Asymmetric Risk Measures and Real Estate Returns

Rational investors distinguish between extremely high and extremely low returns. The measures of investment risk should reflect such asymmetric risk perception. This study presents six asymmetric risk metrics and empirically tests their abilities in explaining the cross-sectional variations of real estate returns. It finds strong evidence that systematic downside risk is associated with a risk premium, and skewness provides significant explanatory power to the variation of cross-sectional property returns. On the other hand, co-skewness does not explain real estate returns well and is not a good systematic risk measure.     

The information content of implied volatility, skewness and kurtosis: empirical evidence from long-term CAC 40 options

Implied standard deviation is widely believed to be the best available forecast of the volatility of returns over the remaining contract life (Jorion, 1995 ). In this paper, we take this result two steps further to the higher moments of the distribution (skewness and kurtosis) based on a Gram–Charlier series expansion of the normal distribution (Corrado and Su, 1996 ) using long-term CAC 40 option prices contract, named PXL. First, we found that implied first moments contain a substantial amount of information for future moments of CAC 40 returns although this amount decreases with respect to the moment's order. Secondly, we found that the different shapes of the volatility smile are consistent with different distribution of the underlying returns. Based on these results, we also observed that including other implied moments significantly improves the out-of-sample pricing performance of the Black–Scholes, (1973) model.     

Uncertainty,investment, and managerial incentives

This study provides evidence that managerial incentives, shaped by compensation contracts, help to explain the empirical relationship between uncertainty and investment. We develop a model in which the manager, compensated with an equity-based contract, makes investment decisions for a firm that faces time-varying volatility. The contract creates incentives that affect both the sign and magnitude of a manager׳s optimal response to volatility shocks. The model is calibrated using compensation data to quantify this predicted investment response for a large panel of firms. Our estimates help explain the variation in firm-level investment responses to volatility shocks observed in the data.     

On Families of Distributions with Shape Parameters

Univariate continuous distributions are one of the fundamental components on which statistical modelling, ancient and modern, frequentist and Bayesian, multi‐dimensional and complex, is based. In this article, I review and compare some of the main general techniques for providing families of typically unimodal distributions on with one or two, or possibly even three, shape parameters, controlling skewness and/or tailweight, in addition to their all‐important location and scale parameters. One important and useful family is comprised of the ‘skew‐symmetric’ distributions brought to prominence by Azzalini. As these are covered in considerable detail elsewhere in the literature, I focus more on their complements and competitors. Principal among these are distributions formed by transforming random variables, by what I call ‘transformation of scale’—including two‐piece distributions—and by probability integral transformation of non‐uniform random variables. I also treat briefly the issues of multi‐variate extension, of distributions on subsets of and of distributions on the circle. The review and comparison is not comprehensive, necessarily being selective and therefore somewhat personal. © 2014 The Authors. International Statistical Review © 2014 International Statistical Institute     

SKEWNESS AND KURTOSIS PROPERTIES OF INCOME DISTRIBUTION MODELS

This paper explores the ability of some popular income distributions to model observed skewness and kurtosis. We present the generalized beta type 1 (GB1) and type 2 (GB2) distributions' skewness–kurtosis spaces and clarify and expand on previously known results on other distributions' skewness–kurtosis spaces. Data from the Luxembourg Income Study are used to estimate sample moments and explore the ability of the generalized gamma, Dagum, Singh–Maddala, beta of the first kind, beta of the second kind, GB1, and GB2 distributions to accommodate the skewness and kurtosis values. The GB2 has the flexibility to accurately describe the observed skewness and kurtosis.     

SKEWNESS FOR THE WEIBULL FAMILY

Abstract. The skewness of the Weibull family of distributions is discussed for all values of the shape parameter. This class includes unimodal probability densities for which the coefficient of skewness μ₃/o³ is positive, but the order of the mean, median and mode is μ < m < M. For values of the shape parameter used in practice the distributions are skewed to the right by a well accepted definition of skewness.     

Skewness of Returns, Capital Adequacy, and Mortgage Lending

We calibrate a simulation model of credit value-at-risk for mortgage lending to UK experience. Simulations to capture the skewness of returns that might arise in the context of a financial crisis suggest that the IRB calculations of the new Basel Accord can substantially understate prudential capital adequacy. The same model shows that raising capital requirements has only a small impact on bank funding costs. We conclude that Pillar 2 supervisory review should increase capital requirements above IRB levels for secured bank assets—those whose returns can potentially fall furthest, relative to other, normally “riskier” assets, in extreme outcomes. JEL classification: G21, G28, R31. Presented at the December 2003 conference at the University of Tor Vegata, Rome. We are grateful for comments from William Lang, Mario Onarato, Larry Wall, and from an anonymous referee. All errors and omissions are our own responsibility. “The lady doth protest too much, methinks. The Queen's response to the players in Hamlet, Act 3, scene 2.     

A simple measure of skewness

Groeneveld (1986) in discussing the skewness for the Weibull family has pointed out the shortcomings of the classical measures of asymmetry—the standardized third moment and the Pearson measure of skewness. He has shown that a modified form of the Pearson measure b₃= (μ-m)/E|X-m| portrays the skewness of Weibull family quite well. We give another competitive measure of skewness T that is easy to interpret and is based on conditional expectations. The proposed measure satisfies the desirable properties of a skewness measure.     

Portfolio selection with skewness: A multiple-objective approach

In the presence of skewness, the portfolio selection entails considering competing and conflicting objectives, such as maximizing both its expected returns and skewness, and minimizing its risk for decreasing absolute risk-aversion investors. Since it is unlikely that a portfolio can solve the multiple-objectives problem simultaneously, a portfolio selection must depend on the investor's preference among objectives. This article shows that investor preference can be incorporated into a polynomial goal programming problem from which a portfolio selection with skewness is determined. An inefficient mean-variance portfolio may be optimal in the mean-variance-skewness content. The features of applying polynomial goal programming in portfolio selection are 1) the existence of an optimal solution, 2) the flexibility of the incorporation of investor preference, and 3) the relative simplicity of computational requirements.     

Trend in aggregate idiosyncratic volatility

We suggest that price interaction among stocks is an important determinant of idiosyncratic volatility. We demonstrate that as more (less) stocks are listed in the markets, price interaction among stocks increases (decreases), and hence stocks, on average, become more (less) volatile. Our results show that price interaction has a significant positive effect of idiosyncratic volatility. The results of various robustness checks indicate that the effect of price interaction is still significant to the presence of liquidity, newly listed firms, cash flow variables, business cycle variables, and market volatility. Once the price interaction effect is taken into account, no trend remains in idiosyncratic volatility. We conclude that there is no trend, but a reflection of the positive effect of price interaction on idiosyncratic volatility.