BacktestMarket - High quality Historical Data

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submitted by ViralMedia007 to FREECoursesEveryday [link] [comments]

How reliable are free sources for historical data?

Has anyone used free sources like histdata.com, dukascopy, forexsb to train models or backtest their algos?
I am working on training a model to trade forex pairs. Still experimenting with the idea and don’t want to invest in an data api before I have a solid strategy.
Wondering if I can make use of this data to test the model with this data and move on to test the model with something paid afterwards OR just go with a single data source as best practices would say.
Thanks in advance!
submitted by vikas-sharma to algotrading [link] [comments]

Historical Data on stocks/options

So I have googled this a couple times and I usually can't find anything, I was wondering if anyone here knew of some websites were you can get historical data on options prices. Even more interesting would be the ability to backtest a strategy but I doubt that would be something anyone would give away for free. I would also be interested in historical data on stocks as well.
I know in Forex the "50" pips a day strategy is pretty common and is basically just a straddle. You set two orders a buy and a sell, the buy to trigger if the price rises by 2 pips and the sell if the price lowers by 2 pips, then you cancel the other. I would be interested to know if something like this would work on open, as the voltality is usually so much higher.
I was also wondering how "Top Mover's" on the day and on the week perform historically, so if you bought puts on these would you make money. I suspect not for a couple reasons but i'd still be interested to know.
I guess the big question with anything is not if your winning everytime but if you making enough on your winners to cover the losers, and thats what I would need to see. Any help is much appreciated.
submitted by vaderlaser to options [link] [comments]

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]

Conflicting BTCUSDT historical Data from Pinned Post

Hi all. I followed the pinned instructions on how to download historical btc data, but I am seeing a discrepancy. I pulled minute data from August and compare recent ticks to binanance.com and the data is different as you can see in the screenshot below. Has anyone experience this before?

https://preview.redd.it/c1cdrfni1ng51.png?width=1048&format=png&auto=webp&s=13d6e884cee0a9e40367fd474060fac9a5d681d6
submitted by RobsRemarks to algotrading [link] [comments]

The best crypto trading bot platform now has a free plan!

What is CLEO.one? CLEO.one, brings powerful, well informed trading automation to independent traders that don’t want to spend time on coding, but need to be present in the markets 24/7, with perfect execution is now free to use when trading on Binance! Strategies are created through simple typing. They can be tested for crypto, forex and stocks, deployed on live trading as crypto bots or paper traded and demoed on real time market conditions. We support the biggest crypto exchanges.
Can I create a grid/dca/specific type of bot? You can create any type of bot you please. The level of flexibility should accommodate any style of trading.
What makes CLEO.one different?
CLEO.one contains more data than any other platform and it can be combined in infinite ways to allow traders to craft any strategy they have in mind. Price action, technical indicators, crypto fundamentals, candlestick patterns, market caps, dominance correlation with other assets – all out of the box.
Trading results are packed with clarity and statistics. This helps you advance your trading by being able to zoom in on any detail, even if you are trading many strategies. CLEO.one lets you test your trading strategies, no matter if they are simple or complex in minutes. Historical data runs back 50 years on the assets that have that much history. You can then automate your trading, or demo your strategies on papertrading.
The first platform that works for crypto, forex and stock traders, allowing them to shrink their strategy creation time by doing it all through simple typing. More data than anywhere else on the web and backtesting so easy that anyone can do it. Independent traders finally get radically better crypto bots and sophistication through simplicity for any asset that they dabble in.
In case you are still trading without a trading strategy, you might find it hard to improve your actions or improve your trading results. CLEO.one features free strategies, all profitable when historically tested that you can modify or straight up trade.
What can I do in CLEO.one? • Create crypto, forex or equities strategies through simple typing • Backtest trading strategies for crypto, forex and equities • Crypto strategies can be automated on the exchange of choice as crypto bots • Place trades with simultaneous Trailing Take Profit and Trailing Stop Loss • Papertrade to test out strategies in current market conditions • Use free, profitable when tested strategies
Who is CLEO.one for? CLEO.one is easy to use and approachable even for traders that are starting out. Under the hood it has more than enough power to satisfy even the most experienced omni-asset traders. • Crypto traders that want to create, test or automate their trading • Forex traders that want to test or papertrade their strategies • Stock traders that want sophisticated asset selection
Who owns my strategy? You do, as stated in our Terms & conditions . Unless it is something super common like “when RSI is above 30.” The algorithm is in CLEO.one and we have permission to run it though our Services. The full Terms & conditions can be found here and are available on every page of the site at the bottom.
How do I get help? - We do free onboarding calls! If you’d like to set up something specific or have a walkthrough we would love to help! - Our responsive staff will answer any question you might have – reach out via chat on CLEO.one. - The CLEO.one helpdesk is always available and growing.
So is it really for free? When trading via Binance it is 100% free. Our subscription plans of €249, €149, and €69 apply only when you do not connect a Binance account. You do need to fulfill 2 conditions for the Binance account: 1. Needs to be created after July 21, 2020 2. Cannot be created using a referral code That’s it! In case you need to create a new account feel free to - no KYC.
You probably still have questions…
Can I make money with your bot? We do not sell a bot, but help you work on your strategies and automate the best. Or place one-off trades with simultaneous (trailing) stop loss and take profit. You become a better trader, you don’t have to rely on shady signals, you get to achieve your long-term trading goals. We do feature strategies that are all tested when profitable and you are free to test them, change them or straight up trade them.
Is it safe? You never transfer any funds to us, everything stays on the exchange.
Do I have to link and account to try the platform? No, we have a freemium version that lets you create strategies and backtest them.
You can find the details here or check out the offer. Thank you! We're happy to help with anything.
submitted by CLEOone to CLEOone [link] [comments]

