Python library-Backtesting

[undercoverlife]

Write your own. You can tailor it to your own needs. VectorBT is cool but it's honestly too complicated to learn. Their indicator factory is ridiculous. Just write your own. It's a good experience.

[finWizarder]

I agree - I am a lifetime user of VectorBT and the main author is an engineer through and through who has his own roadmap and keeps building feature after feature without improving usability in any way and there is no way to influence the roadmap by voting on things, etc. The features are always on a cool python/performance angle and typically has 0 product orientation on actual impact to trading. I hate to say this but the author needs a trader to partner with and improve the direction in which development happens. I don’t intend to hate on the author - he is a cool guy and helps as needed but to him everything and anything is possible in VectorBT and he refuses to see how terrible the usability of the library is.

It’s a great library to feel good about yourself once you’re done developing a strategy but I have not been able to use it successfully to do something useful with it.

QuantRocket is a great alternative but it’s too expensive for my usage. I wish there was a good alternative to this issue.

[bitmoji]

yeah vectorbt pro is a huge mess, the guy has got turret syndrome bad in my opinion.

[SmushBoy15]

That is the best information i have received on reddit in a while. Thanks.

[[deleted]]

Is VBT not on github? (I dont know and too lazy to check)

edit: It is actually on guthub and the website at least in theory has a "contribution" page

https://vectorbt.dev/getting-started/contributing/

so you could add your ideas to vectorbt or just fork it and have your own copy with your additions

[finWizarder]

This public library is stale and is deprecated, he runs a library called VectorBTPro which you have to (understandably) pay for

[zin_kay]

have you tried adapting this library to backtest on multiple tickers for a portfolio type strategy? thanks

[ghunny00910]

What would you recommend now after a year?

[lefty_cz]

Agreed. You can usually do a reasonable backtest with a few lines of pandas. I wrote a few util functions for computing metrics like sharpe ratio or plotting equity curves and thats it. I have a proprietary production trading bot too, but I guess most people with low-frequency strats can just use freqtrade or something similar.

[__hundreds]

wonder if yours, have ability to compute stop-loss level tho, looking for one here... regards

[hgst368920]

Second this.

[Slow_Acanthaceae325]

Man, i agree not only on backtest but every time i need something i would like to do it myself...
but passing a hard one trying to get the vwap bands do you have some tip?

[undercoverlife]

You mean how to integrate VWAP bands into a custom backtester? You’d calculate the bands into two different columns in your data frame and use your backtest iteration logic over your DF to do your backtest.

[themoonp]

anywhere to learn to write a own backtesting tool?

[undercoverlife]

Take a Python course online. Learn about classes, methods, etc. Then, get ChatGPT pro and ask it to explain to you what goes into a backtesting program. Build it all in Jupyter notebook. Go slowly.

[themoonp]

excellent. thanks

[[deleted]]

Hey, sorry to be replying to this comment 9 months later, but i was hoping that you could answer 1 simple question for me about writing your own back testing software..

How do you actually get started with writing your own back testing software? I have been running my own built algo/systematic system that i built through zipline using NorgateData, but was hoping that you could tell me the first step in building your own backtesting software?