GitHub - lukstei/trading-backtest: A stock backtesting ...

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submitted by ViralMedia007 to FREECoursesEveryday [link] [comments]

How To Choose An Automated Trading Platform?

How To Choose An Automated Trading Platform?
When going for an automated trading platform it is very important to look for some important features before you decide on the automated trading platform you want to trade on. Different automated trading platforms offer different services which have their own pros and cons and might suit certain strategies and better than the others.
We have discussed important features that you should consider while choosing an algorithmic trading platform.

Select The Right Automated Trading Platform


https://preview.redd.it/gbx58zrdabu41.png?width=900&format=png&auto=webp&s=5ee3a23bc4f55a88437a8002fedfdf73390ece9b

Backtesting

A backtest is a historical simulation of an algorithmic trading strategy to see how it would’ve performed on the data in the past. Backtest results usually show the strategy’s performance in terms of profits and losses and some popular performance statistics like Sharpe Ratio or Information ratio which help to quantify the strategy’s return on risk. Hence a good backtesting software can be a great plus for an automated trading platform. Backtests can be divided into two categories ‘Research Backtesters’ and ‘Event-Driven Backtesting’.

Programming Languages

Choice of programming language is very important while deciding which platform to use for automating your trading strategy. Different languages have different pros and cons. Most commonly used programming languages used for algorithmic trading are C++, C#, Java, R, Python, and MATLAB. You can refer to one of our recent posts on top backtesting platforms where we’ve discussed popular programming languages.

Data

Different automated trading platforms provide access to/support trading/backtesting of certain securities only; some provide specific access to data feeds like Bloomberg and Thomson/Reuters. For instance, there are platforms dedicated to Forex trading or Equities trading only that too in specific markets. You need to make sure what the automated trading platform offers and then decide based on your needs. The frequency of data that you would need should also be taken into account. Some strategies would require daily EOD data while some other strategies might require intraday trading data.

Web-Based Platform

Some automated trading platforms also provide the web-based platform for online trading and backtesting which makes it easy and convenient to access your trading platform anywhere. The web-based platform may have less number of features compared to the desktop trading platform.

https://preview.redd.it/bwmmw9efabu41.png?width=900&format=png&auto=webp&s=c16e4008e52cf4cdd175241e8698b1fca09b43f4

Complexity

Different automated stock trading platforms vary in ease of use. Some platforms may require actual programming expertise while others may not. Most platforms provide a demo version which can help you decide what fits your comfort level. The complexity of platforms can be different for different assets traded, and one should check the different tools & features available to analyze the specific asset class.

Number of Strategies Allowed

Sometimes there might be restrictions on the number of long or short strategies loaded on a particular account and you might need extra accounts for more strategies. You should also check if you have enough memory on your computer for multiple accounts if required as it can be memory intensive. Some platforms also offer their own trading strategies as add-ons which can be subscribed by paying a periodic or one-time fee.

Commissions/Costs

Trading commissions can impact your profits to a great extent. Carefully choose the plan which suits your trading requirements. Also, check if there are initial and/or monthly fees and what is offered against it to make sure you are only paying for services which you actually want.

Technical Support & Customer Service

Automated Trading platforms are expected to have an extremely high “up-time” and rarely go out of service. Before choosing the platform you should check the history of outages and if there have been any other issues in the past, how soon were those resolved, and how knowledgeable and helpful was the support team.
submitted by FmzQuant to CryptoCurrencyTrading [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]

