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
We have seen that dynamic risk budgeting can ensure sound absolute return management. What is remarkable is the absence of reliance on prediction. Systematic allocation based on past values of the core and satellite portfolios means that the investor bears no forecasting risk. Of course, investment houses may have access to proprietary forecasts that they may wish to use to move the allocation between risk-free and risky assets. In fact, an asset manager may well wish to benefit from his forecasting skill.
It is not our objective here to consider how forecasts are best generated. But once they are generated, a crucial question is how to translate them into portfolio decisions. In any forecast-based core-satellite portfolio, of course, the weight of the satellite will increase when the satellite is expected to outperform the core. We consider two ways of translating these forecasts into action. We look first at forecasts used in a standard tactical asset allocation approach that simply increases the allocation to the satellite to a fixed weight when it is expected to outperform and resets it to the lower weight when it is expected to underperform. We then look at whether the manager could actually benefit from using such forecasts of the outperformance of the satellite in the DCS approach.
3.1. Naïve Tactical Allocation Strategy The performance of forecast-based investment depends, of course, on the accuracy of the forecasts. If the forecast is right most of the time, the portfolio should perform well. In this section, we assess the
performance of a manager with varying degrees of positive prediction skill.
The detailed setup of the analysis is as follows: we simulate an active manager’s approach with the following assumptions:
If the manager thinks the core will
outperform the satellite in the following month he will allocate 100% of the portfolio to the core.
If the manager thinks the satellite will
outperform the core in the following month he will allocate 50% of his portfolio to the satellite. The remaining 50% is allocated to the core.
The manager rebalances his holdings
We assume that the manager has positive
forecasting skill, that is, that he correctly forecasts satellite outperformance over a month at least seven times a year. In other words, we assume a hit ratio of at least 7/12. We look at hit ratios ranging from 7/12 to 11/12.
To assess the performance of this approach, we simulate 1,000 scenarios for the period from January 1999 to December 2008. The investments used in the core and satellite correspond to the previous example, i.e., we use a defensive euro government bond portfolio in the core and a large-cap equity satellite. Each scenario corresponds to a time series of returns for the active manager, given his bets. Thus the 1,000 scenarios represent the returns obtained by 1,000 hypothetical active managers who have a given hit ratio.
Exhibit 5 shows risk and return statistics for these scenarios. Since every scenario represents the returns of a hypothetical manager, the average for expected return
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