A Horse Race Between Tactical Asset Allocation Models
Posted Jul 13 2012 by in Applied Academic Research
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- We conduct a horse race with various tactical asset allocation (TAA) models. We present the performance of 8 different models applied to the “IVY5” asset classes (Domestic equity, foreign equity, long bonds, commodities, and REITs):
- Risk parity (RP) and risk parity with/without a moving average rule
- Momentum (MOMO) with/without a moving average rule
- Risk parity and momentum (RP_MOMO) with/without a moving average rule
- Minimum variance (Min Var) with/without a moving average rule
- All the TAA models outperform the equal-weight IVY5 on the basis of Sharpe ratio and the Sortino ratio, except for the Min Var model. RP and RP with momentum are the top performers, with a Sharpe ratio of .67 and .75, respectively. This compares favorably to the equal-weight IVY5, which has a .54 Sharpe ratio.
- Sharpe ratios are not the only way to assess performance. On a maximum drawdown basis, Min Var is the king with a maxdd of 13.70. Both the RP an the RP_MOMO portfolios do very well relative to the IVY5 portfolio. For example, RP has a maxdd of 30.85% and RP_MOMO has a maxdd of 34.09%. Both of these estimates compare favorably to the IVY5 maxdd of 46.47.
- Applying long-term moving average rules (MA) to the TAA models significantly improves performance. Again, RP and RP_MOMO shine the brightest with Sharpe ratios of .86 and .89, respectively. Relative to the IVY5 benchmark with MA, the TAA rules with MA are not earth shattering. For example, the IVY5 with MA rules has a Sharpe ratio of .79, which is not too far behind the TAA models.
- After the dust settles, the top performing TAA model is the risk parity with momentum model. This model starts with the risk parity benchmark weights and then shifts weights across asset classes depending on relative momentum. The RP_MOMO model works the best with and without MA rules applied. Applying MA rules optimizes performance.
Categories: Applied Academic Research