6 Trading Statistics Every Forex Trader Should Know ...

H1 Backtest of ParallaxFX's BBStoch system

Disclaimer: None of this is financial advice. I have no idea what I'm doing. Please do your own research or you will certainly lose money. I'm not a statistician, data scientist, well-seasoned trader, or anything else that would qualify me to make statements such as the below with any weight behind them. Take them for the incoherent ramblings that they are.
TL;DR at the bottom for those not interested in the details.
This is a bit of a novel, sorry about that. It was mostly for getting my own thoughts organized, but if even one person reads the whole thing I will feel incredibly accomplished.

Background

For those of you not familiar, please see the various threads on this trading system here. I can't take credit for this system, all glory goes to ParallaxFX!
I wanted to see how effective this system was at H1 for a couple of reasons: 1) My current broker is TD Ameritrade - their Forex minimum is a mini lot, and I don't feel comfortable enough yet with the risk to trade mini lots on the higher timeframes(i.e. wider pip swings) that ParallaxFX's system uses, so I wanted to see if I could scale it down. 2) I'm fairly impatient, so I don't like to wait days and days with my capital tied up just to see if a trade is going to win or lose.
This does mean it requires more active attention since you are checking for setups once an hour instead of once a day or every 4-6 hours, but the upside is that you trade more often this way so you end up winning or losing faster and moving onto the next trade. Spread does eat more of the trade this way, but I'll cover this in my data below - it ends up not being a problem.
I looked at data from 6/11 to 7/3 on all pairs with a reasonable spread(pairs listed at bottom above the TL;DR). So this represents about 3-4 weeks' worth of trading. I used mark(mid) price charts. Spreadsheet link is below for anyone that's interested.

System Details

I'm pretty much using ParallaxFX's system textbook, but since there are a few options in his writeups, I'll include all the discretionary points here:

And now for the fun. Results!

As you can see, a higher target ended up with higher profit despite a much lower winrate. This is partially just how things work out with profit targets in general, but there's an additional point to consider in our case: the spread. Since we are trading on a lower timeframe, there is less overall price movement and thus the spread takes up a much larger percentage of the trade than it would if you were trading H4, Daily or Weekly charts. You can see exactly how much it accounts for each trade in my spreadsheet if you're interested. TDA does not have the best spreads, so you could probably improve these results with another broker.
EDIT: I grabbed typical spreads from other brokers, and turns out while TDA is pretty competitive on majors, their minors/crosses are awful! IG beats them by 20-40% and Oanda beats them 30-60%! Using IG spreads for calculations increased profits considerably (another 5% on top) and Oanda spreads increased profits massively (another 15%!). Definitely going to be considering another broker than TDA for this strategy. Plus that'll allow me to trade micro-lots, so I can be more granular(and thus accurate) with my position sizing and compounding.

A Note on Spread

As you can see in the data, there were scenarios where the spread was 80% of the overall size of the trade(the size of the confirmation candle that you draw your fibonacci retracements over), which would obviously cut heavily into your profits.
Removing any trades where the spread is more than 50% of the trade width improved profits slightly without removing many trades, but this is almost certainly just coincidence on a small sample size. Going below 40% and even down to 30% starts to cut out a lot of trades for the less-common pairs, but doesn't actually change overall profits at all(~1% either way).
However, digging all the way down to 25% starts to really make some movement. Profit at the -161.8% TP level jumps up to 37.94% if you filter out anything with a spread that is more than 25% of the trade width! And this even keeps the sample size fairly large at 187 total trades.
You can get your profits all the way up to 48.43% at the -161.8% TP level if you filter all the way down to only trades where spread is less than 15% of the trade width, however your sample size gets much smaller at that point(108 trades) so I'm not sure I would trust that as being accurate in the long term.
Overall based on this data, I'm going to only take trades where the spread is less than 25% of the trade width. This may bias my trades more towards the majors, which would mean a lot more correlated trades as well(more on correlation below), but I think it is a reasonable precaution regardless.

Time of Day

Time of day had an interesting effect on trades. In a totally predictable fashion, a vast majority of setups occurred during the London and New York sessions: 5am-12pm Eastern. However, there was one outlier where there were many setups on the 11PM bar - and the winrate was about the same as the big hours in the London session. No idea why this hour in particular - anyone have any insight? That's smack in the middle of the Tokyo/Sydney overlap, not at the open or close of either.
On many of the hour slices I have a feeling I'm just dealing with small number statistics here since I didn't have a lot of data when breaking it down by individual hours. But here it is anyway - for all TP levels, these three things showed up(all in Eastern time):
I don't have any reason to think these timeframes would maintain this behavior over the long term. They're almost certainly meaningless. EDIT: When you de-dup highly correlated trades, the number of trades in these timeframes really drops, so from this data there is no reason to think these timeframes would be any different than any others in terms of winrate.
That being said, these time frames work out for me pretty well because I typically sleep 12am-7am Eastern time. So I automatically avoid the 5am-6am timeframe, and I'm awake for the majority of this system's setups.

