An Extreme Value Approach to Estimating Volatility and Value at Risk

By Turan G. Bali. 2003

197 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/1b526c57702af6d24a14143ebd19230fdece9a5f

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Citations in the corpus

Does Systemic Risk in the Financial Sector Predict Future Economic Downturns (2012, methodology): “10Following Bali (2008) and Bali and Engle (2010), we estimate the system of equations in (18) using a weighted least square method that allows us to place constraints on coefficients across equations.”
Value at Risk and the Cross-Section of Hedge Fund Returns (2007, methodology): “This table presents the time-series averages of the slope coefficients obtained from the monthly Fama and MacBeth (1973) regressions for defunct funds. The standard t-statistics given in parentheses are the average slope divided by its time-series standard error. The Newey and West (1987) adjusted t”
On the power of generalized extreme value (GEV) and generalized Pareto distribution (GPD) estimators for empirical distributions of stock returns (2006, background): “In order to bypass these problems, some authors (Longin, 2000 ; McNiel and Frey, 2000 ; Bali, 2003 , among many others) have proposed to estimate the extreme quantiles of the distributions in a semi-parametric way, which allows (i) to avoid the model errors and (ii) to limit the sampling errors w”
Do Hedge Funds’ Exposures to Risk Factors Predict Their Future Returns? (2011, unknown): “Since default spread is high in recessions, hedge funds with higher exposure to default premium are expected to generate higher returns (see Bali, 2008; Bali and Engle, 2010). Jagannathan and Korajczyk (1986) indicate that funds investing in stocks with little or no risky debt show negative market t”
Empirical study of value‐at‐risk and expected shortfall models with heavy tails (2006, unknown): “illustrated fat tails in Chilean and US returns series; Bali (2003)”
Cyclicality in Catastrophic and Operational Risk Measurements (2007, unknown): “21 Bali and Neftci (2003) indicate that the mean of the GPD can be measured by the estimated μ-GPD location parameter.”
Using extreme value theory to measure value-at-risk for daily electricity spot prices (2006, methodology): “Bali (2003) adopts the EVT approach to derive VaR for U.S. Treasury yield changes. At present, applications of EVT to estimating VaR in energy markets are sparse. Andrews and Thomas (2002) combine historical simulation with a threshold-based EVT model to fit the tails of the empirical profit-and-los”
Extreme Value Theory for Finance: A Survey (2012, methodology): “The Box-Cox-GEV Distribution Bali (2003b) introduces a new generalization of extreme value distributions, obtained by applying to the GEV of Jenkinson (1955) the transformation proposed by Box and Cox (1964).”
Extreme Downside Risk and Expected Stock Returns (2012, unknown): “EVT is also utilized to improve the estimations of VaR or expected shortfall which are influenced by the shape of tail distribution function (Danielsson and de Vries, 1997; McNeil and Frey, 2000; Bali, 2003). However, there has been little research directly incorporating EVT into asset pricing studi”
Risk Measurement Performance of Alternative Distribution Functions (2008, methodology): “Longin (2000), McNeil and Frey (2000), and Bali (2003a) show that VaR measures based on the distribution of extreme returns, instead of the distribution of all returns, provide good predictions of catastrophic market risks during extraordinary periods. As indicated by a number of excellent papers th”
Is There an Intertemporal Relation between Downside Risk and Expected Returns? (2009, unknown): “Their firm-level Fama-MacBeth (1973) regressions and long-short portfolio analyses indicate that there is a positive and significant relation between down beta and the cross-section of expected returns, whereas up beta cannot explain the cross-sectional variation in average stock returns. We should ”