Timothy B. Barrett, Donald Pierce, James Perry and Arun Muralidhar look at the structure of dynamic beta management and its implications
(e) the tilts would be made just once a month – initially through cash reallocations that are part of the usual monthly process of managing pension funds and later through derivatives;
(f) the programme would have a turnover similar to that of the 3% range rebalancing programme;
(g) since it appeared that utilising this approach lowered the drawdown of the fund (relative to all other options), that it would make sense to widen the rebalancing ranges from 3% to 5% around each asset class; and
(h) the investment consultant requested an out-of-sample test to measure the results from 1962 to 1982 to check against data mining and to include a period in which markets were significantly different from the more recent experience in the last two decades.
At the time in 2005, this went against the grain of most rebalancing recommendations which focused on lowering tracking error and argued for tighter ranges. Implicit in achieving the SBCERA goal was that these rules not only made money, but did so when the target SAA portfolio was suffering (e.g., 2008. 2000-2002, 2011). In the language of statistics, these rules had a positive excess return, but the correlation of the excess return to the target portfolio was negative. Finding rules with a positive excess and a negative correlation to the reference portfolio was in effect getting paid to manage risk.
Table 1 provides return and risk statistics for a simple 60% allocation to the S&P500 Index and 40% to the Barclays Aggregate Index (Portfolio I), a hypothetical risk parity portfolio, the HFRI Weighted Composite Index; and the HFRI Macro Funds Index. It also provides the high level model excess return and risk statistics of dynamic beta. They are excess returns in that they are returns generated from deviating from a given static SAA. The period of analysis for these tables is January 2000 – September 2010.
Table 2 highlights the correlation of dynamic beta to these static approaches and demonstrates immediately the attractive aspects of this programme as all other strategies are a variation of a 60/40 portfolio and hence positively correlated, providing little benefit, but dynamic beta has a negative correlation with positive excess returns. In tests done elsewhere, we note that the dynamic beta has a positive correlation to liabilities.
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