Varying the VaR for unconditional and conditional environments

Accurate forecasting of risk is the key to successful risk management techniques. Using the largest stock index futures from 12 European bourses, this paper presents VaR measures based on their unconditional and conditional distributions for single and multi-period settings. These measures underpinned by extreme value theory are statistically robust explicitly allowing for fat-tailed densities. Conditional tail estimates accounting for volatility clustering are obtained by adjusting the unconditional extreme value procedure with GARCH filtered returns. The conditional modelling results in iid returns allowing for the use of a simple and efficient multi-period extreme value scaling law. The paper examines the properties of these distinct conditional and unconditional trading models. The paper finds that the biases inherent in unconditional single and multi-period estimates assuming normality extend to the conditional setting.     

Reevaluating hedging performance

Mixed results have been documented for the performance of hedging strategies with the use of futures. This article reinvestigates this issue with the use of an extensive set of performance‐evaluation metrics across seven international markets. The hedging performances of short and long hedgers are compared with the use of traditional variance‐based approaches together with modern risk‐management techniques, including value at risk, conditional value at risk, and approaches based on downside risk. The findings indicate that use of these metrics to evaluate hedging performance yields differences in terms of best hedging strategy as compared with the traditional variance measure. Also, significant differences in performance between short and long hedgers are found. These results are observed both in sample and out of sample. © 2006 Wiley Periodicals, Inc. Jrl Fut Mark 26:677–702, 2006     

Type correlated equilibria for games with payoff uncertainty

Summary Aumann's notion of correlated equilibrium is extended to games with payoff uncertainty. A type correlated equilibrium is a correlated equilibrium for Harsanyi's game in player-types. An equivalent definition is a probability distribution over types and actions which is consistent with the prior distribution over types, such that when each player observes its type and action, the observed action is optimal and no further information about other players' types is obtained. Any such equilibrium can be implemented by a type-independent correlation device when players' observations may be type-dependent. The type correlated equilibrium correspondence is shown to be upperhemicontinuous with respect to player information.Support from NSF grant IRI-8609208 is gratefully acknowledged. I am grateful to Maxwell Stinchcombe for comments on an earlier draft of this paper. Any remaining errors are my own.     

Spectral Risk Measures: Properties and Limitations

Spectral risk measures (SRMs) are risk measures that take account of user risk-aversion, but to date there has been little guidance on the choice of utility function underlying them. This paper addresses this issue by examining alternative approaches based on exponential and power utility functions. A number of problems are identified with both types of spectral risk measure. The general lesson is that users of spectral risk measures must be careful to select utility functions that fit the features of the particular problems they are dealing with, and should be especially careful when using power SRMs.

Estimating financial risk measures for futures positions: A nonparametric approach

This study presents nonparametric estimates of spectral risk measures (SRM) applied to long and short positions in five prominent equity futures contracts. It also compares these to estimates of two popular alternative measures, the Value-at-Risk and Expected Shortfall. The SRMs are conditioned on the coefficient of absolute risk aversion, and the latter two are conditioned on the confidence level. Our findings indicate that all risk measures increase dramatically and their estimators deteriorate in precision when their respective conditioning parameter increases. Results also suggest that estimates of SRMs and their precision levels are of comparable orders of magnitude as those of more conventional risk measures. © 2009 Wiley Periodicals, Inc. Jrl Fut Mark 30:689–703, 2010     

An analysis of factors influencing asset writedowns

This study investigates the magnitude of total asset writedowns for a random sample of Australian industrial companies. We adopt an income strategy approach in operationalising our magnitude of writedowns construct to consider the set of accounting policies and negative accruals potentially available to managers. Our focus is on the incentives for and constraints on management to make asset writedowns. We find that the magnitude of writedowns observed are associated with managers' incentives to writedown impaired assets that have declined in value, as well as the firm's capacity to absorb the financial statement effects of the writedown. The number of senior management changes found to be associated with greater writedowns in prior studies is also supported in this study when only writedowns taken to the income statement are considered. The quality of corporate governance mechanisms does not vary systematically with the magnitude of writedowns.     

Extreme spectral risk measures: An application to futures clearinghouse margin requirements

This paper applies the extreme-value (EV) generalised pareto distribution to the extreme tails of the return distributions for the S&P500, FT100, DAX, Hang Seng, and Nikkei225 futures contracts. It then uses tail estimators from these contracts to estimate spectral risk measures, which are coherent risk measures that reflect a user’s risk-aversion function. It compares these to VaR and expected shortfall (ES) risk measures, and compares the precision of their estimators. It also discusses the usefulness of these risk measures in the context of clearinghouses setting initial margin requirements, and compares these to the SPAN measures typically used.     

Multivariate Modeling of Daily REIT Volatility

This paper examines volatility in REITs using a multivariate GARCH based model. The Multivariate VAR–GARCH technique documents the return and volatility linkages between REIT sub-sectors and also examines the influence of other US equity series. The motivation is for investors to incorporate time-varyng volatility and correlations in their portfolio selection. The results illustrate the differences in results when higher frequency daily data is tested in comparison to the monthly data that has been commonly used in the existing literature. The linkages both within the REIT sector and between REITs and related sectors such as value stocks are weaker than commonly found in monthly studies. The broad market would appear to be more influential in the daily case.     

A Comparative Anatomy of Residential REITs and Private Real Estate Markets: Returns,Risks and Distributional Characteristics

Real Estate Investment Trusts (REITs) are the only truly liquid assets related to residential real estate investments. We study the behavior of U.S. Residential REITs over the past three decades and document their return characteristics. REITs have somewhat less market risk than equity; their betas against a broad market index average about 0.58. Decomposing their covariances into principal components reveals several strong factors. Residential REIT characteristics differ to some extent from those of the S&P/Case‐Shiller (SCS) private real estate markets. This is partly attributable to methods of index construction. Our examination of REITs suggests that investment in residential real estate is far more risky than what might be inferred from the widely followed SCS series. Although the SCS and REITs indicate little support for being able to predict each other, there is strong evidence of self‐predictability for the series.