Moving stops up to breakeven

This section goes against everything I know and have ever heard about trade management. Please someone find something wrong with my data. I'd love for someone to check my formulas, but I realize that's a pretty insane time commitment to ask of a bunch of strangers.
Anyways. What I found was that for these trades moving stops up...basically at all...actually reduced the overall profitability.
One of the data points I collected while charting was where the price retraced back to after hitting a certain milestone. i.e. once the price hit the -61.8% profit level, how far back did it retrace before hitting the -100% profit level(if at all)? And same goes for the -100% profit level - how far back did it retrace before hitting the -161.8% profit level(if at all)?
Well, some complex excel formulas later and here's what the results appear to be. Emphasis on appears because I honestly don't believe it. I must have done something wrong here, but I've gone over it a hundred times and I can't find anything out of place.
Now, you might think exactly what I did when looking at these numbers: oof, the spread killed us there right? Because even when you move your SL to 0%, you still end up paying the spread, so it's not truly "breakeven". And because we are trading on a lower timeframe, the spread can be pretty hefty right?
Well even when I manually modified the data so that the spread wasn't subtracted(i.e. "Breakeven" was truly +/- 0), things don't look a whole lot better, and still way worse than the passive trade management method of leaving your stops in place and letting it run. And that isn't even a realistic scenario because to adjust out the spread you'd have to move your stoploss inside the candle edge by at least the spread amount, meaning it would almost certainly be triggered more often than in the data I collected(which was purely based on the fib levels and mark price). Regardless, here are the numbers for that scenario:
From a literal standpoint, what I see behind this behavior is that 44 of the 69 breakeven trades(65%!) ended up being profitable to -100% after retracing deeply(but not to the original SL level), which greatly helped offset the purely losing trades better than the partial profit taken at -61.8%. And 36 went all the way back to -161.8% after a deep retracement without hitting the original SL. Anyone have any insight into this? Is this a problem with just not enough data? It seems like enough trades that a pattern should emerge, but again I'm no expert.
I also briefly looked at moving stops to other lower levels (78.6%, 61.8%, 50%, 38.2%, 23.6%), but that didn't improve things any. No hard data to share as I only took a quick look - and I still might have done something wrong overall.
The data is there to infer other strategies if anyone would like to dig in deep(more explanation on the spreadsheet below). I didn't do other combinations because the formulas got pretty complicated and I had already answered all the questions I was looking to answer.

2-Candle vs Confirmation Candle Stops

Another interesting point is that the original system has the SL level(for stop entries) just at the outer edge of the 2-candle pattern that makes up the system. Out of pure laziness, I set up my stops just based on the confirmation candle. And as it turns out, that is much a much better way to go about it.
Of the 60 purely losing trades, only 9 of them(15%) would go on to be winners with stops on the 2-candle formation. Certainly not enough to justify the extra loss and/or reduced profits you are exposing yourself to in every single other trade by setting a wider SL.
Oddly, in every single scenario where the wider stop did save the trade, it ended up going all the way to the -161.8% profit level. Still, not nearly worth it.

Correlated Trades

As I've said many times now, I'm really not qualified to be doing an analysis like this. This section in particular.
Looking at shared currency among the pairs traded, 74 of the trades are correlated. Quite a large group, but it makes sense considering the sort of moves we're looking for with this system.
This means you are opening yourself up to more risk if you were to trade on every signal since you are technically trading with the same underlying sentiment on each different pair. For example, GBP/USD and AUD/USD moving together almost certainly means it's due to USD moving both pairs, rather than GBP and AUD both moving the same size and direction coincidentally at the same time. So if you were to trade both signals, you would very likely win or lose both trades - meaning you are actually risking double what you'd normally risk(unless you halve both positions which can be a good option, and is discussed in ParallaxFX's posts and in various other places that go over pair correlation. I won't go into detail about those strategies here).
Interestingly though, 17 of those apparently correlated trades ended up with different wins/losses.
Also, looking only at trades that were correlated, winrate is 83%/70%/55% (for the three TP levels).
Does this give some indication that the same signal on multiple pairs means the signal is stronger? That there's some strong underlying sentiment driving it? Or is it just a matter of too small a sample size? The winrate isn't really much higher than the overall winrates, so that makes me doubt it is statistically significant.
One more funny tidbit: EUCAD netted the lowest overall winrate: 30% to even the -61.8% TP level on 10 trades. Seems like that is just a coincidence and not enough data, but dang that's a sucky losing streak.
EDIT: WOW I spent some time removing correlated trades manually and it changed the results quite a bit. Some thoughts on this below the results. These numbers also include the other "What I will trade" filters. I added a new worksheet to my data to show what I ended up picking.
To do this, I removed correlated trades - typically by choosing those whose spread had a lower % of the trade width since that's objective and something I can see ahead of time. Obviously I'd like to only keep the winning trades, but I won't know that during the trade. This did reduce the overall sample size down to a level that I wouldn't otherwise consider to be big enough, but since the results are generally consistent with the overall dataset, I'm not going to worry about it too much.
I may also use more discretionary methods(support/resistance, quality of indecision/confirmation candles, news/sentiment for the pairs involved, etc) to filter out correlated trades in the future. But as I've said before I'm going for a pretty mechanical system.
This brought the 3 TP levels and even the breakeven strategies much closer together in overall profit. It muted the profit from the high R:R strategies and boosted the profit from the low R:R strategies. This tells me pair correlation was skewing my data quite a bit, so I'm glad I dug in a little deeper. Fortunately my original conclusion to use the -161.8 TP level with static stops is still the winner by a good bit, so it doesn't end up changing my actions.
There were a few times where MANY (6-8) correlated pairs all came up at the same time, so it'd be a crapshoot to an extent. And the data showed this - often then won/lost together, but sometimes they did not. As an arbitrary rule, the more correlations, the more trades I did end up taking(and thus risking). For example if there were 3-5 correlations, I might take the 2 "best" trades given my criteria above. 5+ setups and I might take the best 3 trades, even if the pairs are somewhat correlated.
I have no true data to back this up, but to illustrate using one example: if AUD/JPY, AUD/USD, CAD/JPY, USD/CAD all set up at the same time (as they did, along with a few other pairs on 6/19/20 9:00 AM), can you really say that those are all the same underlying movement? There are correlations between the different correlations, and trying to filter for that seems rough. Although maybe this is a known thing, I'm still pretty green to Forex - someone please enlighten me if so! I might have to look into this more statistically, but it would be pretty complex to analyze quantitatively, so for now I'm going with my gut and just taking a few of the "best" trades out of the handful.
Overall, I'm really glad I went further on this. The boosting of the B/E strategies makes me trust my calculations on those more since they aren't so far from the passive management like they were with the raw data, and that really had me wondering what I did wrong.

