Financial advisors and academics both oppose market timing. Their advice: When the market drops wait out the storm. But one recent academic work, "Volatility-Managed Portfolios" by Alan Moreira and Tyler Muir, disagrees saying: Reduce your investments when volatility increases. Don't just sit tight.
Their justification uses simple arithmetic. Sharp Ratio (an accepted measure of return-to-risk) is return divided by volatility. The higher the better. Now volatility is reasonably predictable (except for large jumps like Feb 5th) whereas returns are totally unpredictable. Here’s the arithmetic: if the numerator (return) stays constant while the denominator (volatility) increases, Sharp ratio will decrease when volatility increases. By decreasing investment we're less committed during low Sharp Ratio periods.
The authors tested their thesis with seven investment strategies always finding better returns by decreasing investment size when the market becomes more volatile. One of these strategies was momentum. By happenstance, my GDP-based momentum system, called SPY_PM, had been following their recommendation in two ways.
Low volatility (VIX). Earlier posts discussed relaxing SPY_PM's triggers during low VIX periods to achieve more trades. I didn't follow Moreira and Tyler exactly by increasing assets during these periods but more frequent trading gave an almost equivalent result.
High VIX. Originally SPY_PM backtested with data to 2013. During this period VIX exceeded 30 only during the China plunge of late 2016. (Even the Euro scare in the summer of 2012, solved with words by that “brilliant Italian” Mario Draghi, only brought VIX to 25.) See the chart below. Since SPY_PM wasn't tested with high VIX, it doesn’t trade when VIX exceeds 30. Implicitly I'm following their recommendation by eliminating trades during high volatility periods.
Moreira and Tyler and the SPY_PM model reach the same conclusion from different directions, They're efficient market guys saying saying volatility can't predict returns. SPY_PM finds, however, that volatility does predict PM returns. (See Post 13 at etf12trade.com) One possible explanation is: GDP-weighted momentum posits that the US slowly follows world movement. But in high VIX periods, the US acts more independently; In low VIX periods the US follows the world.
Coincidentally, before reading the article, Post 15 compared SPY_PM having a VIX filter of 30 with a model having a VIX filter of 20. This filter of 30 was luck so after reading the article I retested SPY_PM back to 2011 including the Euro sovereign debt crisis (Spain and Italy). Result: It works best with a filter of 23.