On my journey to build a portfolio of systematic strategies, I will start by backtesting the following ideas.
I will use Codex and Python.
Breakout:
- Donchian Channel with trailing stops (on Daily and H4)
- Intraday breakouts based on ATR (volatility) and key high/low levels (yesterday, ATH, 52‑week high/low, and pivots)
Exit criteria are crucial here: I will test both time‑based exits and trailing exits using MA/VWAP.
Momentum:
- Daily timeframe: trend continuation after a pause
- TDI - and MA‑based momentum strategies (expected to fail)
- VWAP momentum (expected to fail)
Mean Reversion:
- Standard deviation bands around VWAP
I plan to backtest these strategies in a raw form (without pre‑filtering) as well as with regime filtering, distinguishing between low‑ and high‑volatility periods.
Instruments
Stocks and crypto in the beginning.
I would really appreciate further insights and tips on what to pay particular attention to.
I have no experience trading mean‑reversion strategies, as I have always traded breakouts and momentum/trend strategies.
@PKycek Does this mean for smaller, personal accounts the achieveable results would theoretically be better if extend to eg top 100?
Or will spreads etc eat the edge there, regardless of size
You miss a critical point here - which to be fair is hard to answer without further statistical details.
But there is - percentage of time in the market, % of capital used, and not to mention the better risk adjusted returns - which in combination with other strategies could lead to a much higher return on a portfolio level
What is extremely noticeable in the last couple years. Gap between Institutions and Retail got smaller.
And somehow retail traders are even at advantage.
While Instis have to deal with more and more regulatory overhead, the costs of implementing technology + data etc. got so small that almost everyone can run a decent setup at home.
It will not stop, just get different I guess.
Core principles will always work.
@yuriymatso@SystematicPeter Trying to become the textbook example of selection bias?
I have another strategy you could backtest:
100% long Bitcoin in 2010 - hold until October 2025.
...what you should do:
Get Quality data.
Backtest it on HISTORICAL index constituents (eg. S&P500)
I did some backtests on Crypto and from my experience with them the CME futures make trading them easier (at least for my backtests).
My explanation is that the 24/7 market creates a lot of time where there is just „noice“ so signals vanish and edge erases.
What is your thought on this?
@Valckrie I use Codex via CLI and on a VPS via Openclaw every day.
Mainly for researching/backtesting systematic strategies.
And it improved my productivity/speed a lot