Semiparametric Estmation of Value-at-Risk

Event Details
  • Date/Time:
    • Tuesday January 29, 2002
      10:00 am - 10:59 pm
  • Location: Instructional Center, Room 209
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Barbara Christopher
Industrial and Systems Engineering
Contact Barbara Christopher

Summary Sentence: Semiparametric Estmation of Value-at-Risk

Full Summary: Semiparametric Estmation of Value-at-Risk

Value at Risk is a fundamental tool for managing market risks. It measures the worst loss to be expected of a portfolio over a given time horizon under normal market conditions at a given confidence level. Calculation
of VaR frequently involves estimating the volatility of return processes and quantiles of standardized returns. In this talk, several semiparametric techniques are introduced to estimate the volatilities of the market prices of a portfolio. In addition, both parametric and nonparametric techniques are proposed to estimate the quantiles of standardized return processes. The newly proposed techniques also have the
flexibility to adapt automatically to the changes in the dynamics of market prices over time. Their statistical efficiencies are studied both theoretically and empirically. The combination of newly proposed techniques for estimating volatility and standardized quantiles yields
several new techniques for evaluating multiple period VaR. The performance of the newly proposed VaR estimators is evaluated and compared with some of existing methods. Our simulation results and empirical studies endorse convincingly the advantage of the newly proposed time-dependent semiparametric approach for estimating VaR.

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School of Industrial and Systems Engineering (ISYE)

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  • Created By: Barbara Christopher
  • Workflow Status: Published
  • Created On: Oct 8, 2010 - 7:43am
  • Last Updated: Oct 7, 2016 - 9:53pm