b303a8f69eaeb07140e6f4d8a56193eab42

https://preview.redd.it/tkkzekb2eci31.png?width=713&format=png&auto=webp&s=a816b96eb85d6fdb75ae7b9ac057a3062f88825f


What are the purpose of my posts here?

Just wanted to add a different perspective.
submitted by whatthefx to Forex [link] [comments]

Crypto exchange trade. Remember psychology!

https://medium.com/@sergiygolubyev/crypto-exchange-trade-remember-psychology-6d4433569d9d
Crypto Exchange is a high-tech platform in which all trade transactions are conducted using modern software created based on the latest IT solutions. The emergence of new types of currencies, in particular cryptocurrencies, gives a chance for the rapid development of the world economy as a whole. In turn, structural changes in the international economic system gave impetus to the emergence and development of new types of exchange technologies. Thus, crypto exchanges appeared which allowed its participants anywhere in the world to buy, sell and exchange one cryptocurrency for others, or for fiat of other countries. Each crypto exchange tries to offer customers convenient ways to convert financial instruments, and provides the ability to conduct transactions on its own terms. The high rates of development and distribution of cryptocurrencies, which are based on Blockchain, as well as the gradual wide recognition by the world community and leading economists, ensure the further improvement of exchange technologies. This means that in an effort to provide the most comfortable conditions for its customers, each crypto exchange will take them to an ever-higher quality level of service with innovative nuances. But at the same time, within the framework of the technological process of stock trading, which is available to users (from professional traders to amateurs), the question of psychology and its role in the decision making has not been canceled. Successful trading depends on 70% primarily on the psychology of a trader and only 30% on the trading scheme/strategy.
Trading on the exchange, it is necessary to develop discipline, self-control and be able to respond quickly to changing stock charts. All this will allow you to earn and minimize your losses more effectively. Everyone should remember, from the amateur to the professional, that in the financial markets you can not only earn money, but also lose money. Cryptocurrency rates are still subject to political and regulatory influences; their value is influenced by the reputation of the company's founders, informational insertions about blockchain projects and plans for their further development, scandals and disclosures. Nevertheless, there are simple rules for successful trading from the field of psychology, which will reduce the risks when trying to make money on cryptocurrency and not only. There are a number of problems that always hinder every beginner - amateur:
· Excitement
· Fear
· Greed
· Unwillingness to learn new things
· Imaginary visualization of results
All these problems have psychological aspects. Emotions, feelings and desires significantly influence the trading decisions made by the trader. This happens all the time, not only on traditional exchanges, but also in the cryptocurrency sphere as well. Excitement is an emotional state when it seems to a person that he is lucky, and as the series of successful transactions continues, he performs larger by volume financial transactions. Often, the excitement motivates to turn away from long-term transactions and trends, and look towards short-term operations. After all, it seems that the more often you successfully complete operations, the more capital you earn. Not at all! The more often you make mistakes, leading to a default on your account. Money only is earned on long-term trends and operations. Traders are often worried, fearing an unsuccessful deal closing.
Of course, a loss is bad, but sometimes it is better to close a position in minus than to lose a large amount only because of the hope of a quick price reversal. Therefore, fear often pushes for the wrong strategic decisions. Fear of loss as a result becomes a sentence for your positioning in profit. On the same face with fear, if not strange, is the factor of greed. Having essentially a different source of inspiration, greed, like fear, leads to a generally pitiable result — to the default of your trading account. The reluctance to learn new strategies, technologies, and denial of forecasting also leads to failure. Successful is who always strives to learn new things, and perceives the fact and necessity of continuous learning. Since learning is a process of striving for the progress of its results and professional qualities. Another scourge - Wish list or visualization. Everyone wants to see the price move in the right direction. This is pretty dangerous. By visualizing the price jump in the right direction, you can dream and invest too much in cryptocurrency. This will lead to losses. Here you should always remember to diversify your investments. Remember your psychological portrait even when you program your trading strategies, algorithms and bots. After all, your algorithm is essentially your psychological portrait. Finally, the above-mentioned flaws, especially in the strategy can dominate and damage your deposit and reputation. The main signs of competent crypto-trade are the same as on other exchanges (such as FOREX). This is a kind of algorithm for a sustainable profit strategy:
· Risk no more than 10% of the deposit
· Use risk per trade of 5% or less
· Do not close profitable deals too early
· Do not accumulate losing trades
· Fix quick speculative profit
· Respect the trend
· Pay more attention to liquid assets (cryptocurrency)
· Set your personal entry and exit rules for trades and stick to them
· Long-term trading strategy gives you maximum steady profits
· Do not use the principles of Martingale tactics if there is no experience. You cannot double the volume of the transaction, if it closed in the red zone. If a loss was incurred, then the cryptocurrency market situation was predicted incorrectly and it was necessary to work on improving the analytical skills, and not to conclude a larger deal, which probably also closes in the negative
It is obvious that the psychology of trading significantly affects the performance of stock speculation both in the traditional market and in the field of cryptocurrency. It is important to remember that the success of a person in any field of activity depends on the emotional component, namely the internal balance. Exchange trading is a nervous activity, and if you do not learn to take emotions under control, the results can be disastrous. The basis for achieving success in stock trading, in my opinion, are two fundamental factors. The first factor relates to the field of formulation of the trading idea, and the second - to the area of ​​its implementation.
To formulate a trading idea, on the one hand, methods of technical and fundamental analysis are used to select an exchange instrument and determine the moment of opening and closing a position on it. On the other hand, capital management methods are used to determine the optimal size of the position being opened. As you know, without these two crucial moments it is impossible to achieve stable success in stock trading. As experience shows, for the most part, people have enough intelligence to master all the necessary theoretical knowledge of technical and fundamental analysis in a few months of intensive training. There are no special intellectual difficulties. But, as the same experience shows, this is clearly not enough for successful exchange trading, since all knowledge may turn out to be a useless load if the second success factor is not sufficiently present - the practical implementation of trading ideas, which is no longer based on the intellectual sphere, and psycho-emotional. It is within this area that the main problem arises for many traders, which prevents the receipt of stable profits. As a rule, this is due to the psycho-emotional profile of a person. It depends on how the trader will behave in the psychologically stressful situations that the exchange trading is full of. Inherent in all human emotions and feelings - fear, greed, excitement, envy, hope, etc. very often have a decisive influence on the behavior of traders, not allowing them to follow strictly the trading strategy and plan, even if they have one. From a psychological point of view, the process of stock exchange activity can be divided into stages, after which the trader can return to the starting point. The above scenarios and risk factors are one of the options for the behavior of an exchange speculator; however, it often happens exactly the opposite. Having suffered losses from his first transactions in the market, the trader loses interest in exchange trading, he gives up and he falls into despair. In this case, the first step to victory is the admission of defeat. It would seem silly and ridiculous, but it works. After that, there are two options: either the trader leaves the exchange forever, or returns to the battlefield. Such “returns” may occur more than once. In addition, at some other time, after repeated analysis of his actions, mistakes made and their consequences, a person from a beginner begins to turn into an experienced trader, which is marked by the stability of his activity and, perhaps, by slow, but surely growth of his deposit and profit. The psychological basis for success in trading, which leads to victory and the absence of which is equivalent to defeat, are as follows:
· It is not only the lack of self-control, discipline and focus on the process that causes the defeat
· Self-control, discipline and ability to concentrate is not enough to achieve success
· To achieve success, it is equally important to be able to adapt to changes
In principle, one can consider the idea that traditional approaches to the psychology of trading are limited. In the majority of benefits for traders, the key qualities necessary for successful exchange trading are only self-control and discipline. Of course, these qualities are necessary in any field of business activities. Trading is not an exception, especially considering that it is in the risk zone. But self-control and discipline are not enough to achieve success. Trading is a business. Moreover, any business does not stand still. You cannot find a formula for success and use it forever. You will need to monitor trends and constantly look for new successful solutions.
The main feature of a successful trader is adaptability to changes. The lack of development leads to defeat, large monetary losses. Many technology companies continued to produce stationary computers when laptops became popular. The same companies continued to produce laptops when tablets appeared and became popular. The products of these companies were of high quality, and their employees organized pre-set tasks in an organized manner. But they lost large sums due to the fact that they could not adapt to changes in demand. If we draw a parallel with the sphere of investment, the similarities will become noticeable. The stock market, like any other subject to change. One period is replaced by another. Those methods that allowed achieving success in the previous period can lead to failure in the current. The key concept in stock trading is volatility. The change in this indicates the onset of a new period. When volatility increases, trade becomes more risky. Accordingly, with a decrease in this indicator, the degree of risk during trading operations decreases. With a high level of volatility, trends most often unfold. Strong and weak positions can be swapped out. With a high level of volatility, trends continue for some time. From the foregoing, it should be concluded that market processes and methods during periods of high and low volatility differ strongly. You cannot use the same methods during changing market trends. Often it is the adherence to the previous methods, excessive discipline leads to collapse as well. The fact that the investor was defeated does not mean that he suddenly became morally unstable, unorganized. Trading is trading.
Therefore, we have every right to assert that under the psychology of trade in the markets is meant human preparedness for the risks that inevitably accompany any activity. Trading on the stock exchange is based on the interaction of the three most important components: capital management, analysis, and the psychology of trading (which cannot be considered in conjunction with the other aspects of trading). The psychology of human behavior is a source for understanding what is happening in financial markets. The source for understanding the events occurring in the financial markets and the behavior of traders during exchange trading is the psychology of the human person. Emotions — greed, fear, doubt, hope, a sense of self-preservation — are peculiar to any person in life — are clearly manifested in the hard rhythm of decision-making during the dynamic course of exchange trading (which was partially considered above). Knowledge of the human psychology and their behavioral characteristics must be used to achieve success. The psychology of a trader is formed from a multitude of grains - it is a belief in what one does in the stock market, in one’s actions, in own system of one’s decisions, in trading method. In addition, the psychology of a trader is that one can unload oneself emotionally, one does not accept the intellectual challenge that the stock market carries. On the contrary, becomes restrained, calm when making decisions on operations in the stock market. There are many situations where a trader expresses his attention and focus; he does not disperse it on the tracking of news factors or on the receipt of stimuli from the news agencies. Consequently, the crowd psychology is the factor that makes prices move, therefore, in addition to assessing one's own psychological state, one must be sensitive to changes in the mood of other market participants, move in the flow, not against it, and then success will not take long.
Of course, you can argue that why do I need this psychology? After all, besides creating your own strategies and individual work, some exchanges (including crypto exchanges) allow minimizing risks by following the strategies of experienced traders; this service is called a PAMM account. PAMM provides an opportunity for clients (Subscribers) to follow the trading strategy of experienced and professional traders (Providers). Provider's trading results are publicly available. With the help of the rating of accounts, graphs of profitability and reviews of other traders, you can choose the most suitable Provider and begin to follow his strategy. Again, in this case, the provider is a human with all the ensuing consequences. And psychological aspects are not foreign to professionals as well, including victories and mistakes. The financial market attracts people the possibility of obtaining independence, including financial. A successful trader can live and work in any country in the world without having either a boss or subordinates. The motivation of people on the exchanges can be different: from getting a higher percentage than from a bank to making several thousand dollars a day. At the same time, there are two main categories of people in the financial market (including cryptocurrencies): investors who acquire assets or currency for a relatively long period, and speculators who profit from changes in the prices of certain assets for short periods. Many believe, an easy way to make money is not for everybody. First, the skillful use and manipulation of the psychological aspects of a human make it possible to become a speculator. And this, of course, in addition to knowledge and analytical skills. Experience shows that successful speculation is the right state of mind. It would seem that this is the simplest thing that can be acquired by human. But in fact, this self-tuning is available to very few. It is also necessary to distinguish the psychology of the market and the personal psychology of the trader. The behavior of the market as a whole depends on people, since it is the stock market crowd that determines its direction. However, quite often traders lose sight of the most important component of victory - managing their personal emotions, that is, their psychology. Without control over oneself, there can be no control over one’s trading capital. If a trader is not tuned to the trend range of the stock crowd, if he does not pay attention to changes in her psychology, then he will also not achieve significant success in trading. To succeed on the exchange, one needs to take a sober look at exchange trading, recognize its trends and their changes, and not waste time on dreams or lamenting about failures.
Any price of a financial instrument is a momentary agreement on its value, reached by a market crowd and expressed in the fact of a transaction, i.e. it is the equilibrium point between the players for a rise and a fall, or the "equilibrium" price. Crowds of traders create asset prices: buyers, sellers and fluctuating market watchers. Charts of prices and trading volumes reflect the psychology of the exchange. In addition, this is always worth remembering! After all, the main purpose of the presence of the analysis of psychology in stock trading is not the quantity, but the quality of transactions. A person striving to become a good trader needs to remember the words of DiNapoli, a well-known stock exchange trader: “The most important trading tool is not a computer, not a service for supplying information, or even methods developed by a trader. It is he himself! If a trader is not suitable for this - he should not trade at all”! Therefore, before pushing orders on the trading platform, think about whether you are suitable for this role.
Join chat — https://t.me/joinchat/AAAAAE84vCXg5PK-VpHADg
Sergiy Golubyev (Сергей Голубев)
EU structural funds, ICO projects, NGO & investment projects, project management, comprehensive support of business
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Stock Market Week Ahead for the trading week beginning February 4th, 2019 (News, Earnings, etc.)