Naked Forex Noob

TL;DR Just got into Naked Forex trading but I am stuck on backtesting. Can't correctly identify critical zones (supp and res zones) and I haven't found the criteria for my trading system (wammies and moolahs) on the charts that I have back tested. Any advice?

Hi there, I started learning about forex awhile back from a friend and he began to show me the basics while also directing me to babypips for the free course they put you through. Although I got into all of this awhile back, I have been stuck in the stages of finding my own strategy and backtesting it.
At first, I was very much into using the basic indicators (RSI, MACD, SMA/EMA) but then I came across a recommendation in this sub to read 'Naked Forex' and I was hooked. Not in a sense that now I knew exactly what my strategy was and how to implement it, but hooked in the idea of being able to read a chart and make trades based on price action and reversals.
Of course while reading the book, understanding the concepts, and looking at all the examples of the different trading strategies i'm getting hyped in my mind to get to the backtesting stage to see if I can put this knowledge to somewhat of a test. Now here I am, staring at tradingview's daily and 4h charts from 2006 onward.
Here's where I get stuck.
I understand identifying critical support and resistance zones and it all made sense to me in the book, but as I am backtesting I find that the zones are either always changing or I can't figure out which ones are critical. On top of that, my trading system looks something like this (advice is welcome on how this could be improved or if you see any glaring "wtfs" in it)
I trade wammies & moolahs (market touches supp. or res. zone twice, second touch is lowehigher with a bearish/bullish candlestick printed on the 2nd touch) and use either a kangaroo tail or big shadow for confirmation to initiate the trade.
The buy/sell stop is set 8 pips above/below the bearish/bullish candlestick and the stop loss is placed below/above the first touch.
The profit target is the following zone.
There's a bit more criteria for the trade but that's the blueprint of it. I apologize if it either doesn't make sense or confuses you but even after sifting through months/years of backtesting data my eyes never caught any of this action happening in the zones I've identified.
Any help would be appreciated as I am a sponge and will soak in as much criticism and advice as I can.
submitted by VileKyleTM to Forex [link] [comments]

How to derive historical financial data for forex instrument backtesting

Hello,
If you believe backtesting strategies for forex major currency pairs is unhopeful please leave a comment with an explanation.
I'm a CS major at Columbia with internships in back office global bank infrastructure positions here in NY and have great interest in trading algorithmically because I can't trust my behavior to enter trades, among other obvious reasons.
I would like to know what the best sources are for obtaining historical data (OHLCV, etc) for (forex) backtesting purposes. Is a large excel file used in practice, or are historical prices derived via API's? It seems that I need to pay after some research online, but I know you redditors can deliver.

edit
I found a free source here for EURUSD. There are other pairs available too.
submitted by Reciprocates to algotrading [link] [comments]

HOWTO acquire BitMEX historical price data using Python (working code included) for algo trading and backtesting

Hello! I wrote this HOWTO as part of a series of posts on getting historical tick and bar data for various financial products. I've included some custom python code that connected through the BitMEX API and I thought people here might find it useful!
HOWTO acquire BitMEX historical price data using Python (working code included) for algo trading and backtesting
Any comments or feedback is welcome! Cheers!
submitted by finance_student to BitMEX [link] [comments]

HOWTO download Binance historical price data using Python (working code included) for free!

Hello! I wrote this Instructional Post as part of a series on getting historical tick and bar data for various financial products. I've included some custom python code that connected through the Binance API and I thought people here might find it useful. :)
Change the 'BTCUSDT' at the bottom of the included python code to whichever symbol you'd like to pull data on. It's that simple! :)
HOWTO download Binance historical price data using Python (working code included) for free!
Any comments or feedback is welcome! Cheers!
submitted by finance_student to BinanceExchange [link] [comments]

HOWTO download BitMEX historical ETHUSD price data using Python (working code included) for free

Hello! I wrote this HOWTO as part of a series of posts on getting historical tick and bar data for various financial products. I've included some custom python code that connected through the BitMEX API and I thought people here might find it useful!
ETH traders can get minute bar data for entire history of BitMEX's perpetual contract by changing the symbol to "ETHUSD" in the code provided in this post:
HOWTO acquire BitMEX historical price data using Python (working code included) for algo trading and backtesting
Any comments or feedback is welcome! Cheers!
submitted by finance_student to ethtrader [link] [comments]

Can the simplest forex indicators make you a millionaire?