What I will trade

Putting all this together, I am going to attempt to trade the following(demo for a bit to make sure I have the hang of it, then for keeps):
Looking at the data for these rules, test results are:
I'll be sure to let everyone know how it goes!

Other Technical Details

Raw Data

Here's the spreadsheet for anyone that'd like it. (EDIT: Updated some of the setups from the last few days that have fully played out now. I also noticed a few typos, but nothing major that would change the overall outcomes. Regardless, I am currently reviewing every trade to ensure they are accurate.UPDATE: Finally all done. Very few corrections, no change to results.)
I have some explanatory notes below to help everyone else understand the spiraled labyrinth of a mind that put the spreadsheet together.

Insanely detailed spreadsheet notes

For you real nerds out there. Here's an explanation of what each column means:

Pairs

  1. AUD/CAD
  2. AUD/CHF
  3. AUD/JPY
  4. AUD/NZD
  5. AUD/USD
  6. CAD/CHF
  7. CAD/JPY
  8. CHF/JPY
  9. EUAUD
  10. EUCAD
  11. EUCHF
  12. EUGBP
  13. EUJPY
  14. EUNZD
  15. EUUSD
  16. GBP/AUD
  17. GBP/CAD
  18. GBP/CHF
  19. GBP/JPY
  20. GBP/NZD
  21. GBP/USD
  22. NZD/CAD
  23. NZD/CHF
  24. NZD/JPY
  25. NZD/USD
  26. USD/CAD
  27. USD/CHF
  28. USD/JPY

TL;DR

Based on the reasonable rules I discovered in this backtest:

Demo Trading Results

Since this post, I started demo trading this system assuming a 5k capital base and risking ~1% per trade. I've added the details to my spreadsheet for anyone interested. The results are pretty similar to the backtest when you consider real-life conditions/timing are a bit different. I missed some trades due to life(work, out of the house, etc), so that brought my total # of trades and thus overall profit down, but the winrate is nearly identical. I also closed a few trades early due to various reasons(not liking the price action, seeing support/resistance emerge, etc).
A quick note is that TD's paper trade system fills at the mid price for both stop and limit orders, so I had to subtract the spread from the raw trade values to get the true profit/loss amount for each trade.
I'm heading out of town next week, then after that it'll be time to take this sucker live!

Live Trading Results

I started live-trading this system on 8/10, and almost immediately had a string of losses much longer than either my backtest or demo period. Murphy's law huh? Anyways, that has me spooked so I'm doing a longer backtest before I start risking more real money. It's going to take me a little while due to the volume of trades, but I'll likely make a new post once I feel comfortable with that and start live trading again.
submitted by ForexBorex to Forex [link] [comments]

