Inter-temporal risk parity: A constant volatility framework for equities and other asset classes

Abstract

Inter-temporal risk parity is a strategy which rebalances between a risky asset and cash in order to target a constant level of risk over time. When applied to equities and compared to a buy-and-hold strategy it is known to improve the Sharpe ratio and reduce drawdowns. We used Monte Carlo simulations based on a number of time-series parametric models from the GARCH family in order to analyze the relative importance of a number of effects in explaining those benefits. We found that volatility clustering and fat tails in return distributions are the two effects with the largest explanatory power. The results are even stronger when there is a negative relationship between return and volatility. The application of a hidden Markow model to the historical time series of returns revealed volatility clustering and a negative correlation between returns and volatility, not only in equities but also to some extent in corporate bonds, government bonds and commodities. We used historical returns to simulate what the performance of an inter-temporal risk parity strategy would have been when applied to equities, corporate bonds, government bonds and commodities. The benefits of the strategy are more significant for equities and high-yield corporate bonds, which show the strongest volatility clustering, fat tails and negative relationship between returns and volatility. For government bonds and investment-grade bonds, which show less volatility clustering and a weaker negative relationship between returns and volatility, the benefits of the strategy were less marked.