This was a question on Quora I have recently answered for and thought some of you here might find it useful.
So I insert it here:
#####
Do you want to be a millionaire trading Forex with indicators? Well, of course, you do...why would you post this question to Quora otherwise?
The REAL question is – how do you do it?
There are countless different technical indicators out there, so where do you start? Where do you focus your valuable time and money?
Let's understand first what Forex indicators are. In essence, they are tools that turn the already available price data into something else. You've read it right. They don't provide any new information you couldn't get simply by looking at the chart.
But there are still people who get amazing results with indicators. Have they invented a secret tool that actually moves the needle?
I'm not Tyrion Lannister to tell this to you, but it's probably not the case. As far as I know, there tends to be one reason why somebody is crushing it with technical indicators while others don't.
And it has nothing to do with the indicator or indicators being used.
So what I am talking about?
It's the personality of the trader that matters. Just think about it:
Indicator-based trading is more objective than price action trading. You can argue about whether a chart pattern is present, but there's no argument about an indicator's direction.
I really don't want to get into the age-old debate of which one is better because the answer varies from person to person. The point is that you have to find out which works for you.
It's not a complicated process, although requires a lot of time. Can you guess what it is? I know you can, it's called testing.
If I told you to start boxing because it works for Mike Tyson, chances are you would laugh at me. Then, in the same way, don't put money into random indicator just because somebody allegedly makes millions using it.
That somebody might has a large trading capital, a perseverant attitude, years of experience and a system you will never able to follow because it goes against everything you are comfortable with.
You have to test different indicators as well as price action techniques. By doing so, you will know which approach best suits you. Also, you will naturally figure out which of the specific indicators, chart patterns, candlestick patterns, etc., performed the best.
You can use free tools like MetaTrader's strategy tester feature or TradingView's market replay. Also, you can invest in backtesting software such as ForexTester.
####
Have a nice day!
submitted by marcellpetras to Forex [link] [comments]

Best Crypto Trading Bots 2019

Best Crypto Trading Bots 2019
WolfpackBOT - The World's Fastest Crypto Trading Bot

