Skewed By Randomness: Testing Arbitrary Rebalancing Dates

How much influence do investors have over their portfolios? Perhaps it’s less than commonly assumed. The notion that randomness plays a role in money management has been widely studied in finance–Nassim Taleb’s popular treatment in Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets is one example. The concept is a staple in the money game, although it’s easily overlooked, even ignored in some cases. Consider a simple rebalancing strategy. Does it matter which dates you choose to return a portfolio mix back to the target weights? Maybe, but the details matter quite a lot in terms of the answer. For instance, crunching the numbers on an 11-fund portfolio with a Dec. 31, 2003 start date shows that randomly choosing rebalancing dates tends to perform as well if not better than a consistent year-end remix and a buy-and-hold strategy.

This is far from the final word on the subject, but the results from the test below show that for the years 2004-2015 (through Sep. 4) a random choice of 11 rebalancing dates (to match the number of year-end events for that period) delivered a surprisingly competitive/superior range of results for 1,000 portfolios. Surprising because quite a lot of attention and research has been directed over the years in looking for optimal rebalancing dates. But as we’ll see, it’s not clear that spending a lot of time searching for the best dates is a productive use of time and resources if your rebalancing system is a plain-vanilla design.

That doesn’t mean you shouldn’t rebalance. Rather, the analysis below suggests that moving heaven and earth in search of optimal rebalancing dates may be a waste of time for a basic portfolio set-up. The results also imply that in order to add value over a random choice of rebal dates, you’ll probably have to use a relatively sophisticated set of rules for asset allocation design and management.

Otherwise, let’s say that you’re planning on ten rebalancing events over the next decade as a risk-management system. Further, assume that the rebal events will simply move weights back to the target weights. It appears that randomly choosing ten dates over the coming decade for such a system is expected to do about as well, perhaps better, than a carefully designed system that’s focused on choosing the ten best dates in real time.