Some basic algo trading questions on platform and data sources

Hi algoTrading,
I'm new to algorithmic trading, and was hoping to get some advice on how to get set up. My questions fall into two categories, first, what platforms do you guys use for backtesting, and second, where do you get your data from.
First, to clarify what I mean by 'platform'. I am looking for a mechanism which will enable me to (relatively) easily go from idea to backtest. For instance, in quantopian, you can write a strategy, and backtest it. The backtest will generate relevant metrics, and you do not have to worry about the code linking the strategy to the data. Additionally, if the platform allowed for more robust testing, like walk forward testing, and monte carlo analysis, that would be ideal.
I have seen two websites in particular, which seem to be popular. Quantconnect, and Quantopian. Now, I have looked into both of these, and I am not sure they are what I am after. First, I am a little skeptical of putting out algo's which I have poured my time hard work into, on sites which execute the code remotely. Second, I am more interested in derivatives trading than stock trading. If I were to use an online platform, I would prefer one which included data on Options/Futures/Forex. Additionally, while the language isn't a huge deal, I have experience in Java, and am learning Python for data Science applications. If there were a platform which let me use Python or Java, that would be ideal.
Second is the data source. This is a little redundant for online platforms, like quantopian, which are already integrated with the data. However, I have also been looking at Amibroker, which is executed locally on your computer, and does not come bundled with data. I have seen that you can get some data from IB, thinking about switching over to them, just for their data feeds. But really, the data I am interested in would be 1) EOD options data. 2) intra day futures/forex data. 3) intraday stocks/indexes/ETF data.
I am willing to pay for tools/data if necessary, but would prefer to keep costs as minimal as possible, as I am a losing trader with a day job.
Thanks in advance!
submitted by IAmBoredAsHell to algotrading [link] [comments]

How can I call a kernel function for multiple Thrust object member functions in CUDA?

Please note that I am an absolute beginner with CUDA, and everything below is untested pseudocode. I'm coming from JavaScript, and my C++ is also super rusty, so I apologize for my ignorance :)
I am attempting to use CUDA for backtesting many different forex strategies.
Using Thrust, and I have 1000 objects instantiated from a class (pseudocode):
#include  #include  #include  #define N 1000 typedef struct dataPoint { ... } dataPoint; class Strategy { public: __device__ __host__ Strategy(...) { ... } __device__ __host__ void backtest(dataPoint data) { ... } }; int main() { dataPoint data[100000]; thrust::device_ptr strategies[1000]; int i; // Instantiate 5000 strategies. for (i=0; i<1000; i++) { thrust::device_ptr strategies[i] = thrust::device_new(...); } // Iterate over all 100000 data points. for (i=0; i<100000; i++) { // Somehow run .backtest(data[j]) on each strategy here. // i.e. Run backtest() in parallel for all 1000 // strategy objects here. } } 
Now let's say I'd like to run the .backtest() method on each object for each item in data. Procedurally I would do the following:
// Iterate over all 100000 data points. for (j=0; j<100000; j++) { // Iterate over all 1000 strategies. for (i=0; i<1000; i++) { strategies[i].backtest(data[j]); } } 
How might I accomplish this using CUDA such that .backtest() runs in parallel for all strategies each iteration j through the data?
If I have to completely rearchitect everything, so be it -- I'm open to whatever is necessary. If this isn't possible with classes, then so be it.
submitted by chaddjohnson to CUDA [link] [comments]

What other useful Programing languages should I learn along side my college education?

A little backstory im nineteen starting out college at a local community one , Taking my first programming class this fall mainly teaching C++ and a bit of Java I believe. While im finishing up my Bachelors from the University of Houston around 2019, I also plan to receive my CCNA routing switching and teach my self independently instead of taking courses when I could be working towards my bachelors. My mentor recommended me to learn Python as well for the network engineering industry.
I understand SQL / Database could be useful as well as I have a cousin who works for oracle in that field.
I know I'm jumping into it a little too fast but I would love to hear any recommendations involving my career path and options I could take.
I understand receiving an internship in the graduate portion of my education could be beneficial in securing experience and a potential job.
I also plan to use what I learn to facilitate making my own projects and programs that function as automated traders on various instruments such as Forex and Cryptocurrency markets, with a backed portfolio of course and backtested data.
I would love to hear various options as well as advice any person would be willing to share to a young computer geek.
Tldr; want 100k job how do
submitted by mopmango to cscareerquestions [link] [comments]

Forex Trading - Backtesting Larger Timeframe - Big Pis! Forex trading back test. How to start new backtesting session. Back-Testing Jam Session: Strategy and Forex Tester Installation - Forex Trading Strategy How To BACKTEST A Forex Trading Strategy - Trading System ... Backtesting trading strategies in JavaScript: a primer Fantastic open source Java stock exchange simulator for backtesting strategy for HFT or quant.mp4 Backtesting a quantitative trading strategy in JavaScript

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Forex Trading - Backtesting Larger Timeframe - Big Pis!

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