https://preview.redd.it/s5j8hgsgsi131.png?width=799&format=png&auto=webp&s=e0e5597fa32aa74f78fcfbb5cc08d143f8b8ca3b
There are basically two different ways you can make mazuma from digital currencies. You can purchase a couple of coins currently, hold them for an extensive period and offer them after the esteem has risen significantly or you can get started with exchanging digital forms of money, here once more, you can exchange physically or run with the best crypto exchanging bots. While holding cryptographic money for a more drawn out term has turned out to be fulfilling, it takes a bounty of time and tolerance for you to optically observe the estimation of your speculation increase.If you are somebody, who does not have the persistence to hang tight for so long, at that point digital currency trading provides you with the immaculate chance to make some mazuma. Numerous prosperous digital currency dealers do recommend you purchase low and sell high. In any case, this is easier verbalized than done.
Digital currencies have been cosmically unpredictable since the earliest reference point. They are the main tradable resources whose esteem shifts in twofold digit rates every day. The cost does not generally go up either. Along these lines, timing the market is the way to turning into a prosperous cryptographic money merchant.
Exchanging digital money isn't any advanced science. All you require is a record on a digital money trade and some cryptographic money in your wallet. This would have been the situation, had you started exchanging these computerized resources route in 2010.
Presently, on the off chance that you try to put in any limitation request on any famous cryptographic money trade, you will outwardly see another application set appropriate above you're, putting forth a superior arrangement. Hence, you are constrained to put orders at market esteem.
The way that a superior offer quickly negated your offer does not assign that somebody is continually crushing before the PC. You just set off crypto exchanging bot when you submitted your request. The best bitcoin exchanging bots have surmounted the whole cryptographic money exchanging biological system, and this is primarily because of the way that they are more effective than people, particularly when it comes down to exchanging.
Presently that you ken that bots have surmounted the crypto exchanging market, you more likely than not understood as of now that the chances of making mazuma when piled facing a great many bots are cosmically svelte.
You could ace all the distinctive specialized investigation strategies and exceed the bots. In any case, in addition to the fact that this is tedious withal very tedious. So instead of investing more energy finding out about the specialized investigation, you can set up the crypto exchanging bots all alone. By the end of this article, not exclusively will you ken probably the most profitably rewarding cryptographic money exchanging bots out there, yet moreover will be enabled with the intelligence of winnowing your very own exchanging bot later on.
Variables to Look for When Culling the Best Crypto Trading Bots
  1. Dependability
A standout amongst the most vital viewpoints to consider is the dependability of an exchanging bot. You would not operate to lose on a brilliant open door because your crypto bot went disconnected or stopped working for quite a while.
You may contend that there is no real way to make sure about the dependability of a specific exchanging bot. Notwithstanding, you aren't the just a single using a bot. Scan for what alternate clients who have used a particular bot need to verbally express about its consistent quality or basically allude to our rundown of the best bitcoin exchanging bots underneath.
  1. Security
With regards to cryptographic forms of money, you can't inculpate anybody yet yourself if there should be an occurrence of a hack. When you initiate using an exchanging bot, you are giving the bot access to your mazuma. This can be very jeopardous, particularly if the exchanging bot is beginning in the field.
There is no telling how secure a specific bot is. In this way, while separating an exchanging bot, complete quintessential research and winnow a bot that has been broadly extolled for its security.
  1. Productivity
Everything comes down to this fundamental part. Is the bot profitably worthwhile or not? An inquiry for which it is elusive an answer. The primary reason you chose to run with an exchanging bot is to benefit over its exchanging ability. There is no influential pertinence in using a bot that isn't profitably rewarding. In this way, discover the productivity of a bot up to you put both your time and mazuma into it.
  1. Straightforwardness
The fundamental motivation behind why digital currency rose to acclaim is that the entire system is plenarily straightforward. There is the wrong spot for any injustice. The equivalent ought average even from the exchanging bot that you choose to run with.
Attempt to winnow a bot whose engineers are unmistakable for their work in the network. Straightforwardness benefits to fabricate trust as well as also profits you to connect with the ideal individuals to adjust any issue.
  1. Simplicity of profit
The entire cogency of running with a robotized bitcoin exchanging is to make the whole procedure of transferring cryptographic forms of money simple for everybody. A bot which accompanies a simple to use interface is the one that is exceptionally well known. Having the capacity to control the bots with only a couple of snaps of the mouse is something you should pay individual mind to, in the bot that you choose to use.
Considering every one of the variables we have arranged a rundown of the best ten digital currency exchanging bots in 2019, the review will be unendingly refreshed with the goal that data remains apropos.
Top 10 Best Crypto Trading Bots in 2019
  1. Cryptohopper
This may be a new bot in the crypto exchanging market. In any case, this newcomer has figured out how to blow some people's minds because of the comprehensive exhibit of highlights that this bot gives. One of the defeats of most exchanging bots is that they kept running on your neighborhood machine. This betokens they run just when you have turned on your PC.
With the lift in enthusiasm for cloud-predicated advancements, Cryptohopper uses cloud innovation to keep the bot running day in and day out. By running the bot on a cloud, clients will most likely put in exchange requests notwithstanding amid the night. In this manner, no open door is missed.
Another critical reason that prompted the lift in the notoriety of Cryptohopper is its simplicity of usage, particularly for the tyro. The bot has incorporated with an outside exchanging signaller. This assigns anybody can initiate using this bot by running it on autopilot. This is a help to the nascent dealers, who need not stress over setting exchanging signals for their bot. The bot withal gives progressively experienced clients a chance to mess around and set their own exchanging signals. Along these lines, it is satisfying the desiderata of both. Aside from this, the bot is incidentally outfitted with highlights, for example, trailing stops, specialized examination, formats, and backtesting. Formats benefit you to design a nascent setting for your bot quickly, and specialized investigation sanctions you to redo and arrange your own settings.
Like every extraordinary thing, the crypto container comes with a sticker price fastened to it. The cost starts from $19 every month for the fundamental arrangement and goes up to $99 per month if you operate their most extravagant arrangement. When you buy into any of the organizations, you can start using the bot on prominent trades like Binance, Huboi, Kucoin, Bittrex, Coinbase, Poloniex, Kraken, Cryptopia, and Bitfinex. On the off chance that you are slanted to spend the additional buck on an exchanging bot, at that point Cryptohopper is an extraordinary separate.
  1. 3Commas
Even though 3Commas bot is nascent to the exchanging bot scene, it could give its clients huge increases, notwithstanding amid the crypto bear showcase.
The new element that dissevers this bot from other bots is its workforce to trail any crypto advertise. This authorizes the bot to close the exchange at the most profitably excellent position, yet the objective addition set by the utilizer had just been come to. This element benefits enormously amid the crypto bull run. Additionally, the bot adventitiously endorses clients to exchange numerous cryptographic forms of money simultaneously. In this manner, it is not passing up any great exchanging opportunity that goes along the way. The bot is set up on the cloud and is available through the site. This betokens the bot runs 24X7. The bot can be designed with Binance and Bittrex at this moment and increasingly legitimate trades, for example, BitFinex, Poloniex, KuCoin, and so forth will be coordinated anon.
The 3Commas comes with a sticker price appended to it. The starter plan will cost you $24, and the most luxurious genius pack would set you back by $82. On the off chance that you operate to give crypto bot exchanging a go, at that point, you could use the 3Commas starter plan and later peregrinate to the more rich schemes.
  1. Gunbot
This is another mainstream exchanging bot with more than 6000 dynamic merchants using its lodging on a quotidian substructure. Good with a few exchanging stages including Binance and GDAX, it very well may be kept running on your nearby PC. This can keep running on Windows, Linus, and the Mac stages, so running on your neighborhood machine would not be a bind.
The bot has 32 diverse pre-arranged exchanging systems which give clients a wide cluster of choices to induce some automated revenue. Among these techniques, the three most well-known ones are the Bollinger band, step addition, and ping pong. Numerous clients have detailed having made a bounty of benefits with the BB procedures. Gunbot isn't in freedom to use and accompanies a one-time level rate running from 0.1BTC to 0.3BTC, contingent upon the highlights that you would savor to optically observe in the bot. Aside from this, the bot supplementally comes as a Lite rendition that has encircled highlights yet can be habituated to test around with the lesser measure of mazuma.