Hey what's up stocks! Good morning and happy Sunday to all of you on this subreddit. I hope everyone made out pretty decent last week in the market, and are ready for the new trading week ahead! :)
Here is everything you need to know to get you ready for the trading week beginning February 4th, 2019.

Jobs report removes some fear, but market still in 'tug of war' over how much growth is slowing - (Source)

After January's strong jobs report calmed some recession fears, investors will be picking through the next wave of earnings reports and economic data for clues on just how much the U.S. economy could be slowing.
Dozens of earnings, from companies like Alphabet, Disney and Eli Lily, report in the week ahead, and there are just a few economic reports like trade data and ISM services on Tuesday. Investors will also be watching the outcome of Treasury auctions for $84 billion in Treasury notes and bonds Tuesday through Thursday, after the Fed's dovish tone helped put a lid on interest rates in the past week.
Nearly half the S&P 500 companies had reported for the fourth quarter by Friday morning, and 71 percent beat earnings estimates, while 62 percent have beaten revenue estimates. But earnings growth forecasts for the first quarter continue to decline as more companies report, and they are currently barely breaking even at under 1 percent growth, versus the 15 percent growth in the fourth quarter, according to Refinitiv.
"Granted the more we hear from companies, and particularly in terms of their guidance and projections on revenues, things can slowly change. The first thing companies do is they stop spending money. Cap spending slows down, and if revenue growth does not pick up, they let people go. This is still wait and see," said Quincy Krosby, chief market strategist at Prudential Financial.
Krosby said the 304,000 jobs added in January did ease some concerns about a slowing economy, as did a stronger than expected ISM manufacturing report Friday. But the view of the first quarter is still unclear, as many economic reports were missed during the government shutdown. Economists expect growth in the first quarter of just above 2 percent, after growth of about 2.9 percent in the fourth quarter.
Stocks closed out January with a sharp gain on Thursday, and started February on Friday on a flattish note. The S&P 500 has rebounded about 15 percent from its Dec. 24 closing low. Last month's 7.9 percent gain was the best performance for January in more than 30 years. The old Wall Street adage says 'so goes January, so goes the year.' If that holds, stocks could finish 2019 higher. But February is another story, and on average, it is a flat month for the S&P 500.
"The tug of war that you saw in the market, that was going on in the last half of last year is playing out in the data. Some of the data is a bit lower, but some of the economic surprises are picking up to the upside rather than downside," said Krosby.
Peter Boockvar, chief investment strategist at Bleakley Advisory Group, said the ISM may have improved but it reflected very low exports and flat backlogs, even though there was a snap back in new orders.
"I would fade the jobs report," said Boockvar, noting the level of growth may have been inflated by government workers taking on part-time jobs during the government shutdown.
Boocvkar said the jobs report also looked strong on the surface, but he's concerned the unemployment rate ticked up to 4 percent from 3.9 percent.
"The question of whether we go into a recession or not is how does the stock market affect confidence?" Boockvar said. Confidence readings in the past week were low, and consumer sentiment Friday was its lowest since before President Donald Trump took office.
Krosby said stocks could test recent lows or put in a higher low. If there's a big selloff, "That would not necessarily mean it was a clue a recession is coming. It's just a normal testing mechanism," she said.
The Fed removed a big concern from the markets in the past week, when its post-meeting statement and Fed Chairman Jerome Powell's briefing tilted dovish, assuring markets the Fed would pause in its interest rate hiking. Investors had feared the Fed would hurt the softening economy with its rate hikes. Now, the biggest fears are about the trade war between the U.S. and China and slowing Chinese growth.
The jobs report, and the ISM manufacturing data were also important because the lack of data during the government's 35 day shutdown has left gaps in the economic picture.
"This is really a sign the Fed stole the thunder from the economic data. By saying they're patient plasters over any kind of economic data in the near term, and I suspect the near term lasts through the first quarter because of the government shutdown, the weather, weak GDP," said Marc Chandler, chief market strategist at Bannockburn Global Forex.
Chandler said the markets will be hanging on any news on the trade talks with China. "Even if it's not the all encompassing trade deal we were promised, it's a return to where we were before with China promising to buy energy and farm products. We'll continue to have some kind of talks with the China, like we had under Obama and Bush," said Chandler.

This past week saw the following moves in the S&P:

(CLICK HERE FOR THE FULL S&P TREE MAP FOR THE PAST WEEK!)

Major Indices for this past week:

(CLICK HERE FOR THE MAJOR INDICES FOR THE PAST WEEK!)

Major Futures Markets as of Friday's close:

(CLICK HERE FOR THE MAJOR FUTURES INDICES AS OF FRIDAY!)

Economic Calendar for the Week Ahead:

(CLICK HERE FOR THE FULL ECONOMIC CALENDAR FOR THE WEEK AHEAD!)

Sector Performance WTD, MTD, YTD:

(CLICK HERE FOR FRIDAY'S PERFORMANCE!)
(CLICK HERE FOR THE WEEK-TO-DATE PERFORMANCE!)
(CLICK HERE FOR THE MONTH-TO-DATE PERFORMANCE!)
(CLICK HERE FOR THE 3-MONTH PERFORMANCE!)
(CLICK HERE FOR THE YEAR-TO-DATE PERFORMANCE!)
(CLICK HERE FOR THE 52-WEEK PERFORMANCE!)

Percentage Changes for the Major Indices, WTD, MTD, QTD, YTD as of Friday's close:

(CLICK HERE FOR THE CHART!)

S&P Sectors for the Past Week:

(CLICK HERE FOR THE CHART!)

Major Indices Pullback/Correction Levels as of Friday's close:

(CLICK HERE FOR THE CHART!)

Major Indices Rally Levels as of Friday's close:

(CLICK HERE FOR THE CHART!)

Most Anticipated Earnings Releases for this week:

(CLICK HERE FOR THE CHART!)

Here are the upcoming IPO's for this week:

(CLICK HERE FOR THE CHART!)

Friday's Stock Analyst Upgrades & Downgrades:

(CLICK HERE FOR CHART LINK #1!)
(CLICK HERE FOR CHART LINK #2!)

