Articles scientifiques

A New Approach to Comparing VaR Estimation Methods


Journal of Derivatives

hiver 2008, vol. 16, n°2, pp.54-66

Départements : Finance, GREGHEC (CNRS)

Mots clés : Value-at-Risk, Bank Trading Revenue, Backtesting, Coverage Test

Value-at-risk (VaR), despite its known shortcomings, has become established as the most commonly used measure of risk exposure. But many variants of procedures for implementing VaR exist. Some variants use historical data with or without simulations, while others assume parametric models, such as GARCH, with parameters estimated from past data. And, of course, different users might focus on different VaR cutoffs: 5%, 1%, and so on. Perignon and Smith use an innovative method of extracting daily values for bank revenues from their annual reports to explore which VaR methods empirically work best. A second innovation discussed in the article is how to measure the accuracy of tail estimation at multiple points in the tail. The results suggest that, in estimating VaR for banks, parametric methods work best

Acquisition of Information in Financial Markets


Review of Economic Studies

octobre 2008, vol. 75, n°4

Départements : Finance

In their paper "Information Acquisition in Financial Markets" (this journal, ), Barlevy and Veronesi present a model of a one-period financial market, and claim that for an open set of parameter values, the value of information increases with the mass of informed agents. That claim is shown here to be false. The property of strategic substitution is robust in their model.

Applying Regret Theory to Investment Choices: Currency Hedging Decisions

S. Michenaud, B. SOLNIK

Journal of International Money and Finance

septembre 2008, vol. 27, n°5

Départements : Finance

Mots clés : Regret aversion, Loss aversion, Hedging, Portfolio choices

We apply regret theory, an axiomatic behavioral theory, to derive closed-form solutions to optimal currency hedging choices. Investors experience regret of not having chosen the ex post optimal hedging decision. Hence, investors anticipate their future experience of regret and incorporate it in their objective function. We derive a model of financial decision-making with two components of risk: traditional risk (volatility) and regret risk. We find results that are in sharp contrast with traditional expected utility, loss aversion, or disappointment aversion theories. We discuss the empirical implications of our model and its ability to explain observed hedging behavior.

Competition for Order Flow Smart Order Routing Systems

T. FOUCAULT, A.J. Menkveld

The Journal of Finance

février 2008, vol. 63, n°1, pp.119-158

Départements : Finance, GREGHEC (CNRS)

We study changes in liquidity following the introduction of a new electronic limit order market when, prior to its introduction, trading is centralized in a single limit order market. We also study how automation of routing decisions and trading fees affect the relative liquidity of rival markets. The theoretical analysis yields three main predictions: (i) consolidated depth is larger in the multiple limit order markets environment, (ii) consolidated bid-ask spread is smaller in the multiple limit order markets environment and (iii) the liquidity of the entrant market relative to that of the incumbent market increases with the level of automation for routing decisions (the proportion of "smart routers"). We test these predictions by studying the rivalry between the London Stock Exchange (entrant) and Euronext (incumbent) in the Dutch stock market. The main predictions of the model are supportedMarket fragmentation, centralized limit order book, smart routers, trading fees, trade-throughs

Do Banks Overstate their Value-at-Risk ?

C. PERIGNON, Z. Deng, Z. Wang

Journal of Banking and Finance

mai 2008, vol. 32, n°5, pp.783-794

Départements : Finance, GREGHEC (CNRS)

Mots clés : Value-at-Risk (VaR), Capital requirement, Backtesting

This paper is the first empirical study of banks’ risk management systems based on non-anonymous daily Value-at-Risk (VaR) and profit-and-loss data. Using actual data from the six largest Canadian commercial banks, we uncover evidence that banks exhibit a systematic excess of conservatism in their VaR estimates. The data used in this paper have been extracted from the banks’ annual reports using an innovative Matlab-based data extraction method. Out of the 7354 trading days analyzed in this study, there are only two exceptions, i.e. days when the actual loss exceeds the disclosed VaR, whereas the expected number of exceptions with a 99% VaR is 74. For each sample bank, we extract from historical VaRs a risk-overstatement coefficient, ranging between 19 and 79%. We attribute VaR overstatement to several factors, including extreme cautiousness and underestimation of diversification effects when aggregating VaRs across business lines and/or risk categories. We also discuss the economic and social cost of reporting inflated VaRs