The post-buy support given by the organization is truly surprising. Clients get their issues settled in less than multi-day. The main pickle with regards to this bot is that you ought to in every case reliably outwardly look at the present market state. If the instability of the crypto advertise is high, at that point you ought to most likely turn the bot off to shun any misfortune
  1. Gekko
This is the most diverse digital money exchanging bot in subsistence at present. For any individual who needs to gain proficiency with some things about exchanging bots and not spend any mazuma getting one, at that point Gekko is the bot for you. The Gekko trading bot is an open source bitcoin exchanging bot venture that is accessible for anybody to use for nothing. The way that it is in freedom to use is the fundamental purpose behind its wide prevalence. Like some other open-source ventures, Gekko is free of for all intents and purposes all bugs and even the ones the pop are fixed up at lightning speeds. The Gekko bot can collaborate with a few trades, including Bitfinex, Polonix, and BitStamp. The bot uses a web interface to associate with the clients and can keep running on a neighborhood machine with Windows, Linux, or the Mac OS.
The bot comes pre-designed with some exchanging system. You can initiate using the bot on autopilot as anon as you introduce and design it with a trade. In any case, if you would savor to use your very own exchanging system, the bot withal endorses you to design it to your savoring. While the present design is respectable for trying different things with the bot, there are a few other exchanging techniques accessible online that would benefit you make an all the more profitably worthwhile wager. The bot will withal send you a notice at whatever point it executes a specific exchange. This is finished by incorporating it with the Telegram envoy. Consequently, you will dependably ken how well your bot is performing.
The main drawback to the Gekko exchanging bot is that it isn't very utilizer-heartfelt. There are a few aides in the digital world that direct you through the underlying setup process. Be that as it may, this procedure isn't extremely direct and you would presumably hit a barricade at any rate once amid the underlying setup.
  1. Zenbot
Another allowed to use digital currency exchanging bot, Zenbot can be considered as a further developed form of the Gekko exchanging bot. Nonetheless, as Gekko has been around for a more extended time, it is all the more generally used. Much the same as Gekko, Zenbot programming can be downloaded from Github and introduced on your neighborhood PC. The product is perfect with Windows, Mac just as the Linux working frameworks. The bot comes pre-arranged with an entirely nice exchanging system. In any case, its real potential can be opened only when you initiate executing your exchanging order. The primary bind with the allowed to use bots is that they are frequently not very utilizer-genial. In any case, this isn't the situation with Zenbot. The entire setup process is extremely effortless, and you can have the bot fully operational in all respects speedily. The bot chips away at all prevalent trades, for example, Bitfinex, Poloniex, Bittrex, and so on.
As it is an open source venture, it is without now of a few bugs, and regardless of whether one springs up, it will be adjusted all around speedily. The Zenbot can effortlessly actualize with a few informing stages, for example, slack, Telegram, and so on to give you the updates of any exchange that was executed.
Adventitiously, the Zenbot withal braces high-recurrence exchanging. This is a component that outlined the personnel of the Gekko bot. The Zenbot is being refreshed, and more highlights are being incorporated traditionally. Hence, making it a bot for you to reliably outwardly analyze.
  1. WolfpackBOT: WolfpackBOT is a cryptographic money exchanging programming application that has been created with the most developed highlights of any robotized exchanging programming of its sort. The WolfpackBOT has been intended to execute exchanging directions with the usage of restrictive numerical calculations, and specialized investigation bespeakers predicated on the client's predefined assignments.
The cryptographic money advertise as of now bearish, and many exchanging bots easily miss the scarcest vacillations. WolfpackBOT has been built to execute trading directions at a lightning speed and is fit for making up to a large number of exchanges every day, relying upon the states of the market.
WolfpackBOT is among the few cryptographic money exchanging bots that give crypto aficionados full self-governance, security, and control of their exchanging bot and its related API keys. A large portion of the crypto trading bots out there are cloud-predicated stages that are constrained by outsider frameworks. While these stages guarantee dealers of outright wellbeing and security, insightful brokers ken that in the crypto space, outsider frameworks like trades and other cloud-predicated steps are hacked proximately consistently. Since WolfpackBOT programming and your related API keys are put away individually PC or devoted VPS, WolfpackBOT can sidestep a significant number of the security issues related to cloud-predicated frameworks.
WolfpackBOT has been created for the whole crypto network, from experienced merchants to novices, with three in all respects reasonably valued membership levels. WolfpackBOT accompanies a few membership bundles that authorize clients to exchange with a wide scope of chances predicated on their favored membership.
  1. CryptoTrader
cryptotrader_reviewAlmost all digital money merchants would have aurally seen about the crypto dealer exchanging bot. The across the board fame of this bot is because it was one of the absolute first bots to be kept running on the cloud and accessible to the clients day in and day out.
The crypto broker bot is plenarily web-predicated and in this manner, open from anyplace you can associate with the digital world. The bot can be easily designed with a few well-known trades, for example, Poloniex, Bittrex, Kraken, and so on. This bot does not come for nothing out of pocket. You can operate from the few organizations accessible. The valuing initiates with 0.003BTC every month for the most simple arrangement and this goes up to 0.0472 BTC every month for their excellent arrangement.
While all plans do offer clients support for programmed exchanging, the early highlights and as far as possible for the more indulgent plans is higher than that given the basic arrangement. Any early component that is caused is most readily accessible on the higher bundle designs and are later accessible on the basic plans. On the off chance that you would simply savor to exchange on a solitary trade and with exceptionally delineated mazuma, at that point the basic arrangement will get the job done. Be that as it may, on the off chance that you are outwardly looking at the higher volume of exchanges, at that point run with the higher bundle.
This bot additionally sustains algorithmic exchanging. In this manner, I am making it effortless for clients to execute their very own arrangements. The bot can be effortlessly modified. In this manner, I am making it a broadly utilized cryptographic money exchanging bot.
  1. Bitcoin Robot
btcrobotWe simply needed to incorporate the pioneer of digital currency exchanging bots on our rundown of the best crypto exchanging bots. The Bitcoin robot started as a Bitcoin exchanging bot. In any case, it can now withal be designed to exchange different digital currencies, for example, Ethereum and Litecoin. The bot is accessible as a product and should be downloaded and keep running on your neighborhood machine. This betokens the exchanges will be executed just as long as you keep your PC turned on. The bot can effortlessly work with a few digital money trades and is by and large broadly utilized even today. The bot isn't accessible free of expense and costs you a premium. The cost of the bot ranges from $19.99 every month for the principal plan. In any case, clients usually buy the platinum plan that costs just $399 one time charge and offers utilizer unlimited access to every one of the highlights.
The benefits made by individuals using this bot verbalizes for itself. Supplementally, they do offer a 60-days mazuma back assurance. Along these lines, you should look at them once.
  1. USI Tech
This can't be considered as a bot. In any case, the USI tech BTC settlement promises mechanized benefits for your BTC speculations. The USI Tech was at first intended for Forex exchanging. In any case, after the raise of the ubiquity of Bitcoin, they additionally offer BTC bundles. Not at all like some other BTC exchanging bot where you require to give the API key of your trade account to execute exchanges, on USI Tech, you will require to winnow from among the few BTC master exchanges. At that point, you will begin accepting your segment of benefits at whatever point exchange is made.
The USI Tech stage basically ensures extraordinary comes back to your speculations. The entire procedure of purchasing your absolute first BTC bundle is withal simple and pellucidly elucidated on their site. You can explore different avenues regarding the benefits that you gain. In any case, the number of bundles you purchase, the more dominant will be your benefit
  1. Margin.De (Leonardo Bot)
Edge LeonardobotThis is a cryptographic money exchanging bot with the most utilizer-genial interface. The GUI of the bot is easy to use, and the highlights gave are extremely puissant. The bot was structured with two exchanging techniques ping pong and Margin exchanging actualized into it. In any case, you can withal modify it with your very own custom settings. This bot lays incredible complement on the visual parts of exchanging. The specialized examination done by the bot is immensely simple to break down. What more? The bot has an astonishing component called visual exchanging. This interface feels rich smooth to use and offers clients the most extreme authority over the exchanges.
The bot was at first evaluated at 0.5 BTC consistently. Notwithstanding, presently, it is accessible at a one-time cost extending from $89 to $1999 with the most elevated arrangement offering a bigger number of highlights than th
submitted by restpage123 to digitalseo [link] [comments]

