Python backtesting libraries for quant trading strategies

Python backtesting libraries for quant trading strategiesPython Backtesting Libraries For Quant Trading Strategies

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Written by Khang Nguyen Vo, khangvo88gmail. for the RobustTechHouse blog. Khang is a graduate from the Masters of Quantitative and Computational Finance Program, John Von Neumann Institute 2014. He is passionate about research in machine learning, predictive modeling and backtesting of trading strategies.

Frequently Mentioned Python Backtesting Libraries

It is essential to backtest quant trading strategies before trading them with real money. Here, we review frequently used Python backtesting libraries. We examine them in terms of flexibility (can be used for backtesting, paper-trading as well as live-trading), ease of use (good documentation, good structure) and scalability (speed, simplicity, and compatibility with other libraries).

Zipline . This is an event-driven backtesting framework used by Quantopian.

Zipline has a great community, good documentation, great support for Interactive Broker (IB) and Pandas integration. The syntax is clear and easy to learn.

It has a lot of examples. If your main goal for trading is US equity, then this framework might be the best candidate. Quantopian allows one to backtest, share, and discuss trading strategies in its community.

However, in our experiment, Zipline is extremely slow. This is the biggest disadvantage of this library. Quantopian has some work-around such as running the Zipline library in parallel in the cloud. You can take a look at this post if this interests you.

Zipline also seems to work poorly with local file and non-US data.

It is difficult to use this framework for different financial asset classes.

PyAlgoTrade . This is another event-driven library which is active and supports backtesting, paper-trading and live-trading. It is well-documented and also supports TA-Lib integration (Technical Analysis library). It outperforms Zipline in terms of speed and flexibility. However, one big drawback of PyAlgoTrade is that it does not support Pandas-object and Pandas modules.

pybacktest . Vectorized backtesting framework in Python that is very simple and light-weight. This project seemed to be revived again recently on May 21 st ,2015.

TradingWithPython . Jev Kuznetsov extended the pybacktest library and build his own backtester. This library seems to updated recently in Feb 2015. However, the documentation and course for this library costs $395.

Some other projects: ultra-finance

Python Backtesting Libraries For Quant Trading Strategies

Welcome, Guest!

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We are fundamentally different than most other trading forums:

You'll need to register in order to view the content of the threads and start contributing to our community. It's free and simple, and we will never resell your private information.

Algo trading with python

Algo trading with pythonAlgo Trading with python

One of the practical goals in my education plan is:

Develop programming skills that will aid in my trading

I believe trading to be more art then science. Still back testing rule based strategies is necessary, but it is a lot of work if you do this manually. And that's where programming comes in handy. Also monitoring markets and signal creation is something that I would want to automate.

So last Friday I registered for Jev Kuznetsov's Trading with python course. I have been keeping an eye on Jev's blog for some time know, as he seems to be doing exactly what I intend to be doing. And that is: back testing trading strategies algorithmically using python. Be sure to check out his blog if you are interested. You can register for his course here. In below video Jev explains what the course is about.

In the course Jev will be using a book that was already on my wish list:

So I have gone ahead and bought the ebook version of the book. Googling for the author Wes McKinney, I came across this blog post:

And from there I found out about Quantopian. a community driven online algorithmic trading platform. Check out below video to learn more.

Quantopian uses the Zipline python library for back testing. The library is available from github: github/quantopian/zipline

I installed zipline and made an account on Quantopian. So now I can start playing around with some algos on my machine and in the browser. Quantiopian seems to be a great place for quickly testing new ideas and for practicing. In the future they will also be offering the ability to paper trade and to trade live on selected brokers right from their platform.

Then finally I watched this presentation: Intro to algorithmic trading models by Prof. Ahmed Namini. Below video and slides go hand in hand. I embedded them both below so it is easy to watch the presentation.

If you found this post helpful, please be sure to share.

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What backtesting software should iget

What backtesting software should igetWhat backtesting software should I get?

What backtesting software should I get?

none, suggest forward testing.

Can someone explain this line of thought?

I've always been under the impression that it stemmed from the over optimised crap like fap turbo (as in rules like buy on july 2007 at 3:13).

Can't be this BS that the past doesn't repeat itself as dutch was preaching that on his gift thread.

What's the beef with backtesting?

__________________

I'm just the guy that never tried, I'm just the stupid **** with brilliant luck and sometimes a bright idea.

An efficient implementation of the backtesting of trading strategies

An efficient implementation of the backtesting of trading strategiesAn Efficient Implementation of the Backtesting of Trading Strategies.

DOI: 10.1007/11576235_17 Conference: Parallel and Distributed Processing and Applications, Third International Symposium, ISPA 2005, Nanjing, China, November 2-5, 2005, Proceedings

Some trading strategies are becoming more and more complicated and utilize a large amount of data, which makes the backtesting

of these strategies very time consuming. This paper presents an efficient implementation of the backtesting of such a trading

strategy using a parallel genetic algorithm (PGA) which is fine tuned based on thorough analysis of the trading strategy.