Genesis Vision - Development Progress TL;DR

Genesis Vision - TL;DR
As usual I post this every few months or so after a significant update, to inform both old & new investors
Best places to stay up to date:
Upcoming developments:
Not developments as such, but we can also expect:
2019 Progress:
  • Most of the terms on the platform will now display definitions when you hover your mouse cursor over them.
  • In the “Trades” tab on a page of a program, you can now export trading data for the selected period to Excel
  • You can now filter GV Funds by assets
  • When an investor creates a withdrawal request from an investment program, it automatically cancels the previous one.
  • Investors can now select an option to “Withdraw all”
  • Managers now have a separate “Program settings” section
  • The design of the “Program” page was updated and given a facelift. The new version now shows the program’s broker of choice, leverage, duration of the reporting period and more.
  • Addition of program ages to dashboard
  • Managers can now attach social network profiles to their accounts
  • Level/investment calculator
  • Complete revamp of the leveling system
  • First token burn - 1872 GVT / $5821.5 burnt
  • Copytrading & Signals released
  • Integration with Exante - Now full access to over 10,000 additional assets
  • Full integration with Huobi where traders can manage funds through the native Huobi UI
  • Adding new token listings on Huobi & Binance as soon as possible to GV Funds & Programs
  • Risk tags (high/medium/low) added to manager profiles
  • Added ability to hide closed programs in personal dashboard
  • Added open positions into the balance. So you can watch the performance of a program through both its closed and open positions
  • Added visibility to closed programs. So you can now see every program that was opened and managed by a manager
  • Additional tokens already added to GV Funds
  • QUARTERLY GV TOKEN BURN - Starting June 30th 2019
  • Roboforex Integration
  • Ability to short on the platform (via RoboForex)
  • Chain Plus conference in Seoul Korea
  • Genesis Markets & all of its materials translated into Chinese
  • Huobi/Genesis Markets bridge complete
  • Copytrading features
  • Signals w/subscriptions
  • Multicurrency wallet
  • Stop Outs
  • Platform Tags
  • Platform model change (less selling pressure on the GVT token)
  • Additional discounts both for copy trading and investment programs for HODLing GVT
2018 Progress:
  • Metatrader integration
  • Genesis Vision Alpha Version
  • IPFS Integration
  • Numerous trading competitions
  • Launch of Genesis Markets
  • Launch of the iOS & Android Genesis Vision apps
  • Live Platform Launch ~ 30th October
  • Completely overhauled UI/UX for iOS, Android, Investors & Manager portals
  • Fresh website for GV & GM
  • Finance Magnates London Summit
  • Sofia Investor Finance Forum
  • Huobi prestige Investors Fireside Dialogue (speakers)
  • Launch of Genesis Vision Funds
  • Removal of entry fees for level 1 & 2 managers
  • New leveling system -> https://blog.genesis.vision/do-your-level-best-7dc47d16b44e
  • Forex trading went live -> https://blog.genesis.vision/its-forex-time-89a72c7f5fac
In the works for the future (some speculation)
  • Chinese promotion - The platform and all of the reading materials will be translated into Chinese
  • Exploring the possibility of using Binance Chain
  • Genesis Vision DEX
  • Genesis Vision Network -> https://blog.genesis.vision/genesis-vision-network-10bf3e749688
  • Fiat Gateway
  • Bank & Stocks Integration
  • Further platform development for GV & Genesis Markets
  • Further development of all versions of the platform, ie iOS & Android
  • I personally believe we will see GVT listed on some exchanges in 2019
Current Partnerships/Integrations:
Platform statistics
  • Follow @GVTProgressBot on Twitter for updates every 24 hours
The team posted their results for Q1 2019 profits in this article:
Some more info on revenue:
Firstly, I am not part of the team, so any replies are just from research I have done into the project and available information:
1.) The team confirmed that there are 40 people working for Genesis Vision 25 are working in the office and 15 remotely. Jump in the TG if you would like to know more info or even talk to some of the other team members direct. Dmitry Nazarov = CEO, Ruslan Kamensky = Head of Development. (You can do your background research on these guys, they've got skills).
2.) Can't comment accurately on funds, because well, that's the teams business. Ofc a responsible investor should try and find out as much info as they can however.
  • The ICO raised -> $2,836,724 when ETH was around $250-$300 pre-bull run (you do the math).
  • The team/development tokens also amounted to 709,862 GVT/16% of the supply, these funds would/will have been used for development, and remember GVT's ATH was $51 - So if they sold anywhere near this top then there's some hefty funds right there, albeit some are actual team tokens.
3.) Sustainability is a big one. This is why I continue to follow GVT daily because I believe the Genesis Vision model is sustainable. See my previous post:
https://www.reddit.com/genesisvision/comments/9p80igenesis_vision_will_soon_become_a_self_sufficient/
TLDR - Here's how they will create revenue from the GV platform (taken from the whitepaper):
  • The project will receive profit from commissions on investment operations. Each investment will be charged 0.5%³ of the operation amount.
  • The project will also generate profit from managing its own fund and by investing it in successful managers of our platform.
  • Genesis Markets will create revenue from trading fees
Another thing to think about - The team have been extremely responsible with their funds. Zero funds have gone to waste and have been used in the most efficient way possible. One example (although a touchy subject) is marketing. The bottom line is marketing will ramp up when the project/platform has had more development (finishing integrating the brokers + additional features). The team have known that the correct time to market the platform is coming, just not yet... Obviously if they had 100's of millions from the ICO marketing would have been ongoing from Day 1. This is one example of being responsible with your investors/ICO funds.
If you would like some more information about the funds, the ICO etc. See these two links:
Bullish on GVT. You want reasons why im bullish? Re-read this post
submitted by elcryptonerd to genesisvision [link] [comments]

New stars: looking at possible OMG staking revenues with regards to # of transactions instead of volume.

We have an expression in Sweden which translated directly to English becomes “Aim for the stars and you might end up in the tree tops.”. This is my attempt at giving us some new stars to take aim for.
 
I will start by saying that I’m 100 % in OMG and that this is not a technical analysis of the future price movement, nor is it an analysis of OmiseGO’s potential of delivering what they have promised. This is simply a new way of looking at the future rewards to the stakers of OMG.
 
Secondly, this is not a finished product and the approximations that I’ve done can surely be improved by people with more knowledge than me about the subjects. I welcome everyone to correct my mistakes and/or add their knowledge.
 
The reason that I’ve spent the time to research this subject is that I believe that most speculators in this forum are looking at the wrong parameters when trying to calculate future staking returns. They are looking at volume and speculating on which percentage that OMG will take of that volume; I think that we instead should be looking at the number of transactions. The cost of a simple transaction of value from one part to another on a blockchain (Ethereum or OMG) is, as far as I know, not dependent on the size of the value. I believe that the OMG blockchain will have a dynamic fee structure where buying an apple or buying a car will cost the same amount in transaction fees (although payment companies on top of the OMG blockchain might take a fixed percentage for their services, but that won’t affect us OMG stakers).
 
If my assumption above is correct, then we need to figure out how many transactions that OMG might process. So, how many transactions are we talking here? Well, I’ve started now by looking at four different areas of value transactions:
 
  1. Every day purchases
  2. Stock exchange
  3. Money transfers
  4. Forex market
 
 
Every day purchases
 
These are transactions where people use cash or card to purchase some item (buying fruit or a computer). Now, the exact number is impossible to find but we can get some good approximations. According to the 2016 Nilson report there was 227 billion card transactions during 2015 worldwide. [1] But, as we all know, OmiseGO’s plan stretches also to the unbanked and the cash payments. According to Raconteur 85 % of the worlds transactions are still done in cash. [2] Simple math tells us then that
 
A*0.15 = 227 billion -> A = (227 billion)/0.15 = 1.51 trillion payment transactions every year.
 
