During recent StockLab course, we discussed the importance of ensuring that a strategy operates within the appropriate market regime.

I’m now diving deeper into this topic and exploring how different market regimes influence our existing strategies.

One strategy with a particularly clear edge is our “Turn of the Month” example.

What Is the Turn-of-the-Month Effect?
It’s widely believed that, after receiving their salaries, many investors allocate funds into ETFs like SPY, which tends to lift the market during that period.

I tested this behavior over 50 years of data and found that it produced positive returns most of the time. Below is a backtest in AlgoCloud using data starting in 1993.

Backtest of the Turn of the Month strategy

Market Regimes and Recent Volatility
Recently, the strategy suffered a sizable loss when it held a position during the announcement of President Trump’s large tariffs on U.S. imports. I wondered whether a market‐regime filter could have mitigated that drawdown. To explore this, I added a volatility filter designed to keep the strategy out of the market during high‐volatility periods.

Volatility Filter Conditions

• Entry Condition:
  

• Exit Condition:
  

Results
Since adding the filter, the overall stability of the strategy has improved:

Backtest of the strategy with volatility filter

Backtest of the strategy with volatility filter

Original results without volatility filter:

Backtest of the original strategy without volatility filter

Backtest of the original strategy without volatility filter

Final Thoughts
This study is purely exploratory, and the filter does not guarantee that the strategy can’t incur large losses in the future. However, pairing a volatility filter with a known edge feels intuitively sound, and I plan to continue refining and testing this approach.