Free Forextory Trading Tool - Best Forex Trading Simulator 2019

If you wanna backtest your system or practice trading strategies manually with the tick data 99% (exact to milliseconds), feel free to use this tool👇
Free Forextory Trading Tool - Best Forex Trading Simulator 2019

forex #forextradingtool #tradingsimulator

submitted by divergentami to FOREXTORY [link] [comments]

Forex Trend Trading - The Trend is Your Friend

Electronic currency trading is fast becoming Forex Millennium Review a widely popular forex investment venture. This is where you use the Internet and a few software applications to go about your daily forex data providers are hooked up to an electronic forex trading platform. These providers send out forex data including historical foreign exchange information good for forex backtesting, alerts, signals and news.

There are computer applications which can aid you in your trades. These have preconfigured systems which handle trade decisions and predictions based on its updated database of current forex information sent by the electronic currency trading platform itself or any of the forex data providers in its list. The built-in systems of these computer programs are also designed to interact with the decisions, trading styles and predictions of beta users, prioritizing stored user data with the least percentage of trade losses in comparison to its current forex database information. Also, most of these beta testers are popular forex specialists and investment advisers.

To profit from your ECurrency trading ventures, you need to identify the best platform to use. Ask around for advice from your friends and colleagues with knowledge and experience in electronic forex trading.Also consult reputable sources of information about these platforms and software applications. These can include popular forex specialists, finance advisers and investment consultants.

Make sure that your computer is free from malicious programs which can steal your private information. This can be a bigger problem, especially if your forex trading applications and the platforms where you go about your daily trades are compromised. You may not even know that your computer is already sending out confidential data, related to your forex trading ventures or otherwise, to predesignated servers, all while you're using these electronic currency trading platforms.

https://discountdevotee.com/forex-millennium-review/
submitted by adamssmith8754 to u/adamssmith8754 [link] [comments]

After 9 months of obsession, here is my open source Node.js framework for backtesting forex trading strategies

