There are plenty of backtesters available, but some can cost several hundreds or even thousands of dollars. Some of these backtesters are written in proprietary programming languages (easy languages) which can limit you from being able to test complex strategies. There are three main backtesters that we will use: Backtrader, Quantopian, and Excel.

• Backtrader

  • Backtrader is a backtesting engine that you can run from your own computer. To use this backtesting engine, I highly recommend you download Anaconda and Atom first. The website and docs for backtrader can be found at https://www.backtrader.com/

  • Download backtrader at https://github.com/backtrader/backtrader

  • Once you have downloaded backtrader you will need to install it. run this line of code: pip install backtrader

    • You can find out more information about pip can be found here https://www.youtube.com/watch?v=jnpC_Ib_lbc

  • Pros:

    • Very Fast

    • Event-driven (avoids a lookahead bias)

    • Can handle data from any financial market

    • Used by a few hedge funds for research

    • An active community forum for support

    • Well documented

    • Free

  • Cons:

    • Requires substantial knowledge of python to be used efficiently  and effectively

    • You must supply your own data to test on

• Quantopian

  • https://www.quantopian.com/

  • Quantopian is a crowd-sourced hedge fund. They provide you with all the tools and historical data necessary to backtest your own strategies. Quantopian explicitly states that you own any algorithm you create. They do not have the right to look at your code unless you give them explicit permission to do so. If you decide to submit an algorithm for evaluation by Quantopian and they like it then they will allocate anywhere from $500,000 to $50 million and you receive 10% of profits The backtesting and research are performed in python.

  • Pros:

    • Free Data - historical pricing data and fundamental data for all stocks currently listed and previously delisted (avoids survivorship bias)

    • Premium data available i.e. sentiment data, earnings surprise data, etc.

    • Much easier to learn than backtrader. A beginner could learn to work effectively and efficiently in Quantopian if they spent an hour to a few hours each day learning for about three to four weeks

    • Active, highly academic, and professional forum for support

    • Excellent support from Quantopian Staff

    • Easy to follow tutorials

    • Extensive Documentation

    • Free to use

    • An excellent section with lectures about math and finance

  • Cons:

    • Very slow backtesting

    • Only supports equities, ETFs, and futures (futures can be difficult to test on)

    • Data only goes back to 2002 (this may not be enough data for long-term strategies)

• Excel

  • Most people do not realize that its possible to backtest a strategy using Excel. In fact, David Harding, a billionaire investment manager, used an Excel spreadsheet to test trend-following strategies and run a hedge fund for several years.

  • Pros:

    • Easy to learn

    • Plenty of tutorials on the internet

  • Cons:

    • As a strategy’s logic becomes more complex, Excel becomes increasingly difficult to use

    • Must supply your own data

    • Must be purchased ($5-$10 with enrollment at A&M)

    • Possiblity of making mistakes while backtesting which could cause the strategy to appear much better than it actually is.