A Risk Based Approach to Tactical Asset Allocation
Stefano Colucci and Dario Brandolini (Symphonia Sgr) | November 28, 2011
Faber’s ‘A Quantitative Approach to Tactical Asset Allocation’ (2009) proposes the use of a very simple trading rule to improve the risk-adjusted returns across various asset classes. The purpose of this paper is to present an alternative and simple quantitative risk based portfolio management that improves the risk-adjusted portfolio returns across various asset classes. This approach, based on the conclusions of Brandolini D. – Colucci S. ‘Backtesting Value-at-Risk: A comparison between Filtered Bootstrap and Historical Simulation’, has been tested since 1974 for calibration and since 2000 in a real backtest. The asset allocation framework is using a combination of indices, including the Standard&Poors 500, Topix, Dax, MSCI United Kingdom, MSCI France, Italy Comit Globale, MSCI Canada, MSCI Emerging Markets , RJ/CRB, Merril Lynch U.S. Treasuries, 7-10 Yrs , and all indices are expressed in US Dollar. Since 2000 the empirical results present equity-like returns with lower volatility and drawdown and only one negative year both in gross and net of costs returns.
How Expected Shortfall Can Simplify the Equally-Weighted Risk Contribution Portfolio
Stefano Colucci (Symphonia Sgr) | November 26, 2011
In recent years both equity and bond markets have been afflicted by high volatility. In order to build up a conservative portfolio several models may be used, such as minimum variance portfolio or equally weighted portfolio. In 2008/09 another way to deal with diversification came up, that is equally-weighted risk contribution portfolio. This kind of procedure leads not to equalize the portfolio weights but the risk weights. The only thing to understand is how we can measure risk. While many authors focus on volatility, in this paper we shall present an alternative and coherent risk measure, that is Expected Shortfall estimated by Filtered Bootstrap Approach. We shall show how to use the ES properties to derive an easy way to equalize risk contribution, and we shall also present some empirical examples using different models. A model presented in S. Colucci, D. Brandolini “A Risk Based Approach to Tactical Asset Allocation” to compare results will also be introduced. In the end, the empirical result will show that ERC portfolio, ES Stable portfolio and minimum variance portfolio have roughly speaking the same performance risk and distribution, but if turnover and its costs are taken into account, the result changes in favor of ES Stable.
Time-Varying Fund Manager Skill
Marcin T. Kacperczyk (NY University), et al. | November 15, 2011
Mutual fund managers can outperform the market by picking stocks or timing the market successfully. Previous work has estimated picking and timing skill, assuming that each manager is endowed with a fixed amount of each and found some evidence of picking skills and little evidence of timing skills among successful managers. This paper estimates skill separately in booms and recessions and finds that the extent to which managers focus on stock picking or market timing fluctuates with the state of the economy. Stock picking is more prevalent in booms, while market timing dominates in recessions. We use this finding to develop a new methodology for detecting managerial skill. The results suggest that some but not all managers have skill. We describe the characteristics of the skilled managers and show that skilled managers significantly outperform the market.
Managing Sovereign Credit Risk in Bond Portfolios
Benjamin Bruder (Lyxor Asset Management), et al. | October 2011
With the recent development of the European debt crisis, traditional index bond management has been severely called into question. We focus here on the risk issues raised by the classical market-capitalization weighting scheme. We propose an approach to properly measure sovereign credit risk in a fixed-income portfolio. For that, we assume that CDS spreads follow a SABR process and we derive a sovereign credit risk measure based on CDS spreads and duration of portfolio bonds. We then consider two alternative weighting methods which are fundamental indexation and risk-based indexation. Fundamental indexation is based on GDP indexation whereas risk-based indexation uses a risk-budgeting approach based on our sovereign credit risk measure. We then compare all these methods in terms of risk, diversification and performance. We show that the risk-budgeting approach is the most appropriate scheme to manage sovereign risk in bond portfolios and gives very appealing results with respect to active management of bond portfolios.
Time-Varying Sharpe Ratios and Market Timing
Yi Tang (Fordham University) and Robert Whitelaw (NY University) | August 31, 2011
This paper documents predictable time-variation in stock market Sharpe ratios. Predetermined financial variables are used to estimate both the conditional mean and volatility of equity returns, and these moments are combined to estimate the conditional Sharpe ratio, or the Sharpe ratio is estimated directly as a linear function of these same variables. In sample, estimated conditional Sharpe ratios show substantial time-variation that coincides with the phases of the business cycle. Generally, Sharpe ratios are low at the peak of the cycle and high at the trough. In an out-of-sample analysis, using 10-year rolling regressions, relatively naive market-timing strategies that exploit this predictability can identify periods with Sharpe ratios more than 45% larger than the full sample value. In spite of the well-known predictability of volatility and the more controversial forecast-ability of returns, it is the latter factor that accounts primarily for both the in-sample and out-of-sample results.
The Joint Dynamics of Equity Market Factors
Peter Christoffersen (University of Toronto) and Hugues Langlois (McGill University) | September 2011
The four equity market factors from Fama and French (1993) and Carhart (1997) are pervasive in academic empirical asset pricing studies and in applied portfolio allocation. However, the joint distributional dynamics of the factors are rarely studied. For investors basing strategies on the factors or using them to model the returns of a wider set of assets, proper risk management requires knowing the joint factor dynamics which we model. We find striking evidence of asymmetric tail dependence across the factors. While the linear factor correlations are small and even negative, the extreme correlations are large and positive, so that the linear correlations drastically overstate the benefits of diversification across the factors. We model the nonlinear factor dependence and explore its economic importance in a portfolio allocation experiment which shows that significant economic value is earned when acknowledging the nonlinear dependence.