Implied Correlation from VaR

16 Pages Posted: 26 Jun 2007

See all articles by John Cotter

John Cotter

University College Dublin; UCLA Anderson School of Management

Francois M. Longin

ESSEC Business School - Finance Department

Date Written: April 2007

Abstract

Most of the methods used by financial institutions to implement value-at-risk models are based on the multivariate Gaussian distribution with a constant correlation matrix. In this paper we use VaR calculation in a reverse way to imply the correlation between asset price changes. The distribution of implied correlation under normality is also studied in order to take into account any bias and sampling error. Empirical results for US and UK equity markets show that implied correlation is not constant but tends to be higher for long positions than for short positions. This result is statistically significant and can be interpreted as departure from normality. Our test provides a new way - by focusing the tail dependence - to assess the model risk associated with quantitative methods based on normality in asset management and risk management areas.

Keywords: Implied Correlation, Model Risk, Normality, Value at Risk

JEL Classification: G12

Suggested Citation

Cotter, John and Longin, Francois M., Implied Correlation from VaR (April 2007). Available at SSRN: https://ssrn.com/abstract=996080 or http://dx.doi.org/10.2139/ssrn.996080

John Cotter (Contact Author)

University College Dublin ( email )

School of Business, Carysfort Avenue
Blackrock, Co. Dublin
Ireland
353 1 716 8900 (Phone)
353 1 283 5482 (Fax)

HOME PAGE: http://www.ucd.ie/bankingfinance/staff/professorjohncotter/

UCLA Anderson School of Management ( email )

110 Westwood Plaza
Los Angeles, CA 90095-1481
United States

Francois M. Longin

ESSEC Business School - Finance Department ( email )

Avenue Bernard Hirsch
BP 105 Cergy Cedex, 95021
France

HOME PAGE: www.longin.fr

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