[This is of course not 100 % accurate since in the parts of the world where there is the least amount of card transactions there is also probably a lot fewer transactions overall. However, I think that we at least are at the right order of magnitude.]
 
 
Stock exchange
 
All the world’s stock exchanges could be rebuilt on top of the OMG blockchain in a more efficient way than before. So, how many transactions is that? This is a hard number to get ahold of and my estimate will probably end up being too low since many transactions never get registered outside of the trading houses. For example: a trading house can make 1 trade on the exchange where it buys 10,000.00 off Stock A, but then it sells it too 100 of their own customers. This last data is the hardest to get ahold of even if the trade data from the exchanges are almost impossible to find as well. According to Nasdaq there is an average of 10.5 million transactions per day on their exchange. [3] Now, The Money Project has published an infographic showing the worlds largest stock exchanges in relative volume to each other and the whole world market; it says that Nasdaq has a 10.79 % share of a global market of $69 trillion. [4] If we assume that there is a linear correlation between volume and number transactions for all the worlds stock exchanges, then we can assume that Nasdaq’s volume percentage of 10.78 is also it’s transactions percentage in relation to the worlds stock markets. This means that the global number of stock transactions is annually
 
B = (252*10.5 million)/0.1078 = $24.5 billion. [The number 252 in the equation is the average number of trading days per year.]
 
 
Money transfer
 
Pure money transfer transactions. One of the leading actors on that market is Western Union which, according to Forbes holds a 15 % market share with 231 million transactions per year. [5] This leads us to the approximation that the total market sees
 
C = (231*10 million)/0.15 = 1.54 billion transactions every year.
 
 
Forex market
 
Now, the forex market is definitely the hardest one to find information about. I posted in /Forex and they were helpful but told me that exact figures would be impossible to find. [6] However, much in the same manner as with the stock markets I was able to reach an approximation which others will have to judge if it’s fair or not. According to the CEO of LMAX exchange they print 1.5 million trades per day [7] which I will use as 1 trade = 1 transaction (same with the stock market) which gives them
 
252*1.5 million = 378 million transactions per year.
 
The website Leaprate.com has reported that LMAX has an average monthly volume of $175 billion [8] which ends up being $2.1 trillion per year. Let’s say that a linear correlation between number of trades and volume exists over all exchanges on the global forex market, again as we did with the stock market. This means that
 
378 million / ”Number of forex transactions globally” = $2.1 trillion/”$Global forex annual volume”.
 
The number of transactions globally is therefore
 
D = 378 million/($2.1 trillion/”$Global forex annual volume”)
 
with the variable being the annual total volume on the global forex market. According to Businessinsider.com the daily global volume is on average $5.1 trillion [9] which means that the annual volume is 252*$5.1 trillion = $1290 trillion which gives us the number of transactions annually on the global Forex market to be
 
D = 231 billion.
 
 
Total number of transactions and what that means in regard to staking
 
The total number of transactions E = A + B + C + D = 1.51 trillion + 24.5 billion + 1.54 billion + 231 billion = 1.77 trillion transactions every year.
 
If anyone wants to do their own calculations and only include certain percentages of the different markets then of course it is easy to add these percentages before their respected market in the equation above. I however, will calculate staking returns based on the premise that 100 % of these markets will be built and thrive on top of the OMG blockchain.
 
The equation for the returns of every OMG staked is pretty easy:
 
$/omg/year = Number of transaction per year*transaction fee / Number of coins staked .
 
The question is of course: what will the transaction fee be? No one can say, but I will use the transaction fee for the Ethereum network as a benchmark. The transaction fees on the Ethereum network varies but a recent low average has been around $0.2 per transaction. [10] Number of staked coins has also been up for debate at various times; 60 % has been thrown around and I’ll use that.
 
Case 1: OMG blockchain charge as much as the Ethereum blockchain does right now
 
$/omg/year = 1.77 trillion*0.2 / 0.6*140 million = $4,214.29
 
Case 2: OMG blockchain charge 10 % of what Ethereum blockchain does right now
 
$/omg/year = 1.77 trillion*0.1*0.2 / 0.6*140 million = $421.43
 
Case 3: OMG blockchain charge 1 % of what Ethereum blockchain does right now
 
$/omg/year = 1.77 trillion*0.01*0.2 / 0.6*140 million = $42.14
 
Again, I would like to invite anyone here to help me and point out any faults in my calculations, approximations and/or assumptions. However, could you also do the new calculations and add your proposed staking returns? I am a full-time student so hopefully the edits can happen in the comments instead of by me. Thanks!
 