Now What?

What a year it has been. After the worst December for stocks in 87 years that contributed to the worst fourth quarter since the 2008–09 financial crisis, stocks have bounced back in spectacular fashion. In fact, with a day to go, stocks are looking at their best first month of the year in 30 years.
What could happen next? “We like to say that the easy 10% has been made off the lows and the next 10% will be much tougher,” explained LPL Senior Market Strategist Ryan Detrick. “Things like Fed policy, China uncertainty, and overall global growth concerns all will play a part in where equity markets go from here.”
With the S&P 500 Index about 10% away from new highs, we do think new highs are quite possible at some point this year. Positive news from the Federal Reserve (Fed) and China trade talks, as well as the realization by investors that the odds of a recession in 2019 are quite low could spark potential new highs. Remember, fiscal spending as a percentage of overall gross domestic product (GDP) is higher this year than it was last year. Many think the tax cut and fiscal policies in play last year were a one-time sugar high. We don’t see it that way and expect the benefits from fiscal policy to help extend this economic cycle at least another year—likely more.
As we head into February, note that it hasn’t been one of the best months for stocks. In fact, as our LPL Chart of the Day shows, since 1950, February has been virtually flat, and over the past 20 years only June and September have shown worse returns. Overall, the market gains have been quite impressive since the December 24 lows, but we wouldn’t be surprised at all to see a near-term consolidation or pullback.
(CLICK HERE FOR THE CHART!)

A Fed Pause and the Flattening Yield Curve

Investors have increasingly positioned for a Federal Reserve (Fed) pause, which could portend a shift in fixed income markets. Fed fund futures are pricing in about a 70% probability that the Fed will keep rates unchanged for the rest of 2019, and the market’s dovish tilt has weighed on short-term rates.
As shown in the LPL Chart of the Day, the 2-year yield has typically followed the fed funds rate since policymakers began raising rates in December 2015. While we expect one or two more hikes this cycle, there is a possibility that the Fed’s December hike was its last, which will likely cap short-term rates.
(CLICK HERE FOR THE CHART!)
Short-term yields have outpaced longer-term yields over the past few years, flattening the yield curve and raising concerns that U.S. economic progress may not be able to keep up with the Fed’s tightening. The spread between the 2-year and 10-year yield has fallen negative before every single U.S. recession since 1970.
If the Fed pauses, the curve will likely reverse course and steepen as solid economic growth and quickening (but manageable) inflation drives longer-term yields higher. As mentioned in our Outlook 2019, FUNDAMENTAL: How to Focus on What Really Matters in the Markets, we’re forecasting the 10-year Treasury yield will increase significantly from current levels and trade within a range of 3.25–3.75% in 2019.
“We remain optimistic about U.S. economic growth prospects, and recent data show inflation remains at manageable levels,” said LPL Research Chief Investment Strategist John Lynch. “Because of this, we expect the data-dependent Fed to be less aggressive than initially feared, as policymakers juggle these factors with the impacts of trade tensions and tepid global growth.”
To be clear, investors shouldn’t fear a flattening yield curve given the backdrop of solid economic growth and modest inflation. Historically, the yield curve has remained relatively flat or inverted for years before some recessions started. Since 1970, the United States has entered a recession an average of 21 months after the yield curve inverted.

Jobless Claims’ Historic Significance

Jobless claims have dropped to a 49-year low. Based on historical trends, this could signal that a U.S. economic recession is further off than many expect.
Data released January 24 showed jobless claims fell to 199K in the week ending January 18, the lowest number since 1969 and far below consensus estimates of 218K. As shown in the LPL Chart of the Day, current jobless claims have been significantly lower than those in the 12-month periods preceding each recession since the early 1970s.
(CLICK HERE FOR THE CHART!)
Jobless claims have fallen out of the spotlight as the economic cycle has matured, but they could prove important again as investors’ recessionary fears increase. While most labor-market data serve as lagging indicators of U.S. economic health, jobless claims are a leading indicator. Historically, a 75–100K increase in claims over a 26-week period has been associated with a recession.
“Last week’s jobless claims print was particularly impressive given the partial government shutdown and weakening corporate sentiment,” said LPL Research Chief Investment Strategist John Lynch. “The U.S. labor market remains strong and will help buoy consumer health and output growth this year.”
Other predictive data sets have signaled U.S. recessionary odds are low. Data last week showed the Conference Board’s Leading Economic Index (LEI), based on 10 leading economic indicators (like jobless claims, manufacturers’ new orders, and stock prices), grew 4.3% year over year in December. In contrast, the LEI has turned negative year over year before all economic recessions since 1970. Because of its solid predictive ability, the LEI is a component of our Recession Watch Dashboard.

Best S&P January Since 1987

Most major U.S. stock indexes rallied to new recovery and year-to-date highs today shrugging off some misses and weakness from Microsoft, DuPont and Visa. S&P 500 finished the month strong with a 7.9% gain. This is the best S&P January since 1987. This is also the third January Trifecta in a row.
Last year the S&P 500 crumbled in the fourth quarter under the weight of triple threats from a hawkish and confusing Fed, a newly divided Congress and the U.S. trade battle with China, finishing in the red. 2017’s Trifecta was followed by a full-year gain of 19.4%, including a February-December gain of 17.3%. As you can see in the table below, the long term track record of the Trifecta is rather impressive, posting full-year gains in 27 of the 30 prior years with an average gain for the S&P 500 of 17.1%.
Devised by Yale Hirsch in 1972, the January Barometer has registered ten major errors since 1950 for an 85.5% accuracy ratio. This indicator adheres to propensity that as the S&P 500 goes in January, so goes the year. Of the ten major errors Vietnam affected 1966 and 1968. 1982 saw the start of a major bull market in August. Two January rate cuts and 9/11 affected 2001.The market in January 2003 was held down by the anticipation of military action in Iraq. The second worst bear market since 1900 ended in March of 2009 and Federal Reserve intervention influenced 2010 and 2014. In 2016, DJIA slipped into an official Ned Davis bear market in January. Including the eight flat years yields a .739 batting average.
Our January Indicator Trifecta combines the Santa Claus Rally, the First Five Days Early Warning System and our full-month January Barometer. The predicative power of the three is considerably greater than any of them alone; we have been rather impressed by its forecasting prowess. This is the 31st time since 1949 that all three January Indicators have been positive and the twelfth time (previous eleven times highlighted in grey in table below) this has occurred in a pre-election year.
(CLICK HERE FOR THE CHART!)
With the Fed turning more dovish and President Trump tacking to the center and meeting with China and market internals improving along with the gains, the market is tracking Base Case and Best Case scenarios outlined in our 2019 Annual Forecast. Next eleven month and full-year 2019 performance is expected to be more in line with typical Pre-Election returns.

February Almanac: Small-Caps Tend to Outperform

Even though February is right in the middle of the Best Six Months, its long-term track record, since 1950, is not all that stellar. February ranks no better than seventh and has posted paltry average gains except for the Russell 2000. Small cap stocks, benefiting from “January Effect” carry over; tend to outpace large cap stocks in February. The Russell 2000 index of small cap stocks turns in an average gain of 1.1% in February since 1979—just the seventh best month for that benchmark.
In pre-election years, February’s performance generally improves with average returns all positive. NASDAQ performs best, gaining an average 2.8% in pre-election-year Februarys since 1971. Russell 2000 is second best, averaging gains of 2.5% since 1979. DJIA, S&P 500 and Russell 1000, the large-cap indices, tend to lag with average advances of around 1.0%.
(CLICK HERE FOR THE CHART!)

5% Months

7%? Bulls will take it! After an abysmal December, the S&P 500 is currently set to finish the month with its best January return since 1987. This month’s gain will mark the 16th time since the lows of the Financial Crisis in March 2009 that the S&P 500 has rallied more than 5% in a given month. The table below highlights each of the 15 prior months where the S&P 500 rallied more than 5% and shows how much the S&P 500 gained on the month as well as its performance on the last trading day of the month and the first trading day of the subsequent month.
When looking at the table, a few things stand out. First, the first trading day of a month that follows a month where the S&P 500 rallied more than 5% has been extremely positive as the S&P 500 averages a gain of 0.84% (median: 1.01%) with positive returns 13 out of 15 times! In addition to the positive tendency of markets on the first day of the new month, there has also been a clear tendency for the S&P 500 to decline on the last trading day of the strong month. The average decline on the last trading day of a strong month has been 0.09% with positive returns less than half of the time. This is no doubt related to the fact that funds are forced to rebalance out of equities to get back inline with their benchmark weights. However, on those five prior months where the S&P 500 bucked the trend and was positive on the last trading day of a 5%+ month, the average gain on the first trading day of the next month was even stronger at 1.52% with gains five out of six times.
(CLICK HERE FOR THE CHART!)

STOCK MARKET VIDEO: Stock Market Analysis Video for February 1st, 2019

([CLICK HERE FOR THE YOUTUBE VIDEO!]())
(VIDEO NOT YET UP!)

