The paper Factor MAX and Predictable Factor Returns from Liyao Wang and Ming Zeng presents a twist on momentum investing that goes long the factor that had the largest single-day return in the previous month. It is distinct from factor momentum goes long the factor that had the largest return over a specific formation period.
We have been running factor and model momentum for a while now with mixed results so we decided to have a look at this new strategy in the Indian long-only context.
tl;dr: not so hot!
We selected the NIFTY500 factor indices: LOW VOLATILITY 50 TR, MOMENTUM 50 TR, QUALITY 50 TR and VALUE 50 TR to compare Factor MAX vs. Factor Momentum. Factor Momentum out-performed Factor MAX.
The problem with using a single day’s performance to select a factor is that more volatile factors get picked more often. Here’s a plot of the monthly active factor between the two strategies.
Quality and Low-volatility factors do not jump around every day. Hence, their low representation in Factor MAX. You could use volatility adjusted returns to paper over this. However, we felt that went against the main thrust of the paper that investors systematically under-react to factor-level news embedded in these extreme returns, creating exploitable return predictability.
We ran the same backtest over a subset of our momentum and value models. Factor Momentum bested Factor MAX here as well.
If you want to DIY Factor Momentum based on this backtest, you can do so with cheap index funds:
- Nippon India Nifty 500 Quality 50
- Nippon India Nifty 500 Low Volatility 50
- Nippon India Nifty 500 Momentum 50
- Axis Nifty500 Value 50
Code and charts on github.