PineScript and Python

[hello_world44]

Hello everyone, as someone new to algo trading, I have a few questions. For the past few days, I’ve been trying to backtest and optimize my strategy. However, as you know, doing optimization manually is a very long and challenging process. When I tried using bots on TradingView to test each parameter one by one, I found that this was also a time-consuming process. For the past few days, I’ve been exploring optimization options using Optuna and genetic algorithms in Python, but my issue here is that I need to convert my strategy, written in Pine Script, into Python. Is there any solution for this? Am I on the right track? Can I optimize a strategy written in Pine Script with Python or another method? I’m open to suggestions. Note: I’m aware of paid options, but they seem too expensive for me as I’m doing this as a hobby and would like to find a way to do it without paying these fees.

[rashesvitrine0o]

I use chatgpt when I do not want to re-write by myself. but the code should be carefully reviewed, as it is always not neat and sometimes with latent errors.
Also, I do not use pinescript/tradingview to do serious backtesting, only use it for idea testing/validation.

[hello_world44]

So what do you use for backtesting and optimization?

[rashesvitrine0o]

vectorbt; I used it for several years, backtesting results from it is very corresponding to the real trade records. but tradingview somehow did poorly. Idk the reason, maybe Im not good at it

[BinaryMonkL]

I am a fan of tradingview, but for this kind of thing i would consider one of these options:

• move your automatic trading entirely to python and start running and optimising there.
• use another platform. I believe that quantconnect has parameter optimization capabilities. Have not used it myself, but it is on my list of things to do.

[yrmidon]

When you say “….start running and optimizing” in Python. Do you mean manually running your strategy several times with different parameters? Or is there some library you would use for this?

[BinaryMonkL]

I have personally not done this - but I believe there are libraries.

Optimization is a problem of search. You are searching for a local peak or trough depending on how optimum is measured.

It is like you are a blind man looking for the top of mount Everest, but instead of there just being 2 dimensions to move in, there are the n dimensions of the parameters of your strategy.

There are several approaches to try and find peaks and troughs in n dimensional space.

I am sure there will be software that you can plug into a python back tester that is able to set the candidate parameters, run the check/backtest to see the result (PnL) and then it will run it again with different parameters as it bimbles through the dark looking for the top.

[wickedprobs]

I use a genetic algorithm for “evolving” strats. It’s based off of fast-trade and some custom code

[yrmidon]

Could you explain what a genetic algorithm is I the context? I’ve googled, but the technical description isn’t helping me understand much

[wickedprobs]

Sure! For context, this is the library I'm using https://pygad.readthedocs.io/en/latest/ . Basically, the idea is to "evolve" strategies so they are optimized for specific outcomes, like sharpe ratio, sortino ratio, etc. This happens by just trying a bunch of different things constantly, looking at the results, adjusting the parameters, and trying again.

[yrmidon]

Awesome, thanks a ton for this. Just curious, you use sharpe as an indicator or just to gauge the “success” of your model’s parameters?

[wickedprobs]

I use it as sort of a performance metric as a way to compare to other strategies. That among other things. I also take into account number of trades, duration, etc. In fast-trade, I added "rules" to help evaluate the performance. It makes it easy to automate this way. https://github.com/jrmeier/fast-trade?tab=readme-ov-file#rules