On More Robust Estimation of Skewness and Kurtosis: Simulation and Application to the S&P500 Index

By Tae-Hwan Kim, Halbert White. 2003

501 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/c8321234e7f0a2f178013c684d28fdfe1162811f

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Citations in the corpus

Conditional Correlation Models of Autoregressive Conditional Heteroscedasticity With Nonstationary GARCH Equations (2014, background): “Kim and White (2004) suggested to look at robust estimates of these quantities.”
Modelling volatility by variance decomposition (2013, methodology): “Robust skewness and kurtosis estimates (see Kim and White (2004) and Teräsvirta and Zhao (in press)) are also provided.”
Downside Variance Risk Premium (2015, unknown): “More importantly, our construction of the SRP only requires the existence of the second moment of stock returns, while the Kozhan, Neuberger, and Schneider (2014) approach requires the existence of the third moment.”
Modeling Autoregressive Conditional Skewness and Kurtosis with Multi-Quantile CAViaR (2008, background): “(9) and (10) then yield the following asymptotic representation of our estimator ̂T :”
Applying Robust Methods to Operational Risk Modeling (2006, background): “Robust measures of spread include inter-quartile range (IQR), median absolute deviation (MAD), mean absolute deviation, and Winsorized standard deviation; more estimators of scale were proposed by Rousseeuw and Croux (1993). Robust estimators of skewness were studied by Kendall and Stuart (1977), Bo”
Garch forecasting performance under different distribution assumptions (2006, methodology): “quartiles of the returns, is used as suggested by Kim and White (2004) the skewness is small but negative in both periods.”
Portfolio selection in multidimensional general and partial moment space (2010, background): “In particular, the distributional characteristics of a variety of financial and other economic variables (assets, options, hedge funds, etc.) indicate skewness and extreme kurtosis (see, e.g., Jondeau and Rockinger, 2003, or Kim and White, 2004).”
Earnings and Consumption Dynamics: A Nonlinear Panel Data Framework (2015, background): “In a recent model of earnings losses upon displacement, Huckfeldt (2016) included an unskilled sector that tends to absorb laid-off workers. With low probability, workers have the opportunity to escape this sector and move to the skilled sector that features a job ladder. The escape from the unskill”
Modelling changes in the unconditional variance of long stock return series (2012, methodology): “To check this conclusion, we also provide the robust measures of skewness and kurtosis as recommended by Kim and White (2004) in order to account for outliers.”
An Introduction to Univariate GARCH Models (2006, background): “However, Terasvirta and Zhao (2006) recently studied 160 daily return series and, following Kim and White (2004) , used robust kurtosis and autocorrelation”