References
 
[1] https://www.nilsonreport.com/publication_special_feature_article.php
[2] https://www.raconteur.net/technology/the-decline-of-cash
[3] http://www.nasdaqtrader.com/Trader.aspx?id=DailyMarketSummary
[4] http://money.visualcapitalist.com/all-of-the-worlds-stock-exchanges-by-size/
[5] https://www.forbes.com/sites/hilarykrame2013/05/10/wu-stock-report/#45eefb5b7771
[6] https://www.reddit.com/Forex/comments/7exyzn/does_statistics_exist_regarding_number_of_trades/
[7] https://www.lmax.com/blog/business-and-technology/2013/07/05/average-trade-size-declines-spot-fx/
[8] https://www.leaprate.com/forex/institutional/lmax-revenues-20-2016-27-7-million-monthly-volumes-175-billion/
[9] http://www.businessinsider.com/heres-how-much-currency-is-traded-every-day-2016-9?r=US&IR=T&IR=T
[10] https://bitinfocharts.com/comparison/ethereum-transactionfees.html#3m
submitted by jeneman to omise_go [link] [comments]

r/Stocks Technicals Tuesday - Dec 25, 2018

Feel free to talk about technical analysis here (not argue against it), but before you ask any question make sure you see the following information:
Technical analysis (TA) uses historical price movements, real time data, indicators based on math and/or statistics, and charts; all of which help measure the trajectory of a security. TA can also be used to interpret the actions of other market participants and predict their actions:
Measure: Is the security's price trending, has it dipped or is it a falling knife? Interpret: Does the current price mean investors think it's undervalued or overvalued; when did they buy/sell more and why? Predict: If price reaches a certain point, will there be a rally or get rejected?
The main benefit to TA is that everything shows up in the price (commonly known as priced in): All news, investor sentiment, and changes to fundamentals are reflected in a security's price.
TA is best used for short term trading, but can also be used for long term.
Intro to technical analysis by Stockcharts chartschool and their article on candlesticks
Terminology
Useful indicators
Methods or Systems
Strategies: See the TA wiki here as this will be a work in progress, feel free to reply with your own strategy.
See our past daily discussions here. Also links for: Technicals Tuesday, Options Trading Thursday, and Fundamentals Friday.
submitted by AutoModerator to stocks [link] [comments]

How To Trade Forex

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Learn The Basics |Advanced Topics | Chart Patterns | Choose The Best Broker
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How does Forex Work?

Forex trading is the simultaneous buying of one currency and selling of another…
Read more

Basic Terminology

Before trading currencies, an investor has to understand the basic terminology of the forex market…
Read more

Fundamental Analysis

Fundamental analysis is the study of the overall economic, financial, political…
Read more

Technical Analysis

Technical analysis is the study of prices over time, with charts being the primary tool…
Read more

Trend Lines

The term ‘trend’ describes the current direction of the financial instrument…
Read more

What is a Technical Indicator

Technical Indicators are a result of mathematical calculations/algorithms…
Read more

Gold Trading

As an investment, gold is the most popular of the precious metals…
Read more

Order Types

A market order is an order to open a buy or sell position at…
Read more

We complete our education centre with a breakdown of Gold Trading and details of the different Order Types.
You can also review our glossary to find brief definitions of various trading and financial terms you may encounter.
Once you have familiarised yourself with the information and concepts, you can open a Demo Trading Account to practice what you have learnt and build on your knowledge and understanding of how to trade successfully. Treat your demo account as you would your real account.
Aprender a operar con Forex | Lernen Sie Forex zu handeln

  1. What is Forex? Think the stock market is huge? Think again. Learn about the LARGEST financial market in the world and how to trade in it.
    1. What Is Forex?Learn about this massively huge financial market where fiat currencies are traded.
    2. What Is Traded In Forex?Currencies are the name of the game. Yes, you can buy and sell currencies against each other as a short-term trade, long-term investment, or something in-between.
    3. Buying And Selling Currency PairsThe first thing that you need to know about forex trading is that currencies are traded in pairs; you can’t buy or sell a currency without another.
    4. Forex Market Size And LiquidityThe Forex market is yuuuuuuuggggeeee! And that comes with a lot of benefits for currency traders!
    5. The Different Ways To Trade ForexSome of the more popular ways that traders participate in the forex market is through the spot market, futures, options, and exchange-traded funds.
  2. Why Trade Forex? Want to know some reasons why traders love the forex market? Read on to find out what makes it so attractive!
    1. Why Trade Forex: Advantages Of Forex TradingLow transaction costs and high liquidity are just a couple of the advantages of the forex market.
    2. Why Trade Forex: Forex vs. StocksNobody likes bullies! Good thing for us, unlike the stock market, there is no one financial institute large enough to corner the forex market!
    3. Why Trade Forex: Forex vs. FuturesThe futures market trades a puny $30 billion per day. Thirty billion? Peanuts compared to the FIVE TRILLION that is traded daily in the forex market!
  3. Who Trades Forex? From money exchangers, to banks, to hedge fund managers, to local Joes like your Uncle Pete – everybody participates in the forex market!
    1. Forex Market StructureBecause there is no centralized market, tight competition between banks normally leads to having the best prices! Boo yeah!
    2. Forex Market PlayersThe forex market is basically comprised of four different groups.
    3. Know Your Forex History!If it wasn’t for the Bretton Woods System (and the great Al Gore), there would be no retail forex trading! Time to brush up on your history!
  4. When Can You Trade Forex? Now that you know who participates in the forex market, it’s time to learn when you can trade!
    1. Forex Trading SessionsJust because the forex market is open 24 hours a day doesn’t mean it’s always active! See how the forex market is broken up into four major trading sessions and which ones provides the most opportunities.
    2. When Can You Trade Forex: Tokyo SessionGodzilla, Nintendo, and sushi! What’s not to like about Tokyo?!? The Tokyo session is sometimes referred to as the Asian session, which is also the session where we start fresh every day!
    3. When Can You Trade Forex: London SessionNot only is London the home of Big Ben, David Beckham, and the Queen, but it’s also considered the forex capital of the world–raking in about 30% of all forex transactions every day!
    4. When Can You Trade Forex: New York SessionNew York baby! The concrete jungle where forex dreams are made of! Just like Asia and Europe, the U.S. is considered one of the top financial centers in the world, so it definitely sees its fair share of action–and then some!
    5. Best Times of Day to Trade ForexTrading is all about volatility and liquidity. Which times of day provide the most dynamic market action and volumes?
    6. Best Days of the Week to Trade ForexEach trader should know when to trade and when NOT to trade. Read on to find out the best and worst times to trade.
  5. How Do You Trade Forex? Now, it’s time to learn HOW to rake in the moolah!
    1. How to Make Money Trading ForexJust like any other market: buy low and sell high…and vice versa. Simple, right!?
    2. Know When to Buy or Sell a Currency PairLet’s start with the very basics. First, what drives the value of a currency?
    3. What is a Pip in Forex?You’ve probably heard of the terms “pips,” “pipettes,” and “lots” thrown around, and here we’re going to explain what they are and show you how their values are calculated.
    4. What is a Lot in Forex?How many units of currency can we trade? What size positions can we trade and what are they called?
    5. Impress Your Date with Forex LingoWanna impress your crush? Here are some forex terms to help you wow that special someone!
    6. Types of Forex Orders“Would you like pips with that?” Okay, not that type of order, but buying and selling currencies can be just as simple with a little practice.
    7. Demo Trade Your Way to SuccessCurrency market behavior is constantly evolving. Trade on demo first to get a lot of the rookie mistakes out of the way before risking live capital. There are no take-backs in the real market.
    8. Forex Trading is NOT a Get-Rich-Quick SchemeWhile possible if you’re a trading genius with ice in your veins and you’re luckier than a lottery winner, building wealth through trading takes time and practice to build the skills and experience needed to be successful.
📷
Via XNTRADES.com
Topics Which Every Trader Must Master.
Or at least know your Chart Patterns
Support and Resistance v.1
Support and Resistance v.2
Elliot Waves Theory
Elliott Waves 101
Harmonic Patterns
Chart Patterns
How to Trade Market Structure
More educational materials from TRESORFX.com and XNTRADES.com