STOCK MARKET VIDEO: ShadowTrader Video Weekly 2.3.19

([CLICK HERE FOR THE YOUTUBE VIDEO!]())
(VIDEO NOT YET UP!)
Here are the most notable companies reporting earnings in this upcoming trading month ahead-
  • $GOOGL
  • $TWTR
  • $SNAP
  • $CLF
  • $TTWO
  • $ALXN
  • $DIS
  • $BP
  • $CLX
  • $SYY
  • $GM
  • $GILD
  • $CMG
  • $GRUB
  • $EA
  • $STX
  • $SPOT
  • $AMG
  • $SAIA
  • $RL
  • $CNC
  • $EL
  • $UFI
  • $GLUU
  • $MTSC
  • $JOUT
  • $PM
  • $GPRO
  • $LITE
  • $FEYE
  • $SWKS
  • $LLY
  • $MPC
  • $BDX
  • $REGN
  • $VIAB
  • $ONVO
  • $HUM
  • $ARRY
  • $PBI
  • $ADM
  • $BSAC
(CLICK HERE FOR NEXT WEEK'S MOST NOTABLE EARNINGS RELEASES!)
(CLICK HERE FOR NEXT WEEK'S HIGHEST VOLATILITY EARNINGS RELEASES!)
(CLICK HERE FOR NEXT WEEK'S BIGGEST DECLINE IN EARNINGS EXPECTATIONS!)
(CLICK HERE FOR NEXT WEEK'S HIGHEST INCREASE IN EARNINGS EXPECTATIONS!)
Below are some of the notable companies coming out with earnings releases this upcoming trading week ahead which includes the date/time of release & consensus estimates courtesy of Earnings Whispers:

Monday 2.4.19 Before Market Open:

(CLICK HERE FOR MONDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES!)

Monday 2.4.19 After Market Close:

(CLICK HERE FOR MONDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES!)

Tuesday 2.5.19 Before Market Open:

(CLICK HERE FOR TUESDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES LINK #1!)
(CLICK HERE FOR TUESDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES LINK #2!)

Tuesday 2.5.19 After Market Close:

(CLICK HERE FOR TUESDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #1!)
(CLICK HERE FOR TUESDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #2!)

Wednesday 2.6.19 Before Market Open:

(CLICK HERE FOR WEDNESDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES!)

Wednesday 2.6.19 After Market Close:

(CLICK HERE FOR WEDNESDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #1!)
(CLICK HERE FOR WEDNESDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #2!)

Thursday 2.7.19 Before Market Open:

(CLICK HERE FOR THURSDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES LINK #1!)
(CLICK HERE FOR THURSDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES LINK #1!)

Thursday 2.7.19 After Market Close:

(CLICK HERE FOR THURSDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #1!)
(CLICK HERE FOR THURSDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES LINK #2!)

Friday 2.8.19 Before Market Open:

(CLICK HERE FOR FRIDAY'S PRE-MARKET EARNINGS TIME & ESTIMATES!)

Friday 2.8.19 After Market Close:

([CLICK HERE FOR FRIDAY'S AFTER-MARKET EARNINGS TIME & ESTIMATES!]())
NONE.

Alphabet, Inc. -

Alphabet, Inc. (GOOGL) is confirmed to report earnings at approximately 4:05 PM ET on Monday, February 4, 2019. The consensus earnings estimate is $11.08 per share on revenue of $31.28 billion and the Earnings Whisper ® number is $11.03 per share. Investor sentiment going into the company's earnings release has 71% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 14.23% with revenue decreasing by 3.23%. Short interest has decreased by 6.6% since the company's last earnings release while the stock has drifted higher by 6.7% from its open following the earnings release to be 0.7% below its 200 day moving average of $1,127.05. Overall earnings estimates have been revised lower since the company's last earnings release. On Thursday, January 24, 2019 there was some notable buying of 1,493 contracts of the $1,200.00 call expiring on Friday, February 15, 2019. Option traders are pricing in a 5.2% move on earnings and the stock has averaged a 3.8% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Twitter, Inc. $33.19

Twitter, Inc. (TWTR) is confirmed to report earnings at approximately 7:00 AM ET on Thursday, February 7, 2019. The consensus earnings estimate is $0.25 per share on revenue of $871.59 million and the Earnings Whisper ® number is $0.29 per share. Investor sentiment going into the company's earnings release has 73% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 38.89% with revenue increasing by 19.14%. Short interest has decreased by 54.7% since the company's last earnings release while the stock has drifted higher by 6.0% from its open following the earnings release to be 3.1% below its 200 day moving average of $34.24. Overall earnings estimates have been revised higher since the company's last earnings release. On Monday, December 31, 2018 there was some notable buying of 45,575 contracts of the $34.00 call expiring on Friday, March 15, 2019. Option traders are pricing in a 13.4% move on earnings and the stock has averaged a 13.9% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Snap Inc. $6.91

Snap Inc. (SNAP) is confirmed to report earnings at approximately 4:10 PM ET on Tuesday, February 5, 2019. The consensus estimate is for a loss of $0.08 per share on revenue of $376.64 million and the Earnings Whisper ® number is ($0.04) per share. Investor sentiment going into the company's earnings release has 31% expecting an earnings beat The company's guidance was for revenue of $355.00 million to $380.00 million. Consensus estimates are for year-over-year earnings growth of 27.27% with revenue increasing by 31.83%. Short interest has decreased by 1.8% since the company's last earnings release while the stock has drifted higher by 12.7% from its open following the earnings release to be 33.6% below its 200 day moving average of $10.40. Overall earnings estimates have been revised higher since the company's last earnings release. On Thursday, January 3, 2019 there was some notable buying of 29,739 contracts of the $7.00 call expiring on Friday, February 15, 2019. Option traders are pricing in a 15.7% move on earnings and the stock has averaged a 19.2% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Cleveland-Cliffs Inc $10.53

Cleveland-Cliffs Inc (CLF) is confirmed to report earnings at approximately 8:00 AM ET on Friday, February 8, 2019. The consensus earnings estimate is $0.57 per share on revenue of $713.61 million and the Earnings Whisper ® number is $0.63 per share. Investor sentiment going into the company's earnings release has 87% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 119.23% with revenue increasing by 18.76%. Short interest has increased by 4.6% since the company's last earnings release while the stock has drifted lower by 9.8% from its open following the earnings release to be 11.2% above its 200 day moving average of $9.47. Overall earnings estimates have been revised lower since the company's last earnings release. On Monday, January 7, 2019 there was some notable buying of 10,030 contracts of the $8.00 call expiring on Thursday, April 18, 2019. Option traders are pricing in a 9.4% move on earnings and the stock has averaged a 7.0% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Take-Two Interactive Software, Inc. $104.95

Take-Two Interactive Software, Inc. (TTWO) is confirmed to report earnings at approximately 7:00 AM ET on Wednesday, February 6, 2019. The consensus earnings estimate is $2.72 per share on revenue of $1.46 billion and the Earnings Whisper ® number is $2.82 per share. Investor sentiment going into the company's earnings release has 84% expecting an earnings beat The company's guidance was for earnings of $0.31 to $0.41 per share. Consensus estimates are for year-over-year earnings growth of 106.06% with revenue increasing by 203.64%. Short interest has increased by 37.1% since the company's last earnings release while the stock has drifted lower by 18.7% from its open following the earnings release to be 9.9% below its 200 day moving average of $116.52. Overall earnings estimates have been revised higher since the company's last earnings release. On Wednesday, January 23, 2019 there was some notable buying of 2,067 contracts of the $120.00 call expiring on Friday, February 15, 2019. Option traders are pricing in a 9.2% move on earnings and the stock has averaged a 8.3% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Alexion Pharmaceuticals, Inc. $126.28

Alexion Pharmaceuticals, Inc. (ALXN) is confirmed to report earnings at approximately 6:35 AM ET on Monday, February 4, 2019. The consensus earnings estimate is $1.82 per share on revenue of $1.06 billion and the Earnings Whisper ® number is $1.95 per share. Investor sentiment going into the company's earnings release has 67% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 23.81% with revenue increasing by 16.52%. Short interest has decreased by 16.7% since the company's last earnings release while the stock has drifted higher by 0.4% from its open following the earnings release to be 5.8% above its 200 day moving average of $119.40. On Friday, February 1, 2019 there was some notable buying of 1,235 contracts of the $130.00 call expiring on Friday, February 15, 2019. Option traders are pricing in a 7.8% move on earnings and the stock has averaged a 6.5% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Walt Disney Co $111.30

Walt Disney Co (DIS) is confirmed to report earnings at approximately 4:05 PM ET on Tuesday, February 5, 2019. The consensus earnings estimate is $1.57 per share on revenue of $15.18 billion and the Earnings Whisper ® number is $1.62 per share. Investor sentiment going into the company's earnings release has 71% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 16.93% with revenue decreasing by 1.11%. Short interest has increased by 7.2% since the company's last earnings release while the stock has drifted lower by 5.8% from its open following the earnings release to be 1.9% above its 200 day moving average of $109.22. Overall earnings estimates have been revised lower since the company's last earnings release. On Friday, February 1, 2019 there was some notable buying of 8,822 contracts of the $110.00 put expiring on Friday, February 8, 2019. Option traders are pricing in a 3.1% move on earnings and the stock has averaged a 2.2% move in recent quarters.

(CLICK HERE FOR THE CHART!)

BP p.l.c $41.34

BP p.l.c (BP) is confirmed to report earnings at approximately 5:25 AM ET on Tuesday, February 5, 2019. The consensus earnings estimate is $0.77 per share on revenue of $60.72 billion and the Earnings Whisper ® number is $0.75 per share. Investor sentiment going into the company's earnings release has 65% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 20.31% with revenue decreasing by 13.28%. Short interest has increased by 6.5% since the company's last earnings release while the stock has drifted lower by 1.6% from its open following the earnings release to be 3.9% below its 200 day moving average of $43.01. Overall earnings estimates have been revised lower since the company's last earnings release. On Thursday, January 17, 2019 there was some notable buying of 2,010 contracts of the $33.00 put expiring on Friday, January 17, 2020. Option traders are pricing in a 3.3% move on earnings and the stock has averaged a 2.1% move in recent quarters.

(CLICK HERE FOR THE CHART!)

