BNP: Wie Risikomanagement zu höherer Rendite führt

Inter-temporal risk parity, sometimes referred to as constant volatility or inverse volatility weighting, is a strategy which rebalances betweena risky asset and cash in such as to keep the risk constant over time. If financial assets behaved as it is described in most financial textbooks,i.e. returns followed Gaussian distributions, the strategy would be of no interest. But empirical evidence tells us otherwise.

“An inter-temporal risk strategy, when applied to equities (and compared to a buy and hold strategy) is known to improve the Sharpe ratioand reduce drawdowns,” according to Romain Perchet, BNP Paribas Investment Partners Quantitative Analyst and a co-author of the study.“We used Monte Carlo simulations based on a number of time series parametric models from the GARCH1 family, in order to analyze therelative importance of a number of effects in explaining those benefits. We found that volatility clustering with constant returns and the ‘fattails’ are the two effects with the greatest explanatory power. The results are even stronger if there is a negative relationship between returnand volatility,” Mr. Perchet continued.

“Using historical data, we also simulated what would have been the performance of this strategy when applied to equities, corporate bonds,government bonds and commodities. We found that the benefits of this strategy are more important for emerging equities and high yieldbonds, which show the strongest volatility clustering and fat tails. The effects are also important for developed equities, but less so thanfor commodities. For investment grade corporate bonds and government bonds, volatility clustering has not been sufficiently strong in thelast 20 years to generate any significant or visible effects, according to the authors of this study,” noted Raul Leote de Carvalho, BNP ParibasInvestment Partners Head of Quantitative Research and Investment Solutions and a co- author of this study.

MONTE CARLO SIMULATIONS, GARCH MODELS KEY

“Our Monte Carlo simulations, based on scenarios generated from GARCH models, allow us to confi rm these effects and to analyze in detailthe dependence of the benefi ts of inter-temporal risk parity strategies on the parameters of the models,” said Mr. Perchet. “The volatilityclustering effect is, in essence, a market timing effect. If the volatility changes and returns remain constant, then the Sharpe ratio is higherin lower volatility regimes, and increasing the weight of the risky asset in such periods will result in better risk-adjusted performances,”added Mr. Perchet.

“When fat tails are present in the distribution of the returns of the risky asset (reducing the exposure to the risky asset in regimes of highervolatility) in addition to volatility clustering, the result is not only a larger improvement in the Sharpe ratio, but also smaller drawdownsthan when following a buy and hold strategy,” Mr. Carvalho observed. “The effects are more pronounced if, additionally, the distribution ofrisky asset returns shows a smaller mean return in regimes of higher volatility and larger mean returns in regimes of lower volatility. Inparticular, this tends to be the case for equities and for high yield bonds,” he added.

Die vollständige Strategie im pdf-Dokument