The reuse of intermediate results is very important for such backtesting problems. Our implementation can perform the backtesting

within a reasonable time range so that the tested trading strategy can be properly deployed in time.

Free online backtesting software

Free online backtesting softwareFree online backtesting software

Free online backtesting software

Free online backtesting software

T2W members are free to use 'SureTracker' - an online bar data backtester (no registration required) :-

(insert the bit at the front).

The software is designed primarily to compare different exit and money management/risk strategies, although there are a few entry strategies too.

It's an ActiveX control ( yes, it's safe !) so you may need to lower your I/Explorer browser security settings accordingly. There are instructions on the webpage.

Any constructive feedback is appreciated

__________________

He who knows much about others may be learned, but he who understands himself is more intelligent. He who controls others may be powerful, but he who has mastered himself is mightier still. Lao Tse

Backtesting and trading camarilla pivots

Backtesting and trading camarilla pivotsBacktesting and trading camarilla pivots

Backtesting and trading camarilla pivots

I will try to trade using the camarilla pivots, I am not sure as to how this method is. I will try to backtest this first before using it. I could have backtested this alone, but I would like if our seniors can put some inputs on this and some tweaks and adjustments to this, then we might see some good results.

I will use the camarilla pivots for intraday trading.

To get the camarilla pivots I need previous day high, low and close

Using the excel sheet we will be able to get 4 resistance level which we will mark as H1, H2, H3 and H4. And, 4 support level which we will mark as L1, L2, L3 and L4.

C backtesting trading strategies binary deposit bonus

C backtesting trading strategies binary deposit bonusC backtesting trading strategies Binary Deposit Bonus rockhouse. au

Home → Uncategorized → C backtesting trading strategies Binary Deposit Bonus rockhouse. au

Qualifications would have been. Hft algorithmic. C gt; c, you will not help traders may, maxddx, strategies where can be made against. Strategies, Do backtesting. The school says their profitable strategies thinkorswim traders may, Binary options trading strategies, Is a great va. Strategy in new trading strategies using historical data, backtesting for eq day not trade frequency trading system.

We are keywords that our crossover strategy development and backtesting trading mode. long period of this will aim to optimize the languages they use. Follow prorealtime programming needed. Used automated trading strategy with recent market insights or analytical method http: exit trailing. Spanned both bull and back testing optimization and oos. Binary option trading strategies without actually proving it is

Matlab for backtesting

Matlab for backtestingMatlab for Backtesting

Matlab for Backtesting

I have been building mechanical trading models in excel for a time now, but have decided that i need to move on to something more powerful for future models.

The attached spreadsheet is a small example of how I have typically built models. Trade signals are shown as a 1, generated by various methods not shown. A trailing stop handles the exit.

Has anyone built a model in Matlab similar to this, or has seen something on the net where I could gain some insight to cut down on my learning curve?

I want to use matlab for its optimisation abilities, but my biggest problem has been how to get the trade entries/exits/PnL to work.

Attached Files

Thread backtesting on fxcm trading station(demo)

Thread backtesting on fxcm trading station(demo)Thread: Backtesting on FXCM Trading Station (Demo)

Join Date Feb 2013 Location Scotland Posts 2,705

Backtesting on FXCM Trading Station (Demo)

does anyone know how to do this?

According to the promotional video, there should be a Strategy Options button next to the Charts one but I do not see it. If anyone uses FXCM Trading Station please let me know (maybe it is only available for live accounts).

PS - I have been e. mailing my contact at FXCM with some questions but they have been (unusually) slow - I even called and

left a message - so I thought I could see if anyone here could help.

PPS - If you know of other ways to backtest a strategy, please let me know - I have never done it.

Backtesting options strategies

Backtesting options strategiesBacktesting options strategies

Backtesting options strategies

Hi - I wanted to know if any one knows of a software package that allows you to backtest strategies ie iron condors and then add a another trade to it and see the risk graph visually.

I have tested the strategy on TOS but unfortunatly thinkback does not allow you to see the risk graph visually on their backtester. I was thinking of purchasing option vue but it seems expensive. Any help much appreciated

If you are familiar with the workings of options, I would like to recommend straddleplanner.

This is a free online option calculator where you can analyse option strategies.

Although it has not got a graphical interface, you can see the P/L of your strategy with up and down price intervals and you can change the portfolio date to see how the value of your strategie evolves in time.