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Best Forex Broker in Hong Kong
Best Forex Broker in China 中國最好的外匯經紀商
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Best Forex Broker in South Africa
Best Forex Broker in Monaco
Best Forex Broker in Vietnam | Nhà môi giới Forex tốt nhất tại Việt Nam
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Best Forex Broker in India | இந்தியாவில் சிறந்த அந்நிய செலாவணி ப்ரோக்கர் | भारत में सर्वश्रेष्ठ विदेशी मुद्रा ब्रोकर
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Best Forex Broker in Slovakia | Najlepší Forex Broker na Slovensku
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Best Forex Broker in Czech Republic | Nejlepší Forex Broker v České republice
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Best Forex Broker in Hungary | A legjobb Forex bróker Magyarországon Best Forex Broker in Persia | بهترین کارگزاری فارکس در ایران
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submitted by TRESORFX to u/TRESORFX [link] [comments]

r/Stocks Technicals Tuesday - Nov 27, 2018

Feel free to talk about technical analysis here (not argue against it), but before you ask any question make sure you see the following information:
Technical analysis (TA) uses historical price movements, real time data, indicators based on math and/or statistics, and charts; all of which help measure the trajectory of a security. TA can also be used to interpret the actions of other market participants and predict their actions:
Measure: Is the security's price trending, has it dipped or is it a falling knife? Interpret: Does the current price mean investors think it's undervalued or overvalued; when did they buy/sell more and why? Predict: If price reaches a certain point, will there be a rally or get rejected?
The main benefit to TA is that everything shows up in the price (commonly known as priced in): All news, investor sentiment, and changes to fundamentals are reflected in a security's price.
TA is best used for short term trading, but can also be used for long term.
Intro to technical analysis by Stockcharts chartschool and their article on candlesticks
Terminology
Useful indicators
Methods or Systems
Strategies: See the TA wiki here as this will be a work in progress, feel free to reply with your own strategy.
See our past daily discussions here. Also links for: Technicals Tuesday, Options Trading Thursday, and Fundamentals Friday.
submitted by AutoModerator to stocks [link] [comments]

r/Stocks Technicals Tuesday - Dec 11, 2018

Feel free to talk about technical analysis here (not argue against it), but before you ask any question make sure you see the following information:
Technical analysis (TA) uses historical price movements, real time data, indicators based on math and/or statistics, and charts; all of which help measure the trajectory of a security. TA can also be used to interpret the actions of other market participants and predict their actions:
Measure: Is the security's price trending, has it dipped or is it a falling knife? Interpret: Does the current price mean investors think it's undervalued or overvalued; when did they buy/sell more and why? Predict: If price reaches a certain point, will there be a rally or get rejected?
The main benefit to TA is that everything shows up in the price (commonly known as priced in): All news, investor sentiment, and changes to fundamentals are reflected in a security's price.
TA is best used for short term trading, but can also be used for long term.
Intro to technical analysis by Stockcharts chartschool and their article on candlesticks
Terminology
Useful indicators
Methods or Systems
Strategies: See the TA wiki here as this will be a work in progress, feel free to reply with your own strategy.
See our past daily discussions here. Also links for: Technicals Tuesday, Options Trading Thursday, and Fundamentals Friday.
submitted by AutoModerator to stocks [link] [comments]

