How do you adjust a portfolio through time? This is the key question facing most money managers. The allocation decision of static portfolio may have gotten easier with ETF's which can allow easy access to a benchmark, but there is still an important issue of how asset allocation should adjust through time especially if there are costs associated with any adjustment.
Garleanu and Pedersen have looked at this issue in "Dynamic Trading with Predictable Returns and Transaction Costs". They conclude that the optimal trading or dynamic adjustment policy for a portfolio is to: 1. aim in front of the target and 2. trade partially toward the current aim. Simply put, the allocation the optimal trading strategy will take a weighted average of the current portfolio and the portfolio based on the future expected return. Moving to the target or aim portfolio will be affected by the mean reversion of the expected return. If there is slow mean reversion, there will be reason to focus way ahead on what should be the return allocation. Thus, if there is a slower mean reversion of the the expected return there will be more weight on the aim portfolio and less on the current portfolio. Hence, there is a trade-off between the current portfolio, the Markowitz portfolio based on the expected return, and the aim portfolio which is the mechanism to get the the best expected return portfolio. The Markowitz portfolio is a moving target but a portfolio manager has to worry about where the target will be in the future not what is predicted today.
A factor based model may predict that growth should lead to a higher expected return or that there is a macro surprise effect, but the issue for a portfolio manager is that there are costs with moving to any new target portfolio. If the fact generating expected return does not have persistence, moving to the new optimal Markowitz allocation may not be appropriate. The market may already be moving in a new direction if there is a mean-reversion or factor decay.
Garleanu and Pedersen have looked at this issue in "Dynamic Trading with Predictable Returns and Transaction Costs". They conclude that the optimal trading or dynamic adjustment policy for a portfolio is to: 1. aim in front of the target and 2. trade partially toward the current aim. Simply put, the allocation the optimal trading strategy will take a weighted average of the current portfolio and the portfolio based on the future expected return. Moving to the target or aim portfolio will be affected by the mean reversion of the expected return. If there is slow mean reversion, there will be reason to focus way ahead on what should be the return allocation. Thus, if there is a slower mean reversion of the the expected return there will be more weight on the aim portfolio and less on the current portfolio. Hence, there is a trade-off between the current portfolio, the Markowitz portfolio based on the expected return, and the aim portfolio which is the mechanism to get the the best expected return portfolio. The Markowitz portfolio is a moving target but a portfolio manager has to worry about where the target will be in the future not what is predicted today.
A factor based model may predict that growth should lead to a higher expected return or that there is a macro surprise effect, but the issue for a portfolio manager is that there are costs with moving to any new target portfolio. If the fact generating expected return does not have persistence, moving to the new optimal Markowitz allocation may not be appropriate. The market may already be moving in a new direction if there is a mean-reversion or factor decay.
This strategy makes perfect sense. The more any new strategy has an expectation of not decaying, there should be more emphasis on this new allocation. If there is a fast decay or mean reversion of the expected return there will be more weight place on the current portfolio. Do not make a quick adjustment. You will be disappointed, as you reach the new allocation the returns will no longer exist.
The authors discuss alphas and alpha decays as different return strengths and mean reversion speeds. If there is a lot of alpha or return strength, aim for the new allocation. If there is a lot of alpha decay focus on the current portfolio. The Markowitz portfolio is always a moving target because expected return are constantly changing; however, with transaction cost, an investor cannot just move to any target immediately. There will always have to be a trade-off between where the portfolio currently is and where it should be based on the cost of adjustment and the type of factor expectation.
The authors discuss alphas and alpha decays as different return strengths and mean reversion speeds. If there is a lot of alpha or return strength, aim for the new allocation. If there is a lot of alpha decay focus on the current portfolio. The Markowitz portfolio is always a moving target because expected return are constantly changing; however, with transaction cost, an investor cannot just move to any target immediately. There will always have to be a trade-off between where the portfolio currently is and where it should be based on the cost of adjustment and the type of factor expectation.
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