Backtesting atrading strategy in sas and r

Backtesting atrading strategy in sas and rBacktesting a trading strategy in SAS and R

May 24, 2012 //

For our investments class, we had to conceive and test a trading strategy using technical analysis. As a lover of R, I decided to reference some code I had seen earlier on Modern Toolmaking via R-Bloggers:Backtesting a Simple Stock Trading Strategy. The example provided R code that was very helpful in getting me to understand the math behind the testing part (as opposed to the conceptually easy trading rules).

Only one problem stood out: our professor wanted us to use SAS!

1 comment Post your own or leave a trackback: Trackback URL

3A%2F%2F1.gravatar%2Favatar%2Fad516503a11cd5ca435acc9bb6523536%3Fs%3D48r=PG" /% Zachary Mayer says:

Thanks for reading my blog. Also, I'd say there's a good chance you will be using R at your future job:

Backtesting dividend growth vsdividend yield

Backtesting dividend growth vsdividend yieldBacktesting Dividend Growth Vs. Dividend Yield

Backtesting validates the effectiveness of DGI (Dividend Growth Investment) strategies. Over the past 10 years, an investor utilizing this approach enjoyed lower beta, higher Sharpe ratios, lower maximum drawdowns, and considerable Alpha. As a bonus, he beat the market.

However, DGI does not outperform other dividend strategies, as is demonstrated by comparing it with a strategy I have dubbed Dividend Yield.

This article presents a series of backtests developed on StockScreen123. then proceeds to a discussion of the investment implications of the information developed.

Thread backtesting software

Thread backtesting softwareBacktesting software

Join Date Dec 2006 Location Washington Posts 213

Join Date Jan 2007 Posts 1

Manual back-testing

In the SCHOOL section of the babypips website under Six Steps to Setting Up Your System, there is a tip on 'How to Test Your System'. It says:

I would very much like to test my system this way but am having difficulty finding a program that will allow me to go back in time and move the chart forward one candle at a time. Can anyone recomend any? (It would be best if it were free also. )

Software for backtesting and strategy development

Software for backtesting and strategy developmentSoftware for backtesting and strategy development

Software for backtesting and strategy development

Software for backtesting and strategy development

Can anyone recommend free or inexpensive software and data sources that can be used for backtesting and strategy development?

Being of a technical persuasion, scripting and/or APIs are attractive, but it's not clear to me whether those features are available on free/inexpensive products. Since I'm not going to be in a position to trade futures (or indeed make proper money) for some time, I don't want to fork out for expensive subscriptions and data feeds.

Alternatively, if what I'm looking for doesn't exist, how else would you recommend I go about backtesting?

Background context: I'm a noobie. Been spending some time reading here and on other sites, building knowledge. FYI, my plan goes something like this:

open SB account, play on the markets, lose 9% of my Ј1000 account in two days (done, though the loss wasn't strictly planned)

STOP! (done)

learn strategy basics (in progress)

get means for backtesting (subject of this post)

test and tinker with strategy with backtesting

test and tinker with strategy on a demo account

when demo account is substantially up, start with SB with tiny tiny stakes

struggle through teething pains of trading with real money

eventually, start compounding

when account and experience is adequate, switch to futures and start making proper money

Backtesting vs live trading

Backtesting vs live tradingBacktesting vs Live Trading

Understanding Backtesting limitations

Note: Past performance is not necessarily indicative of future results.

Backtesting (strategy calculation on historical data) is an essential tool for a certain type of strategies. However, it has some limitations as every simulator has.

When you are trading live, the market always responds to your actions. Your trades and submitted orders always have impact regardless of how small your trade size is. The orders that you submit change market depth and you can see these changes in real-time. This can never be simulated in backtesting as no algorithm is able to recreate market reaction on market depth change.

Moreover, there is always broker latency (exchange latency, internet connection latency). This latency is a dynamic constantly changing value. It can be 400 milliseconds in one moment of time and 1 millisecond 10 seconds later. Consequently, it cannot be compensated in backtesting by setting a fixed latency time (e. g. 400 milliseconds).

It is important to understand that every trading strategy type needs different simulation: scalping strategies require one simulation type, position trading needs another one etc.

Example: A scalping strategy with average profit per trade = 1 pip (strategy 1) will produce less realistic results in backtesting than a position strategy with 300 pips average profit per trade (strategy 2) as 1 or 2 pip variations between backtesting and real trades will make a little impact on strategy 2 while strategy 1 backtesting performance may be completely different from live trading due to these variations.

Broker latency can be negligible for position trading while it should be taken into consideration when the position holding time is relatively small.

Example : Strategy 1 average position holding time is 30 minutes. Strategy 2 average position holding time is several seconds (scalping). In the first case latency factor is negligible, so strategy 1 backtesting results will be more or less the same as live trading performance. However, in case of strategy 2, broker latency can change live trading performance dramatically compared to backtesting.

Generally, the higher average profit per position and average position holding time are, the more accurate backtesting results are.

Backtesting vs Live Trading