Clorox Co. $149.86

Clorox Co. (CLX) is confirmed to report earnings at approximately 6:30 AM ET on Monday, February 4, 2019. The consensus earnings estimate is $1.32 per share on revenue of $1.48 billion and the Earnings Whisper ® number is $1.34 per share. Investor sentiment going into the company's earnings release has 63% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 7.32% with revenue increasing by 4.52%. Short interest has decreased by 9.8% since the company's last earnings release while the stock has drifted higher by 3.5% from its open following the earnings release to be 5.9% above its 200 day moving average of $141.57. Overall earnings estimates have been revised lower since the company's last earnings release. On Friday, January 18, 2019 there was some notable buying of 1,025 contracts of the $152.50 put expiring on Friday, February 8, 2019. Option traders are pricing in a 4.7% move on earnings and the stock has averaged a 3.3% move in recent quarters.

(CLICK HERE FOR THE CHART!)

SYSCO Corp. $63.57

SYSCO Corp. (SYY) is confirmed to report earnings at approximately 8:00 AM ET on Monday, February 4, 2019. The consensus earnings estimate is $0.72 per share on revenue of $14.85 billion and the Earnings Whisper ® number is $0.73 per share. Investor sentiment going into the company's earnings release has 63% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 9.09% with revenue increasing by 3.04%. Short interest has decreased by 1.0% since the company's last earnings release while the stock has drifted lower by 2.0% from its open following the earnings release to be 5.6% below its 200 day moving average of $67.34. Overall earnings estimates have been revised lower since the company's last earnings release. On Friday, February 1, 2019 there was some notable buying of 1,691 contracts of the $66.00 call expiring on Friday, February 8, 2019. Option traders are pricing in a 4.5% move on earnings and the stock has averaged a 4.8% move in recent quarters.

(CLICK HERE FOR THE CHART!)

DISCUSS!

What are you all watching for in this upcoming trading week ahead?
Have a fantastic Sunday and a great trading week ahead to all here on stocks! ;)
submitted by bigbear0083 to stocks [link] [comments]

Invacio versus the world

British born entrepreneur William West is set to go “toe to toe” with major institutions around the world with his, one of a kind, applied artificial intelligence organisation Invacio. Created over the last 5 years William’s brainchild is far more than your average chatbot or sentiment scraper creating tech company. In point of fact it is such a powerful system that Invacio were invited to make their inaugural presentation in front of the United Nations during a UNESCAP FDI meeting in Thailand last year.
The main elements that have made the elite sit up and take notice are Invacio’s flexibility and shere data processing capabilities. When you have a system that is plugged into thousands upon thousands of data sources with the capacity to analyse and correlate everything from historical market exchange data, and live news feeds with satellite data, and social media interactions, to formulate comprehensive reports and predictions for virtually any industry on earth, it tends to make an impact when people become aware of it.
Data crunching leviathans are ten a penny, in this day and age, so what is so unique about invacio that world leaders invite them to elaborate the details in front of them? That is the secret sauce: a multi agent deep neural network that constantly learns from the data coming in and its own self created distinct datasets. A system that is aware enough of its own data requirements that it literally sourced its own hacking software to gain access to some data it really wanted to see (that got shut down immediately and new rules were implemented “no entry means no entry”).
Wealth generation and crisis management were two of the areas explored during the initial UN presentation and since then further, more detailed, discussions have continued behind closed doors.
First off the bat the sector which is going to feel the full force of Invacio, muscling its way in, is the finance sector, initially they will be putting “Agnes” into the ring. A subscription based service which monitors 2995 stocks/shares and the main forex pairs, Agnes will provide highly accurate short term price predictions to whomever pays the fees be that professionals looking to get ahead of the game or hobbyist day traders looking to put a lump sum away for their future. With accuracy levels regularly running between 92 & 98% on any given trade, with the correct type of equity management trading might just become fun again, even during downturns.
Next up will be an onslaught to capture institutional money through the application of AI directly into the hedge fund market, Aquila, Archimedes and Tomahawk are the names given to these funds. Archimedes will be a human/AI hybrid fund that applies predictions made by Agnes and actioned by a human fund manager. In a 16 week experiment, with real money, Archimedes showed growth of 79%. Tomahawk is a long term forecasting system which looks anywhere from 6 months to 2 years into the future. Aquila will be a combination of all of these with the addition of invacio’s full market oversight (all commodities, shares, indices and forex pairs)
Other markets that will feel the wrath of Invacio are, Market intelligence, communications, social networking, data provision and Global security but they are a different story altogether.
Invacio are currently undergoing an ICO (initial coin offering) in order to fund the roll out of Their various divisions. The coins sold during the sale will be directly connected to the use of Invacios products find out more here www.invest.invacio.com
submitted by InvacioOfficial to u/InvacioOfficial [link] [comments]

Subreddit Stats: cs7646_fall2017 top posts from 2017-08-23 to 2017-12-10 22:43 PDT

Period: 108.98 days
Submissions Comments
Total 999 10425
Rate (per day) 9.17 95.73
Unique Redditors 361 695
Combined Score 4162 17424