TL;DR There's lots more to the story. But the code is all open source now. Have at it. I'm too exhausted to continue with this. If you'd like more details, feel free to message me. If you happen to carry on with this project or use any ideas from it, I would greatly appreciate it if you could keep in touch on your findings. If anyone has any insights, please feel free to comment or message me.
I've spent the last nine months working furiously on this. I started a project for backtesting strategies against data I exported from MetaTrader. I had a very powerful computer crunching numbers constantly, trying to find the most optimal configuration of strategy indicator inputs that would results in the highest win rate and profit possible.
Eventually, after talking with a data scientist, I realized my backtesting optimizer was suffering from something called overfitting. He then recommend using the k-fold cross-validation technique. So, I modified things (in the "k-fold" forex-backtesting branch), and in fact it provided very optimistic results when backtested against MetaTrader data (60 - 70% win rate for 3 years). However, I had collected 3 months of data from a trading site (by intercepting their Web Socket data), and when I performed validation tests against that data using the k-fold results created from the MetaTrader data, I only got a ~57% win rate or so. In order to break even with Binary Options trading, you need at least a 58% win rate. So in short, the k-fold optimization results produce a good result when validation tested against data exported from MetaTrader, but they do not produce a good result when validation tested against the trading site's data.
I have two theories on why this ended up not working with the trading site's data:
For the strategy I use the following indicators: SMA (Simple Moving Average), EMA (Exponential Moving Average), RSI (Relative Strength Index), Stochastic Oscillator, and Polynomial Regression Channel. forex-backtesting has an optimizer which tries hundreds of thousands of combinations of values for each of these indicators, combined, and saves the results to a MongoDB database. It can take days to run depending on how many configurations there are.
Basically the strategy tries to detect price reversals and trade with those. So if it "thinks" the price is going to go down within the next five minutes, it places a 5 minutes PUT trade. The Polynomial Regression Channel indicator is the most important indicator; if the price deviates outside the upper or lower value for this indicator (and other indicators meet their criteria for the strategy), then a trade is initiated. The optimizer tries to find the best values for the upper and lower values (standard deviations from the middle regression line).
Additionally, I think it might be best to enter trades at the 59th or 00th second of each minute. So I have used minute tick data for backtesting.
Also, I apologize that some of the code is messy. I tried to keep it clean but ended up hacking some of it in desperation toward the end :)
gulpfile.js is a good place to start as far as figuring out how to use the tools available. Look through the available tasks, and see how various "classes" are used ("classes" in quotes because ES5 doesn't have real class support).
The best branches to look at are "k-fold" and "master", and "validation".
One word of advice: never, ever create an account with Tradorax. They will call you every other day, provide very bad customer support, hang up the phone on you, and they will make it almost impossible to withdraw your money.
submitted by chaddjohnson to algotrading [link] [comments]

IAmA profitable discretionary Forex trader..

/trading and /forex are dead so I thought I would post in here. Feel free to ask me anything. I am not a guru, and am just looking to help aspiring traders by cutting through the many misconceptions that exist around trading.
I have spent a LOT of time learning how to trade consistently and profitably. I have also spent a LOT of time learning how to do things that do not work. What works for me may differ with what works for you, I can only comment based on my own experience of what works.
I have tried using hundreds of different indicators and combinations thereof, I have also done extensive backtesting and data mining and can advise somewhat on my experience with that. I have tried trading with EAs.
However, these are things that do not work for me.
I consistently and profitably trade using horizontal support and resistance and a fibonacci scale. This method is sometimes referred to as "Price Action" or "Naked" trading in online forums. I also use angular support and resistance (trendlines), but less often. The market is very simple if you let it be.
I trade patterns that constantly repeat themselves in the market. They repeat consistently, I see them again and again and again. I do not know the outcome of each trade before I take it. I cannot tell the future, and I do not believe anyone who says that they can. Because I cannot tell the future, I cannot eliminate losing trades entirely, and they form part of my profitable trading.
I owe much of my initial trading belief to a group of traders that I met online. I have since met these people in person to confirm their situations. Their advice has always been free and I am deeply thankful for their mentoring, these traders helped me to believe that consistently profitable trading was possible. These traders trade different markets using different methods, but each is able to be consistenly profitable and trade for a living. I believe that having profitable traders to talk to day-in-day-out greatly helps the learning process.
Having said that, I do not currently trade for a living and I do maintain a fulltime job. This will change in years to come as I get a better idea of what to expect from the market week to week, month to month. Trading Forex is not a consistent income in the same way that a wage is - profits fluctuate, as the market is dynamic - and there are practicalities that need to be considered before I leave the workforce and commit to trading fulltime.
I am currently learning to trade the DAX by paper trading. I aim to take smaller profts on a daily basis from the DAX to supplement my Forex trading. This more consistent income will assist me in being able to leave the workforce.
A large amount of capital is NOT necessarily required to trade for a living..
Anything that I can help with? Ask away
submitted by grebfar to investing [link] [comments]

Best/Cheapest source of live ECN market data feed (FIX API)

Hey guys. Awesome sub you got here. I'm a software engineer and I'm interested in learning more about the forex markets. Before I put any real money down, I want to analyze the data and come up with some hypotheses and backtest them.
I'm looking for a live data feed of prices, volume, market depth, etc that I can use for the analysis.
Do you guys know of a cheap/free source of such data? It needs to be ECN data or as close as possible. And historical data would be nice but not necessary, I'm looking more for a live feed.
I've look at various ECN brokers but they only offer their FIX API to institutional investors with hundreds of millions of USD in trades per month.
The cheapest I've seen is Interactive Brokers, but their minimum account balance is USD10k.
Please let me know if you know of other brokers or have any other ideas about attaining this kind of data.
Thanks
submitted by drkenta to Forex [link] [comments]

