Which parametric model for conditional skewness?

This paper addresses an existing gap in the developing literature on conditional skewness. We develop a simple procedure to evaluate parametric conditional skewness models. This procedure is based on regressing the realized skewness measures on model-implied conditional skewness values. We find that an asymmetric generalized autoregressive conditional heteroscedasticity specification on shape parameters with a skewed generalized error distribution provides the best in-sample fit for the data, as well as reasonable predictions of the realized skewness measure. Our empirical findings imply significant asymmetry with respect to positive and negative news in both conditional asymmetry and kurtosis processes.     

Compensating Wage Differentials for Schooling Risk in Denmark*

In this paper we analyse the association between wage differentials and risk using detailed information on length and type of education as seen in Danish administrative registers. Our contribution to the literature is that we distinguish between transitory (time‐series) and permanent (cross‐sectional) income shocks, and estimate the compensation for both sorts of risk. We find that wage risk in a given education cell is associated with higher wages, while skewness is associated with lower wages. As a robustness check, we see that ad hoc risk measures based on earnings‐mobility indicators confirm these findings.     

Properties of Multinomial Lattices with Cumulants for Option Pricing and Hedging

In this paper, we analyze properties of multinomial lattices that model general stochastic dynamics of the underlying stock by taking into account any given cumulants (or moments). First, we provide a parameterization of multinomial lattices, and demonstrate that mean, variance, skewness, and kurtosis of the underlying may be matched using five branches. Then, we investigate the convergence of the multinomial lattice when the basic time period approaches zero, and prove that the limiting process of the multinomial lattice that matches annualized mean, variance, skewness and kurtosis is given by a compound Poisson process. Finally, we illustrate the effect of higher order moments in the underlying asset process on the price of derivative securities through numerical experiments using the multinomial lattice, and provide a comparison with jump-diffusion models.     

Time-varying moments, idiosyncratic risk, and an application to hot-issue IPO aftermarket returns

This paper proposes time-varying idiosyncratic risk as a component driving conditional abnormal returns and outlines a corresponding Engle et al. [Econometrica 55 (1987) 391] ARCH-M market model. An application is given to initial public offering (IPO) aftermarket stock returns, where a positive relation between idiosyncratic risk and returns is consistent with young issues’ equity as a contingent claim on firm assets. The empirical results for an illustrative sample of German Neuer Markt stocks traded during the first two years after initial listing indicate pronounced skewness as well as a positive relation between conditional idiosyncratic risk and expected returns. Conditioning aftermarket performance on risk yields much lower levels of abnormal return significance than a standard approach.     

Does conditional market skewness resolve the puzzling market risk-return relationship?

In this paper, we employ instrumental variables methods that allow time-varying risk and reward-to-risk to test various conditional asset pricing models. We find a negative partial relation between the market excess return and conditional market variance. In contrast with recent findings, we show that this negative relationship is not due to the omission of the hedge term associated with the ICAPM. However, conditional market skewness seems to partly account for this negative risk-return relationship.     

基于偏度调整条件模型的中国证券投资基金表现评价

目前关于证券投资基金表现评价模型是在正态分布假设基础上以股市指数超额收益事为市场基准的评价模型。然而由于中国证券投资基金规范发展历史较短．研究样本有限，因此存在偏度（非正态分布）问题。另外．证券投资基金不但可以投资股票还可以投资于债券，仅以股市指数超额收益率为市场基准是不符合实际的。基于此，本文通过修正以上缺陷构建了含偏度调整的条件模型并且利用合理的计量方法验证了该模型的有效性。通过实证分析发现，2001年初～2004年底中国封闭式基金具有一定证券选择能力．但是市场时机把握能力是负向的。     

异质型人力资本产权与企业所有权安排

异质型人力资本是知识经济时代创造企业利润的关键。重视异质型人力资本产权特点的研究有特殊意义。异质型人力资本的本质和产权特点决定了其在企业所有权安排中的特殊性。     

Robust Likelihood Methods Based on the Skew-t and Related Distributions

The robustness problem is tackled by adopting a parametric class of distributions flexible enough to match the behaviour of the observed data. In a variety of practical cases, one reasonable option is to consider distributions which include parameters to regulate their skewness and kurtosis. As a specific representative of this approach, the skew‐t distribution is explored in more detail and reasons are given to adopt this option as a sensible general‐purpose compromise between robustness and simplicity, both of treatment and of interpretation of the outcome. Some theoretical arguments, outcomes of a few simulation experiments and various wide‐ranging examples with real data are provided in support of the claim.     

Investment,idiosyncratic risk,and growth options

We provide evidence that growth options play an important role in determining the negative relation between corporate investment and idiosyncratic risk in the absence of agency problem. A simple real options model predicts that the negative relation between corporate investment and idiosyncratic risk is a U-shaped function of the level of idiosyncratic risk: investment responds the most when idiosyncratic risk is at the intermediate level. And the negative relation is stronger when firms possess more growth options. Our results are robust when we control for the effect of managerial risk aversion, supporting the view that firms’ optimal response to uncertainty is an important driving force behind the negative investment–idiosyncratic risk relation.     

Mixed Normal Conditional Heteroskedasticity

Both unconditional mixed normal distributions and GARCH modelswith fat-tailed conditional distributions have been employedin the literature for modeling financial data. We consider amixed normal distribution coupled with a GARCH-type structure(termed MN-GARCH) which allows for conditional variance in eachof the components as well as dynamic feedback between the components.Special cases and relationships with previously proposed specificationsare discussed and stationarity conditions are derived. For theempirically most relevant GARCH(1,1) case, the conditions forexistence of arbitrary integer moments are given and analyticexpressions of the unconditional skewness, kurtosis, and autocorrelationsof the squared process are derived. Finally, employing dailyreturn data on the NASDAQ index, we provide a detailed empiricalanalysis and compare both the in-sample fit and out-of-sampleforecasting performance of the MN-GARCH as well as recentlyproposed Markov-switching models. We show that the MN-GARCHapproach can generate a plausible disaggregation of the conditionalvariance process in which the components' volatility dynamicshave a clearly distinct behavior, which is, for example, compatiblewith the well-known leverage effect.