Top Submitters' Top Submissions

  1. 296 points, 24 submissions: tuckerbalch
    1. Project 2 Megathread (optimize_something) (33 points, 475 comments)
    2. project 3 megathread (assess_learners) (27 points, 1130 comments)
    3. For online students: Participation check #2 (23 points, 47 comments)
    4. ML / Data Scientist internship and full time job opportunities (20 points, 36 comments)
    5. Advance information on Project 3 (19 points, 22 comments)
    6. participation check #3 (19 points, 29 comments)
    7. manual_strategy project megathread (17 points, 825 comments)
    8. project 4 megathread (defeat_learners) (15 points, 209 comments)
    9. project 5 megathread (marketsim) (15 points, 484 comments)
    10. QLearning Robot project megathread (12 points, 691 comments)
  2. 278 points, 17 submissions: davebyrd
    1. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes (37 points, 10 comments)
    2. Project 1 Megathread (assess_portfolio) (34 points, 466 comments)
    3. marketsim grades are up (25 points, 28 comments)
    4. Midterm stats (24 points, 32 comments)
    5. Welcome to CS 7646 MLT! (23 points, 132 comments)
    6. How to interact with TAs, discuss grades, performance, request exceptions... (18 points, 31 comments)
    7. assess_portfolio grades have been released (18 points, 34 comments)
    8. Midterm grades posted to T-Square (15 points, 30 comments)
    9. Removed posts (15 points, 2 comments)
    10. assess_portfolio IMPORTANT README: about sample frequency (13 points, 26 comments)
  3. 118 points, 17 submissions: yokh_cs7646
    1. Exam 2 Information (39 points, 40 comments)
    2. Reformat Assignment Pages? (14 points, 2 comments)
    3. What did the real-life Michael Burry have to say? (13 points, 2 comments)
    4. PSA: Read the Rubric carefully and ahead-of-time (8 points, 15 comments)
    5. How do I know that I'm correct and not just lucky? (7 points, 31 comments)
    6. ML Papers and News (7 points, 5 comments)
    7. What are "question pools"? (6 points, 4 comments)
    8. Explanation of "Regression" (5 points, 5 comments)
    9. GT Github taking FOREVER to push to..? (4 points, 14 comments)
    10. Dead links on the course wiki (3 points, 2 comments)
  4. 67 points, 13 submissions: harshsikka123
    1. To all those struggling, some words of courage! (20 points, 18 comments)
    2. Just got locked out of my apartment, am submitting from a stairwell (19 points, 12 comments)
    3. Thoroughly enjoying the lectures, some of the best I've seen! (13 points, 13 comments)
    4. Just for reference, how long did Assignment 1 take you all to implement? (3 points, 31 comments)
    5. Grade_Learners Taking about 7 seconds on Buffet vs 5 on Local, is this acceptable if all tests are passing? (2 points, 2 comments)
    6. Is anyone running into the Runtime Error, Invalid DISPLAY variable when trying to save the figures as pdfs to the Buffet servers? (2 points, 9 comments)
    7. Still not seeing an ML4T onboarding test on ProctorTrack (2 points, 10 comments)
    8. Any news on when Optimize_Something grades will be released? (1 point, 1 comment)
    9. Baglearner RMSE and leaf size? (1 point, 2 comments)
    10. My results are oh so slightly off, any thoughts? (1 point, 11 comments)
  5. 63 points, 10 submissions: htrajan
    1. Sample test case: missing data (22 points, 36 comments)
    2. Optimize_something test cases (13 points, 22 comments)
    3. Met Burt Malkiel today (6 points, 1 comment)
    4. Heads up: Dataframe.std != np.std (5 points, 5 comments)
    5. optimize_something: graph (5 points, 29 comments)
    6. Schedule still reflecting shortened summer timeframe? (4 points, 3 comments)
    7. Quick clarification about InsaneLearner (3 points, 8 comments)
    8. Test cases using rfr? (3 points, 5 comments)
    9. Input format of rfr (2 points, 1 comment)
    10. [Shameless recruiting post] Wealthfront is hiring! (0 points, 9 comments)
  6. 62 points, 7 submissions: swamijay
    1. defeat_learner test case (34 points, 38 comments)
    2. Project 3 test cases (15 points, 27 comments)
    3. Defeat_Learner - related questions (6 points, 9 comments)
    4. Options risk/reward (2 points, 0 comments)
    5. manual strategy - you must remain in the position for 21 trading days. (2 points, 9 comments)
    6. standardizing values (2 points, 0 comments)
    7. technical indicators - period for moving averages, or anything that looks past n days (1 point, 3 comments)
  7. 61 points, 9 submissions: gatech-raleighite
    1. Protip: Better reddit search (22 points, 9 comments)
    2. Helpful numpy array cheat sheet (16 points, 10 comments)
    3. In your experience Professor, Mr. Byrd, which strategy is "best" for trading ? (12 points, 10 comments)
    4. Industrial strength or mature versions of the assignments ? (4 points, 2 comments)
    5. What is the correct (faster) way of doing this bit of pandas code (updating multiple slice values) (2 points, 10 comments)
    6. What is the correct (pythonesque?) way to select 60% of rows ? (2 points, 11 comments)
    7. How to get adjusted close price for funds not publicly traded (TSP) ? (1 point, 2 comments)
    8. Is there a way to only test one or 2 of the learners using grade_learners.py ? (1 point, 10 comments)
    9. OMS CS Digital Career Seminar Series - Scott Leitstein recording available online? (1 point, 4 comments)
  8. 60 points, 2 submissions: reyallan
    1. [Project Questions] Unit Tests for assess_portfolio assignment (58 points, 52 comments)
    2. Financial data, technical indicators and live trading (2 points, 8 comments)
  9. 59 points, 12 submissions: dyllll
    1. Please upvote helpful posts and other advice. (26 points, 1 comment)
    2. Books to further study in trading with machine learning? (14 points, 9 comments)
    3. Is Q-Learning the best reinforcement learning method for stock trading? (4 points, 4 comments)
    4. Any way to download the lessons? (3 points, 4 comments)
    5. Can a TA please contact me? (2 points, 7 comments)
    6. Is the vectorization code from the youtube video available to us? (2 points, 2 comments)
    7. Position of webcam (2 points, 15 comments)
    8. Question about assignment one (2 points, 5 comments)
    9. Are udacity quizzes recorded? (1 point, 2 comments)
    10. Does normalization of indicators matter in a Q-Learner? (1 point, 7 comments)
  10. 56 points, 2 submissions: jan-laszlo
    1. Proper git workflow (43 points, 19 comments)
    2. Adding you SSH key for password-less access to remote hosts (13 points, 7 comments)
  11. 53 points, 1 submission: agifft3_omscs
    1. [Project Questions] Unit Tests for optimize_something assignment (53 points, 94 comments)
  12. 50 points, 16 submissions: BNielson
    1. Regression Trees (7 points, 9 comments)
    2. Two Interpretations of RFR are leading to two different possible Sharpe Ratios -- Need Instructor clarification ASAP (5 points, 3 comments)
    3. PYTHONPATH=../:. python grade_analysis.py (4 points, 7 comments)
    4. Running on Windows and PyCharm (4 points, 4 comments)
    5. Studying for the midterm: python questions (4 points, 0 comments)
    6. Assess Learners Grader (3 points, 2 comments)
    7. Manual Strategy Grade (3 points, 2 comments)
    8. Rewards in Q Learning (3 points, 3 comments)
    9. SSH/Putty on Windows (3 points, 4 comments)
    10. Slight contradiction on ProctorTrack Exam (3 points, 4 comments)
  13. 49 points, 7 submissions: j0shj0nes
    1. QLearning Robot - Finalized and Released Soon? (18 points, 4 comments)
    2. Flash Boys, HFT, frontrunning... (10 points, 3 comments)
    3. Deprecations / errata (7 points, 5 comments)
    4. Udacity lectures via GT account, versus personal account (6 points, 2 comments)
    5. Python: console-driven development (5 points, 5 comments)
    6. Buffet pandas / numpy versions (2 points, 2 comments)
    7. Quant research on earnings calls (1 point, 0 comments)
  14. 45 points, 11 submissions: Zapurza
    1. Suggestion for Strategy learner mega thread. (14 points, 1 comment)
    2. Which lectures to watch for upcoming project q learning robot? (7 points, 5 comments)
    3. In schedule file, there is no link against 'voting ensemble strategy'? Scheduled for Nov 13-20 week (6 points, 3 comments)
    4. How to add questions to the question bank? I can see there is 2% credit for that. (4 points, 5 comments)
    5. Scratch paper use (3 points, 6 comments)
    6. The big short movie link on you tube says the video is not available in your country. (3 points, 9 comments)
    7. Distance between training data date and future forecast date (2 points, 2 comments)
    8. News affecting stock market and machine learning algorithms (2 points, 4 comments)
    9. pandas import in pydev (2 points, 0 comments)
    10. Assess learner server error (1 point, 2 comments)
  15. 43 points, 23 submissions: chvbs2000
    1. Is the Strategy Learner finalized? (10 points, 3 comments)
    2. Test extra 15 test cases for marketsim (3 points, 12 comments)
    3. Confusion between the term computing "back-in time" and "going forward" (2 points, 1 comment)
    4. How to define "each transaction"? (2 points, 4 comments)
    5. How to filling the assignment into Jupyter Notebook? (2 points, 4 comments)
    6. IOError: File ../data/SPY.csv does not exist (2 points, 4 comments)
    7. Issue in Access to machines at Georgia Tech via MacOS terminal (2 points, 5 comments)
    8. Reading data from Jupyter Notebook (2 points, 3 comments)
    9. benchmark vs manual strategy vs best possible strategy (2 points, 2 comments)
    10. global name 'pd' is not defined (2 points, 4 comments)
  16. 43 points, 15 submissions: shuang379
    1. How to test my code on buffet machine? (10 points, 15 comments)
    2. Can we get the ppt for "Decision Trees"? (8 points, 2 comments)
    3. python question pool question (5 points, 6 comments)
    4. set up problems (3 points, 4 comments)
    5. Do I need another camera for scanning? (2 points, 9 comments)
    6. Is chapter 9 covered by the midterm? (2 points, 2 comments)
    7. Why grade_analysis.py could run even if I rm analysis.py? (2 points, 5 comments)
    8. python question pool No.48 (2 points, 6 comments)
    9. where could we find old versions of the rest projects? (2 points, 2 comments)
    10. where to put ml4t-libraries to install those libraries? (2 points, 1 comment)
  17. 42 points, 14 submissions: larrva
    1. is there a mistake in How-to-learn-a-decision-tree.pdf (7 points, 7 comments)
    2. maximum recursion depth problem (6 points, 10 comments)
    3. [Urgent]Unable to use proctortrack in China (4 points, 21 comments)
    4. manual_strategynumber of indicators to use (3 points, 10 comments)
    5. Assignment 2: Got 63 points. (3 points, 3 comments)
    6. Software installation workshop (3 points, 7 comments)
    7. question regarding functools32 version (3 points, 3 comments)
    8. workshop on Aug 31 (3 points, 8 comments)
    9. Mount remote server to local machine (2 points, 2 comments)
    10. any suggestion on objective function (2 points, 3 comments)
  18. 41 points, 8 submissions: Ran__Ran
    1. Any resource will be available for final exam? (19 points, 6 comments)
    2. Need clarification on size of X, Y in defeat_learners (7 points, 10 comments)
    3. Get the same date format as in example chart (4 points, 3 comments)
    4. Cannot log in GitHub Desktop using GT account? (3 points, 3 comments)
    5. Do we have notes or ppt for Time Series Data? (3 points, 5 comments)
    6. Can we know the commission & market impact for short example? (2 points, 7 comments)
    7. Course schedule export issue (2 points, 15 comments)
    8. Buying/seeking beta v.s. buying/seeking alpha (1 point, 6 comments)
  19. 38 points, 4 submissions: ProudRamblinWreck
    1. Exam 2 Study topics (21 points, 5 comments)
    2. Reddit participation as part of grade? (13 points, 32 comments)
    3. Will birds chirping in the background flag me on Proctortrack? (3 points, 5 comments)
    4. Midterm Study Guide question pools (1 point, 2 comments)
  20. 37 points, 6 submissions: gatechben
    1. Submission page for strategy learner? (14 points, 10 comments)
    2. PSA: The grading script for strategy_learner changed on the 26th (10 points, 9 comments)
    3. Where is util.py supposed to be located? (8 points, 8 comments)
    4. PSA:. The default dates in the assignment 1 template are not the same as the examples on the assignment page. (2 points, 1 comment)
    5. Schedule: Discussion of upcoming trading projects? (2 points, 3 comments)
    6. [defeat_learners] More than one column for X? (1 point, 1 comment)
  21. 37 points, 3 submissions: jgeiger
    1. Please send/announce when changes are made to the project code (23 points, 7 comments)
    2. The Big Short on Netflix for OMSCS students (week of 10/16) (11 points, 6 comments)
    3. Typo(?) for Assess_portfolio wiki page (3 points, 2 comments)
  22. 35 points, 10 submissions: ltian35
    1. selecting row using .ix (8 points, 9 comments)
    2. Will the following 2 topics be included in the final exam(online student)? (7 points, 4 comments)
    3. udacity quiz (7 points, 4 comments)
