Volatility Based TAA

If you are not following Wes Gray and his writing you are missing out.  He churns out more research on quant strategies, stock picking, and investment theory than just about anyone I know.  He runs a few websites (in addition to being a professor) where you can find more information, and I highly recommend following the blogs (listed at end of email) of both as well as his Twitter feed.

In the two pieces below, Wes takes a look at applying risk parity weightings as well as a volatility filter to a simple tactical asset allocation model with impressive results.

Highly recommended reading!  (Also here is a list of more TAA reads from the Butler Philbrick crew.)

From the volatility based paper:


  • Diversification is an effective risk-management tool, but it does not do enough for the investor that is intensely afraid of large drawdowns. We propose volatility-based allocation as an additional tool.

  • Volatility-Based Allocation (VBA) is a two-signal model that is simple-to-implement, robust, and historically generates a favorable risk/reward return profile. The first indicator in VBA is the volatility regime signal, which simply identifies “Risk-On” and “Risk-Off” market regimes. The second indicator in VBA is the long-term moving average signal, which invests when the current price is above the 12-month MA, and invests in the risk-free rate otherwise.

  • Over the March 1, 1986 to August 31, 2012 period, VBA generates a CAGR of 9.76% and a maximum drawdown of 9.64% when applied to our 5 core assets classes: domestic equity, developed equity, emerging equity, real estate, and long-term government bonds.

  • VBA dominates the stand-alone long-term moving average as a risk management platform.

  • VBA also has a low correlation with other “standard” asset allocation frameworks (e.g., risk-parity, min-variance, momentum/trend-following, etc.)

Download the two PPTs here:

Their new book:


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