Algorithmic Trading Strategy for Forex (EUR/USD)

Dear Reddit,
We are a team of three people that have developed an algorithmic trading strategy for Forex during the beginning of this year.
It is coded in .NET and the broker we use is Interactive Brokers (API). Strategy is simple and trades after technical indicators, but highly optimized.
The algorithms works very well and has already given us a return of 30% without margin during three weeks of live trading. We did get good results when we backtested the algorithms too (6 months), but we get even better results during live trading. We have developed our own backtesting software with our own recorded data. The strategy is only trading EUUSD right now because this currency pair has the highest amount of liquidity in the market, and our robot needs liquidity. We hold positions from 60 ms up to 1 hour.
We are trading Live with our own money right now. But we are very interested to get in touch with people in this area to continue to develop this strategy, attract capital or collaborate with other people in this area.
We often get the question: "Is it really possible to make money with algorithmic trading?" Answer: Yes you can, but it involves a lot of work, experience and sense of how markets work. This strategy for example should only be used when the markets conditions are "right" for this strategy and that is; High liquidity in the FX markets, low volatility and no major news events or volatile stock markets that can have spill over effects on the FX market. Otherwise big unexpectedly moves in this currency pair will occur more often and and this will result in unnecessary losses.
Which boards or communities are best for this kind of things?
Please let us know. If you have any questions about our strategy or anything else, feel free to ask :)
Thanks.
submitted by AlgoFX to algotrading [link] [comments]

How do I backtest, i.e. TradingView, ForexTester, or ??? and how do I get data?

As a newbie, I have been reading books and learning as much as possible before entering the market. I've got an Oanda demo account, but when I'm ready to test my strategy I don't want to test it in real-time, or at least as much as the demo allows, because that is too slow.
As a complete newbie, here is the way I imagine backtesting should work. I'm curious to see how this compares to reality:
  1. Load up charting software (which, I don't know).
  2. File→Load market data from the past, i.e. 2012-present.
  3. Go to the start of the chart, set the chart/bar time.
  4. Hit the left cursor button, or whatever button, each time I want the chart to proceed forward one bar.
  5. Take my time between each bar analyzing whether I should get in, out etc.
The above system would let me test my system without waiting the full 4 or n hours before bars like a demo account would require. Plus, I'm a programmer so I'd like to try and eventually write an indicator and test out other indicators.
In my title I put TradingView and ForexTester because those are the only two I've come across so far that might do this. Do I have to pay for back data, or do people just record it themselves and offer it for free online?
While I don't want people to do my work for me, it just seems like this question might be one that a lot of other people are wondering about and I haven't seen one like it so far on this subreddit.
Thanks!
submitted by lightley to Forex [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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[xpost /r/stats]New book for backtesting trading strategies - would appreciate help

If you use R's quantstrat packages I would appreciate any help you can offer with a new open-source project I am working on:
Backtesting Strategies in R.
The book is designed to provide information beyond the PDF's demo's and help files as I want to explain how things work, what the functions mean and what the limitations are.
In addition I wanted to get a little into analyzing the data and ensuring accuracy (Ch. 6) and obtaining faster resources such as AWS (Ch. 11).
Some things I need help with:
I would appreciate any help provided and will contributors to the credits.
submitted by timtrice to algotrading [link] [comments]

Download historical Forex data for FREE in 3 Simple Steps How To Download Free Historical Data With Metatrader 4 ... Metatrader 4 - 99% Back-testing in 5 Simple Steps - YouTube How I BACKTEST a Forex Trading Strategy in 2020 - YouTube How to BACKTEST a Forex Trading Strategy - YouTube Tutorial [Forex Trading] How to backtest a trading ... Soft4Fx: The Forex Best Backtesting Software Thus Far ...

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Download historical Forex data for FREE in 3 Simple Steps

FREE: Advanced Pattern Tutorial - https://www.thetradingchannel.net/optinpage CHECK OUT: EAP Training Program - https://goo.gl/7RrMM5 JOIN: "Advanced Pattern... Demonstrates how to back-test your Expert Advisers (EAs) with Metatrader and get 99% modelling quality in 5 simple steps. The back-test is executed with qualit... Demonstrates how to easily acquire free historical data for your trading platform - in 3 simple steps! Note that this video has closed captions that can be translated into your local language. Today we kick off #TheTradingEssentials Series, starting out with How I Backtest a Forex Trading Strategy in 2020... ----- Trading Platform I Use: https:... The Forex Best Backtesting Software Thus Far! Heikin Ashi Backtest Part 1 Soft4Fx Forex Simulator: https://d2t.link/soft4fx In this video, I share what I c... In this video you can see how to download Free Historical Data in Metatrader 4. https://mql4tradingautomation.com/metatrader-download-historical-data-backtes... This video will show you How to Backtest a Forex Trading Strategy, as well as 3 TIPS on BACKTESTING... Trading Platform I Use: https://www.tradingview.com/...

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