    4. pdf of lecture (3 points, 4 comments)
    5. print friendly version of the course schedule (3 points, 9 comments)
    6. about learner regression vs classificaiton (2 points, 2 comments)
    7. is there a simple way to verify the correctness of our decision tree (2 points, 4 comments)
    8. about Building an ML-based forex strategy (1 point, 2 comments)
    9. about technical analysis (1 point, 6 comments)
    10. final exam online time period (1 point, 2 comments)
  23. 33 points, 2 submissions: bhrolenok
    1. Assess learners template and grading script is now available in the public repository (24 points, 0 comments)
    2. Tutorial for software setup on Windows (9 points, 35 comments)
  24. 31 points, 4 submissions: johannes_92
    1. Deadline extension? (26 points, 40 comments)
    2. Pandas date indexing issues (2 points, 5 comments)
    3. Why do we subtract 1 from SMA calculation? (2 points, 3 comments)
    4. Unexpected number of calls to query, sum=20 (should be 20), max=20 (should be 1), min=20 (should be 1) -bash: syntax error near unexpected token `(' (1 point, 3 comments)
  25. 30 points, 5 submissions: log_base_pi
    1. The Massive Hedge Fund Betting on AI [Article] (9 points, 1 comment)
    2. Useful Python tips and tricks (8 points, 10 comments)
    3. Video of overview of remaining projects with Tucker Balch (7 points, 1 comment)
    4. Will any material from the lecture by Goldman Sachs be covered on the exam? (5 points, 1 comment)
    5. What will the 2nd half of the course be like? (1 point, 8 comments)
  26. 30 points, 4 submissions: acschwabe
    1. Assignment and Exam Calendar (ICS File) (17 points, 6 comments)
    2. Please OMG give us any options for extra credit (8 points, 12 comments)
    3. Strategy learner question (3 points, 1 comment)
    4. Proctortrack: Do we need to schedule our test time? (2 points, 10 comments)
  27. 29 points, 9 submissions: _ant0n_
    1. Next assignment? (9 points, 6 comments)
    2. Proctortrack Onboarding test? (6 points, 11 comments)
    3. Manual strategy: Allowable positions (3 points, 7 comments)
    4. Anyone watched Black Scholes documentary? (2 points, 16 comments)
    5. Buffet machines hardware (2 points, 6 comments)
    6. Defeat learners: clarification (2 points, 4 comments)
    7. Is 'optimize_something' on the way to class GitHub repo? (2 points, 6 comments)
    8. assess_portfolio(... gen_plot=True) (2 points, 8 comments)
    9. remote job != remote + international? (1 point, 15 comments)
  28. 26 points, 10 submissions: umersaalis
    1. comments.txt (7 points, 6 comments)
    2. Assignment 2: report.pdf (6 points, 30 comments)
    3. Assignment 2: report.pdf sharing & plagiarism (3 points, 12 comments)
    4. Max Recursion Limit (3 points, 10 comments)
    5. Parametric vs Non-Parametric Model (3 points, 13 comments)
    6. Bag Learner Training (1 point, 2 comments)
    7. Decision Tree Issue: (1 point, 2 comments)
    8. Error in Running DTLearner and RTLearner (1 point, 12 comments)
    9. My Results for the four learners. Please check if you guys are getting values somewhat near to these. Exact match may not be there due to randomization. (1 point, 4 comments)
    10. Can we add the assignments and solutions to our public github profile? (0 points, 7 comments)
  29. 26 points, 6 submissions: abiele
    1. Recommended Reading? (13 points, 1 comment)
    2. Number of Indicators Used by Actual Trading Systems (7 points, 6 comments)
    3. Software Install Instructions From TA's Video Not Working (2 points, 2 comments)
    4. Suggest that TA/Instructor Contact Info Should be Added to the Syllabus (2 points, 2 comments)
    5. ML4T Software Setup (1 point, 3 comments)
    6. Where can I find the grading folder? (1 point, 4 comments)
  30. 26 points, 6 submissions: tomatonight
    1. Do we have all the information needed to finish the last project Strategy learner? (15 points, 3 comments)
    2. Does anyone interested in cryptocurrency trading/investing/others? (3 points, 6 comments)
    3. length of portfolio daily return (3 points, 2 comments)
    4. Did Michael Burry, Jamie&Charlie enter the short position too early? (2 points, 4 comments)
    5. where to check participation score (2 points, 1 comment)
    6. Where to collect the midterm exam? (forgot to take it last week) (1 point, 3 comments)
  31. 26 points, 3 submissions: hilo260
    1. Is there a template for optimize_something on GitHub? (14 points, 3 comments)
    2. Marketism project? (8 points, 6 comments)
    3. "Do not change the API" (4 points, 7 comments)
  32. 26 points, 3 submissions: niufen
    1. Windows Server Setup Guide (23 points, 16 comments)
    2. Strategy Learner Adding UserID as Comment (2 points, 2 comments)
    3. Connect to server via Python Error (1 point, 6 comments)
  33. 26 points, 3 submissions: whoyoung99
    1. How much time you spend on Assess Learner? (13 points, 47 comments)
    2. Git clone repository without fork (8 points, 2 comments)
    3. Just for fun (5 points, 1 comment)
  34. 25 points, 8 submissions: SharjeelHanif
    1. When can we discuss defeat learners methods? (10 points, 1 comment)
    2. Are the buffet servers really down? (3 points, 2 comments)
    3. Are the midterm results in proctortrack gone? (3 points, 3 comments)
    4. Will these finance topics be covered on the final? (3 points, 9 comments)
    5. Anyone get set up with Proctortrack? (2 points, 10 comments)
    6. Incentives Quiz Discussion (2-01, Lesson 11.8) (2 points, 3 comments)
    7. Anyone from Houston, TX (1 point, 1 comment)
    8. How can I trace my error back to a line of code? (assess learners) (1 point, 3 comments)
  35. 25 points, 5 submissions: jlamberts3
    1. Conda vs VirtualEnv (7 points, 8 comments)
    2. Cool Portfolio Backtesting Tool (6 points, 6 comments)
    3. Warren Buffett wins $1M bet made a decade ago that the S&P 500 stock index would outperform hedge funds (6 points, 12 comments)
    4. Windows Ubuntu Subsystem Putty Alternative (4 points, 0 comments)
    5. Algorithmic Trading Of Digital Assets (2 points, 0 comments)
  36. 25 points, 4 submissions: suman_paul
    1. Grade statistics (9 points, 3 comments)
    2. Machine Learning book by Mitchell (6 points, 11 comments)
    3. Thank You (6 points, 6 comments)
    4. Assignment1 ready to be cloned? (4 points, 4 comments)
  37. 25 points, 3 submissions: Spareo
    1. Submit Assignments Function (OS X/Linux) (15 points, 6 comments)
    2. Quantsoftware Site down? (8 points, 38 comments)
    3. ML4T_2017Spring folder on Buffet server?? (2 points, 5 comments)
  38. 24 points, 14 submissions: nelsongcg
    1. Is it realistic for us to try to build our own trading bot and profit? (6 points, 21 comments)
    2. Is the risk free rate zero for any country? (3 points, 7 comments)
    3. Models and black swans - discussion (3 points, 0 comments)
    4. Normal distribution assumption for options pricing (2 points, 3 comments)
    5. Technical analysis for cryptocurrency market? (2 points, 4 comments)
    6. A counter argument to models by Nassim Taleb (1 point, 0 comments)
    7. Are we demandas to use the sample for part 1? (1 point, 1 comment)
    8. Benchmark for "trusting" your trading algorithm (1 point, 5 comments)
    9. Don't these two statements on the project description contradict each other? (1 point, 2 comments)
    10. Forgot my TA (1 point, 6 comments)
  39. 24 points, 11 submissions: nurobezede
    1. Best way to obtain survivor bias free stock data (8 points, 1 comment)
    2. Please confirm Midterm is from October 13-16 online with proctortrack. (5 points, 2 comments)
    3. Are these DTlearner Corr values good? (2 points, 6 comments)
    4. Testing gen_data.py (2 points, 3 comments)
    5. BagLearner of Baglearners says 'Object is not callable' (1 point, 8 comments)
    6. DTlearner training RMSE none zero but almost there (1 point, 2 comments)
    7. How to submit analysis using git and confirm it? (1 point, 2 comments)
    8. Passing kwargs to learners in a BagLearner (1 point, 5 comments)
    9. Sampling for bagging tree (1 point, 8 comments)
    10. code failing the 18th test with grade_learners.py (1 point, 6 comments)
  40. 24 points, 4 submissions: AeroZach
    1. questions about how to build a machine learning system that's going to work well in a real market (12 points, 6 comments)
    2. Survivor Bias Free Data (7 points, 5 comments)
    3. Genetic Algorithms for Feature selection (3 points, 5 comments)
    4. How far back can you train? (2 points, 2 comments)
  41. 23 points, 9 submissions: vsrinath6
    1. Participation check #3 - Haven't seen it yet (5 points, 5 comments)
    2. What are the tasks for this week? (5 points, 12 comments)
    3. No projects until after the mid-term? (4 points, 5 comments)
    4. Format / Syllabus for the exams (2 points, 3 comments)
    5. Has there been a Participation check #4? (2 points, 8 comments)
    6. Project 3 not visible on T-Square (2 points, 3 comments)
    7. Assess learners - do we need to check is method implemented for BagLearner? (1 point, 4 comments)
    8. Correct number of days reported in the dataframe (should be the number of trading days between the start date and end date, inclusive). (1 point, 0 comments)
    9. RuntimeError: Invalid DISPLAY variable (1 point, 2 comments)
  42. 23 points, 8 submissions: nick_algorithm
    1. Help with getting Average Daily Return Right (6 points, 7 comments)
    2. Hint for args argument in scipy minimize (5 points, 2 comments)
    3. How do you make money off of highly volatile (high SDDR) stocks? (4 points, 5 comments)
    4. Can We Use Code Obtained from Class To Make Money without Fear of Being Sued (3 points, 6 comments)
    5. Is the Std for Bollinger Bands calculated over the same timespan of the Moving Average? (2 points, 2 comments)
    6. Can't run grade_learners.py but I'm not doing anything different from the last assignment (?) (1 point, 5 comments)
    7. How to determine value at terminal node of tree? (1 point, 1 comment)
    8. Is there a way to get Reddit announcements piped to email (or have a subsequent T-Square announcement published simultaneously) (1 point, 2 comments)
  43. 23 points, 1 submission: gong6
    1. Is manual strategy ready? (23 points, 6 comments)
  44. 21 points, 6 submissions: amchang87
    1. Reason for public reddit? (6 points, 4 comments)
    2. Manual Strategy - 21 day holding Period (4 points, 12 comments)
    3. Sharpe Ratio (4 points, 6 comments)
    4. Manual Strategy - No Position? (3 points, 3 comments)
    5. ML / Manual Trader Performance (2 points, 0 comments)
    6. T-Square Submission Missing? (2 points, 3 comments)
  45. 21 points, 6 submissions: fall2017_ml4t_cs_god
    1. PSA: When typing in code, please use 'formatting help' to see how to make the code read cleaner. (8 points, 2 comments)
    2. Why do Bollinger Bands use 2 standard deviations? (5 points, 20 comments)
    3. How do I log into the [email protected]? (3 points, 1 comment)
    4. Is midterm 2 cumulative? (2 points, 3 comments)
    5. Where can we learn about options? (2 points, 2 comments)
    6. How do you calculate the analysis statistics for bps and manual strategy? (1 point, 1 comment)
  46. 21 points, 5 submissions: Jmitchell83
    1. Manual Strategy Grades (12 points, 9 comments)
    2. two-factor (3 points, 6 comments)
    3. Free to use volume? (2 points, 1 comment)
    4. Is MC1-Project-1 different than assess_portfolio? (2 points, 2 comments)
    5. Online Participation Checks (2 points, 4 comments)
  47. 21 points, 5 submissions: Sergei_B
    1. Do we need to worry about missing data for Asset Portfolio? (14 points, 13 comments)
    2. How do you get data from yahoo in panda? the sample old code is below: (2 points, 3 comments)
    3. How to fix import pandas as pd ImportError: No module named pandas? (2 points, 4 comments)
    4. Python Practice exam Question 48 (2 points, 2 comments)
    5. Mac: "virtualenv : command not found" (1 point, 2 comments)
  48. 21 points, 3 submissions: mharrow3
    1. First time reddit user .. (17 points, 37 comments)
    2. Course errors/types (2 points, 2 comments)
    3. Install course software on macOS using Vagrant .. (2 points, 0 comments)
  49. 20 points, 9 submissions: iceguyvn
    1. Manual strategy implementation for future projects (4 points, 15 comments)
    2. Help with correlation calculation (3 points, 15 comments)
    3. Help! maximum recursion depth exceeded (3 points, 10 comments)
    4. Help: how to index by date? (2 points, 4 comments)
    5. How to attach a 1D array to a 2D array? (2 points, 2 comments)
    6. How to set a single cell in a 2D DataFrame? (2 points, 4 comments)
    7. Next assignment after marketsim? (2 points, 4 comments)
    8. Pythonic way to detect the first row? (1 point, 6 comments)
    9. Questions regarding seed (1 point, 1 comment)
  50. 20 points, 3 submissions: JetsonDavis
    1. Push back assignment 3? (10 points, 14 comments)
    2. Final project (9 points, 3 comments)
    3. Numpy versions (1 point, 2 comments)
  51. 20 points, 2 submissions: pharmerino
    1. assess_portfolio test cases (16 points, 88 comments)
    2. ML4T Assignments (4 points, 6 comments)

