PEROLD-SHARPE REBALANCING STRATEGIES IN PRACTICE

Abstract

The purpose of this paper is to investigate the different strategies for portfolio rebalanc-ing (buy-and-hold, constant weights, and constant-proportion portfolio insurance (CPPI) suggested by Perold and Sharpe in a reallife environment using the actual market data and considering trans-action costs. Methodology. Exchange-traded funds were used to represent asset classes, and actual market prices in 2007-2015 for the ETFs used to conduct the research. The Monte-Carlo simulations were used to generate 400 portfolios over 3 different time horizons in order to get a representative sample. Two actual fee structures were used from the leading U.S. brokerage firms. Results of the portfolio dynamics research show outperformance of CPPI over other strategies on holding periods over 36 months, and on shorter time horizons CPPI and constant weights strategies clearly dominate over buyand- hold strategy. Contrary to the previous conclusions by Perold and Sharpe, there was no definite link between the stock market dynamics or volatility and the preferred strategy. We also see that after a bull market period the CPPI portfolio allocation shifts to 100% equity. The portfolio turnover is typically higher and much more dispersed for CPPI strategy than for constant weights strategy. We also found a strong negative correlation between the CPPI portfolio turnover and the initial equity allocation, whereas for constant weights strategy the turnover is higher at 50% allocation to both stocks and bonds. Practical implications. The strategy choice is shown to be more a matter of the holding period; CPPI seems the best choice over longer periods. Contrary to the widespread perception, our research shows that brokerage fees has not had a material influence on the simulated portfolio performance and, thus, should not be a factor for choosing a strategy. Originality/value. Unlike previous studies in this area that focused on analytical derivation based on sample statistics, we used the Monte-Carlo simulation on the actual asset prices and brokerage fees structures. The results of our research are much closer to the actual portfolio dynamics seen in practice. We also address issues like portfolio turnover and transaction costs that are often over-looked by academic researchers.