create functionality that scans a very large number of potential pairs, backtests a subset of them and returns pairs that have good backtesting scores.
there are a whole host of different potential problems with this and this is likely to be a really good way of showing that there is a huge difference between backtesting and actual trading, but regardless I think it could be useful.
finding a way to reduce the number of backtests might be key to making this possible. one way would be to create a correlation matrix of all candidate assets and only run backtesting on ones that meet a certain correlation level.
would need to evaluate whether or not all of this could be done in-memory or not, as well.
create functionality that scans a very large number of potential pairs, backtests a subset of them and returns pairs that have good backtesting scores.
there are a whole host of different potential problems with this and this is likely to be a really good way of showing that there is a huge difference between backtesting and actual trading, but regardless I think it could be useful.
finding a way to reduce the number of backtests might be key to making this possible. one way would be to create a correlation matrix of all candidate assets and only run backtesting on ones that meet a certain correlation level.
would need to evaluate whether or not all of this could be done in-memory or not, as well.