Top Commenters

  1. tuckerbalch (2296 points, 1185 comments)
  2. davebyrd (1033 points, 466 comments)
  3. yokh_cs7646 (320 points, 177 comments)
  4. rgraziano3 (266 points, 147 comments)
  5. j0shj0nes (264 points, 148 comments)
  6. i__want__piazza (236 points, 127 comments)
  7. swamijay (227 points, 116 comments)
  8. _ant0n_ (205 points, 149 comments)
  9. ml4tstudent (204 points, 117 comments)
  10. gatechben (179 points, 107 comments)
  11. BNielson (176 points, 108 comments)
  12. jameschanx (176 points, 94 comments)
  13. Artmageddon (167 points, 83 comments)
  14. htrajan (162 points, 81 comments)
  15. boyko11 (154 points, 99 comments)
  16. alyssa_p_hacker (146 points, 80 comments)
  17. log_base_pi (141 points, 80 comments)
  18. Ran__Ran (139 points, 99 comments)
  19. johnsmarion (136 points, 86 comments)
  20. jgorman30_gatech (135 points, 102 comments)
  21. dyllll (125 points, 91 comments)
  22. MikeLachmayr (123 points, 95 comments)
  23. awhoof (113 points, 72 comments)
  24. SharjeelHanif (106 points, 59 comments)
  25. larrva (101 points, 69 comments)
  26. augustinius (100 points, 52 comments)
  27. oimesbcs (99 points, 67 comments)
  28. vansh21k (98 points, 62 comments)
  29. W1redgh0st (97 points, 70 comments)
  30. ybai67 (96 points, 41 comments)
  31. JuanCarlosKuriPinto (95 points, 54 comments)
  32. acschwabe (93 points, 58 comments)
  33. pharmerino (92 points, 47 comments)
  34. jgeiger (91 points, 28 comments)
  35. Zapurza (88 points, 70 comments)
  36. jyoms (87 points, 55 comments)
  37. omscs_zenan (87 points, 44 comments)
  38. nurobezede (85 points, 64 comments)
  39. BelaZhu (83 points, 50 comments)
  40. jason_gt (82 points, 36 comments)
  41. shuang379 (81 points, 64 comments)
  42. ggatech (81 points, 51 comments)
  43. nitinkodial_gatech (78 points, 59 comments)
  44. harshsikka123 (77 points, 55 comments)
  45. bkeenan7 (76 points, 49 comments)
  46. moxyll (76 points, 32 comments)
  47. nelsongcg (75 points, 53 comments)
  48. nickzelei (75 points, 41 comments)
  49. hunter2omscs (74 points, 29 comments)
  50. pointblank41 (73 points, 36 comments)
  51. zheweisun (66 points, 48 comments)
  52. bs_123 (66 points, 36 comments)
  53. storytimeuva (66 points, 36 comments)
  54. sva6 (66 points, 31 comments)
  55. bhrolenok (66 points, 27 comments)
  56. lingkaizuo (63 points, 46 comments)
  57. Marvel_this (62 points, 36 comments)
  58. agifft3_omscs (62 points, 35 comments)
  59. ssung40 (61 points, 47 comments)
  60. amchang87 (61 points, 32 comments)
  61. joshuak_gatech (61 points, 30 comments)
  62. fall2017_ml4t_cs_god (60 points, 50 comments)
  63. ccrouch8 (60 points, 45 comments)
  64. nick_algorithm (60 points, 29 comments)
  65. JetsonDavis (59 points, 35 comments)
  66. yjacket103 (58 points, 36 comments)
  67. hilo260 (58 points, 29 comments)
  68. coolwhip1234 (58 points, 15 comments)
  69. chvbs2000 (57 points, 49 comments)
  70. suman_paul (57 points, 29 comments)
  71. masterm (57 points, 23 comments)
  72. RolfKwakkelaar (55 points, 32 comments)
  73. rpb3 (55 points, 23 comments)
  74. venkatesh8 (54 points, 30 comments)
  75. omscs_avik (53 points, 37 comments)
  76. bman8810 (52 points, 31 comments)
  77. snladak (51 points, 31 comments)
  78. dfihn3 (50 points, 43 comments)
  79. mlcrypto (50 points, 32 comments)
  80. omscs-student (49 points, 26 comments)
  81. NellVega (48 points, 32 comments)
  82. booglespace (48 points, 23 comments)
  83. ccortner3 (48 points, 23 comments)
  84. caa5042 (47 points, 34 comments)
  85. gcalma3 (47 points, 25 comments)
  86. krushnatmore (44 points, 32 comments)
  87. sn_48 (43 points, 22 comments)
  88. thenewprofessional (43 points, 16 comments)
  89. urider (42 points, 33 comments)
  90. gatech-raleighite (42 points, 30 comments)
  91. chrisong2017 (41 points, 26 comments)
  92. ProudRamblinWreck (41 points, 24 comments)
  93. kramey8 (41 points, 24 comments)
  94. coderafk (40 points, 28 comments)
  95. niufen (40 points, 23 comments)
  96. tholladay3 (40 points, 23 comments)
  97. SaberCrunch (40 points, 22 comments)
  98. gnr11 (40 points, 21 comments)
  99. nadav3 (40 points, 18 comments)
  100. gt7431a (40 points, 16 comments)

Top Submissions

  1. [Project Questions] Unit Tests for assess_portfolio assignment by reyallan (58 points, 52 comments)
  2. [Project Questions] Unit Tests for optimize_something assignment by agifft3_omscs (53 points, 94 comments)
  3. Proper git workflow by jan-laszlo (43 points, 19 comments)
  4. Exam 2 Information by yokh_cs7646 (39 points, 40 comments)
  5. A little more on Pandas indexing/slicing ([] vs ix vs iloc vs loc) and numpy shapes by davebyrd (37 points, 10 comments)
  6. Project 1 Megathread (assess_portfolio) by davebyrd (34 points, 466 comments)
  7. defeat_learner test case by swamijay (34 points, 38 comments)
  8. Project 2 Megathread (optimize_something) by tuckerbalch (33 points, 475 comments)
  9. project 3 megathread (assess_learners) by tuckerbalch (27 points, 1130 comments)
  10. Deadline extension? by johannes_92 (26 points, 40 comments)

Top Comments

  1. 34 points: jgeiger's comment in QLearning Robot project megathread
  2. 31 points: coolwhip1234's comment in QLearning Robot project megathread
  3. 30 points: tuckerbalch's comment in Why Professor is usually late for class?
  4. 23 points: davebyrd's comment in Deadline extension?
  5. 20 points: jason_gt's comment in What would be a good quiz question regarding The Big Short?
  6. 19 points: yokh_cs7646's comment in For online students: Participation check #2
  7. 17 points: i__want__piazza's comment in project 3 megathread (assess_learners)
  8. 17 points: nathakhanh2's comment in Project 2 Megathread (optimize_something)
  9. 17 points: pharmerino's comment in Midterm study Megathread
  10. 17 points: tuckerbalch's comment in Midterm grades posted to T-Square
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