Value at Risk Calculations, Extreme Events, and Tail Estimation

By Salih N. Neftçi. 2000

259 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/e98113b8f6d596129a8fdb1beeb733555de624b7

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

In Finance

Citations in the corpus

On the Validity of Value-at-Risk: Comparative Analyses with Expected Shortfall (2002, methodology): “For numerical calculations of expected shortfall using EVT, see Neftci [2000] and Scaillet [2000]. 32 Historical simulations may not be able to ensure stable estimation because of insufficient historical data of tail loss.”
Extreme Value Theory for Finance: A Survey (2012, methodology): “76Bali (2003a) analyzes daily observations for the annualized yields on 3-month, 6-month, 1-year and 10-year U.S. Treasury securities; Neftci (2000), as seen above, includes in his data-set three-month, two-year, five-year and seven-year interest rates from the U.S.; while Werner and Upper (2004)…”
Empirical study of value‐at‐risk and expected shortfall models with heavy tails (2006, unknown): “In recent years, significant work has been made by researchers towards the applicability of EVT to real market data: Neftci (2000)”
An Application of Extreme Value Theory for Measuring Risk (2003, background): “…in Koedijk et al. (1990), Dacorogna et al. (1995), Loretan and Phillips (1994), Longin (1996), Danielsson and de Vries (1997b), Kuan and Webber (1998), Straetmans (1998), McNeil (1999), Jondeau and Rockinger (1999), Rootzèn and Klüppelberg (1999), Neftci (2000) and McNeil and Frey (2000).”
An Application of Extreme Value Theory for Measuring Financial Risk (2006, background): “…(1990), Dacorogna et al. (1995), Loretan and Phillips (1994), Longin (1996), Danielsson and de Vries (2000), Kuan and Webber (1998), Straetmans (1998), McNeil (1999), Jondeau and Rockinger (1999), Rootz`en and Kl¨uppelberg (1999), Neftci (2000), McNeil and Frey (2000) and Gen¸cay et al. (2003b).”
Effectiveness of copula-extreme value theory in estimating value-at-risk: empirical evidence from Asian emerging markets (2012, background): “Previous studies, such as Neftci (2000), McNeil and Frey (2000), and Longin and Solnik (2001), suggest different levels of threshold or propose methods to determine the optimal level.”
A Comparison of Extreme Value Theory Approaches for Determining Value at Risk (2005, unknown): “…(“delta-normal”) Value at Risk methodology requires that the underlying returns generating distribution for the security in question is normally distributed, with moments which can be estimated using historical data and are time-invariant (see Danielsson and DeVries (2000) or Neftci (2000)).”
Evaluating Predictive Performance of Value-at-Risk Models in Emerging Markets: A Reality Check (2006, methodology): “We follow Neftçi (2000) and use the empirical 10% quantile.”
Conditional Quantile Estimation for Generalized Autoregressive Conditional Heteroscedasticity Models (2009, methodology): “Other approaches to estimating VaR include the hybrid method of Boudoukh, Richardson, and Whitelaw (1998) and methods based on extreme value theory (see, e.g., Boos 1984; McNeil 1998; Neftci 2000).”