r/Stocks Technicals Tuesday - Dec 04, 2018

Feel free to talk about technical analysis here (not argue against it), but before you ask any question make sure you see the following information:
Technical analysis (TA) uses historical price movements, real time data, indicators based on math and/or statistics, and charts; all of which help measure the trajectory of a security. TA can also be used to interpret the actions of other market participants and predict their actions:
Measure: Is the security's price trending, has it dipped or is it a falling knife? Interpret: Does the current price mean investors think it's undervalued or overvalued; when did they buy/sell more and why? Predict: If price reaches a certain point, will there be a rally or get rejected?
The main benefit to TA is that everything shows up in the price (commonly known as priced in): All news, investor sentiment, and changes to fundamentals are reflected in a security's price.
TA is best used for short term trading, but can also be used for long term.
Intro to technical analysis by Stockcharts chartschool and their article on candlesticks
Terminology
Useful indicators
Methods or Systems
Strategies: See the TA wiki here as this will be a work in progress, feel free to reply with your own strategy.
See our past daily discussions here. Also links for: Technicals Tuesday, Options Trading Thursday, and Fundamentals Friday.
submitted by AutoModerator to stocks [link] [comments]

r/Stocks Technicals Tuesday - Dec 18, 2018

Feel free to talk about technical analysis here (not argue against it), but before you ask any question make sure you see the following information:
Technical analysis (TA) uses historical price movements, real time data, indicators based on math and/or statistics, and charts; all of which help measure the trajectory of a security. TA can also be used to interpret the actions of other market participants and predict their actions:
Measure: Is the security's price trending, has it dipped or is it a falling knife? Interpret: Does the current price mean investors think it's undervalued or overvalued; when did they buy/sell more and why? Predict: If price reaches a certain point, will there be a rally or get rejected?
The main benefit to TA is that everything shows up in the price (commonly known as priced in): All news, investor sentiment, and changes to fundamentals are reflected in a security's price.
TA is best used for short term trading, but can also be used for long term.
Intro to technical analysis by Stockcharts chartschool and their article on candlesticks
Terminology
Useful indicators
Methods or Systems
Strategies: See the TA wiki here as this will be a work in progress, feel free to reply with your own strategy.
See our past daily discussions here. Also links for: Technicals Tuesday, Options Trading Thursday, and Fundamentals Friday.
submitted by AutoModerator to stocks [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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Fisher App Review 2015 - Is Fisher App SCAM Or LEGIT? Binary Options Trading Signals System. Fisher Method By Jacob Clark Review

Fisher App Review 2015 - FISHER APP?? Discover the Truth about the Fisher Method in this Fisher App review! So Exactly what is Fisher App Software all about? Does Fisher App Actually Work? Is Fisher App Software application scam or does it really work?
To discover answers to these concerns continue reading my in depth and honest Fisher App Review below.
Fisher App Description:
Name: Fisher App
Niche: Binary Option Trading Signals.
The Fisher App Is A Custom High Quality App Built From Scratch! The Fisher APP is 100% developed in house. Its based on very solid trading indicators and designed by a top UX designer. The Fisher Method is not new at all. Universities around the world have been using this statistical formula for a long time. Why haven't private traders used this formula to their advantage? Because its very complicated to calculate in real time while trading. That's why Jacob has decided to create this brilliant formula called the Fisher App!
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What is Fisher App?
Fisher App is basically a binary options trading software application that is created to help traders win and predict the marketplace trends with binary options. The software also provides analyses of the market conditions so that traders can understand what should be your next step. It provides different secret methods that ultimately helps. traders without using any complex trading indicators or follow charts.
Fisher App Binary Options Trading Method
Base the Fisher App trading method. After you see it working, you can start to execute your technique with regular sized lots. This approach will certainly settle over time. Every Forex binary options trader should select an account type that is in accordance with their requirements and expectations. A larger account does not suggest a bigger revenue potential so it is a fantastic concept to begin small and slowly add to your account as your returns increase based on the trading selections you make.
Binary Options Trading
To assist you trade binary options effectively, it is necessary to have an understanding behind the fundamentals of Binary Options Trading. Currency Trading, or foreign exchange, is based on the viewed value of 2 currencies pairs to one another, and is affected by the political stability of the country, inflation and interest rates among other things. Keep this in mind as you trade and find out more about binary options to optimize your learning experience.
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Simple to understand video training explaining the Fisher Method and how to profit with it
Personal 1 on 1 Support
Chat directly and 1 on 1 with trading experts.
Private Community
Watch the live results all verified by an independent 3rd party
How long before I will see profits?
It depends! But as you will see on the membership area page it can go very quickly! On that page Jacob sets up an account live in front of your eyes and Jacob even mange to catch 2 profitable trades, all within about 8 minutes!
Fisher App Summary
In summary, there are some evident concepts that have been checked in time, as well as some newer methods. that you might not have considered. Hopefully, as long as you follow exactly what we suggest in this article you can either get going with trading with Fisher App or improve on what you have already done.
Meet Jacob, check out the free presentation to see what everybody in the financial world is raving about: As a Professor or Statistics and honorary Professor of Mathematics Jacob has over 100 published research articles. All these papers are related to statical calculus and algorithms. Jacob not only teach statistics, but have used it to earn over $5M trading Binary Options over the last 3 years. Now the Fisher APP™ is finally available to the public.
Click Here To Claim Your Fisher App LIFETIME User License!!
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BEST Forex Trading Strategy To Make $1000 per Day in 2019 ...

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