Long Short Equity Trading Strategy

[piby 180]

Hi all!

First of all, I am very new here and trying to learn the platform.

Typically, I want to implement long short equity trading strategy where I would like to rank securities weekly and rebalance my portfolio.

For backtesting this, I have download the OHLCV data for all US securities in my Postgres database. To provide this data to cerebro, I am planning to create a pandas dataframe for each security (3000's) (iterable, using chunksize) and adding it to cerebro through loop.

I don't want the entire data to be loaded into memory, so I am planning to making use of dataframe's chunksize parameter.

I haven't tried it but will cerebro support this? Or what would be the best way to go about this problem?

Thanks!

[backtrader]

@piby-180 said in Long Short Equity Trading Strategy:

I don't want the entire data to be loaded into memory, so I am planning to making use of dataframe's chunksize parameter.

Using chunksize would only have the effect that you load things in chunks and not that you load less.

@piby-180 said in Long Short Equity Trading Strategy:

I haven't tried it but will cerebro support this? Or what would be the best way to go about this problem?

You have to use exactbars=True, to make sure the data feeds are not fully (pre)-loaded and all buffers are kept to the exact minimum needed for operation.

See: Docs - Cerebro