Risk Control through Dynamic Core-Satellite Portfolios of ETFs: Applications to Absolute Return Funds and Tactical Asset Allocation — January 2010
3. Beyond Tactical Bets: Integrating Predictions in a Risk-Controlled Framework
clearly unrealistic hit ratios of 11/12 maximum drawdowns are considerably higher than in the absolute-return portfolio based on the DCS approach we described above. So risk control can reduce risk more than forecasting ability can.
One naturally wonders if it is possible to combine the return potential of forecasting and downside risk management that would mitigate the high figures for maximum drawdown. As it happens, it may be possible by making the active manager’s forecasting ability an integral part of the DCS. We will thus condition the DCS strategy on the return forecasts for the satellite, all while respecting the dynamic risk budget used in the absolute return application above.
3.2. Risk-Controlled Tactical Allocation Strategy Since the main objective is to reduce the drawdown statistics that result from the errors made by skilled forecasters, we impose a maximum drawdown of 10%. Next, we incorporate the manager’s forecasting ability by introducing a time-varying multiplier m. If the manager expects the satellite to outperform the core, the multiplier is set to m=5, thus allowing a considerable fraction to be invested in the
equity satellite. If the manager expects the satellite to underperform the core, the multiplier is set to m=0. So the portfolio is fully protected from the expected negative performance of the satellite.
As before, we simulate 1,000 scenarios to assess the average performance of this risk-controlled strategy. The results in exhibit 6 show the benefits of using DCS management to limit the extreme drawdown induced by forecast error.
Again, active management provides high returns that evidently increase as forecasting ability (the hit ratio) improves. However, the approach that makes forecasts part of a DCS approach manages downside risk much better; for a hit ratio of 7/12 the average maximum drawdown is only
7.89%. In the simple tactical allocation
strategy, by comparison, the average maximum drawdown is -13.24%. This dynamic risk budgeting makes it possible to limit the severe drawdown in the standard tactical allocation. This reduction is more pronounced for relatively low hit ratios. But even with the higher hit ratios it leads to considerable risk reduction. Exhibit 7 shows the reduction in maximum drawdown for each hit ratio. Risk control, then, clearly leads to significant benefits.
Hit ratio Average return
7/12 5.96% -7.89%
8/12 7.93% -7.45%
9/12 10.19% -6.81%
10/12 12.57% -5.89%
11/12 15.28% -4.32%
Average maximum drawdown
Worst maximum drawdown
Worst performance over a rolling one-year period
Exhibit 6: Forecast-based strategy made part of DCS management: the table shows the performance and maximum drawdown of the strategy that integrates forecasts into a DCS framework. Forecasts are based on a simulation of 1,000 scenarios with various hit ratios.
An EDHEC-Risk Institute Publication