Daniel Smith

Queensland University of Technology

Australia

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Daniel Smith created these companion sites

A New Approach to Comparing VaR Estimation Methods
Abstract
We develop a novel backtesting framework based on multidimensional Value-at-Risk (VaR) that focuses on the left tail of the distribution of the bank trading revenues. Our coverage test is a multivariate generalization of the unconditional test of Kupiec (Journal of Derivatives, 1995). Applying our method to actual daily bank trading revenues, we find that non-parametric VaR methods, such as GARCH-based methods or filtered Historical Simulation, work best for bank trading revenues.
Perignon, C., and D. Smith, C. Hurlin, "A New Approach to Comparing VaR Estimation Methods", Journal of Derivatives , 15, 54-66.
Authors: Perignon
Smith
Coders: Perignon
Smith
Hurlin
Last update
Mon Jul 16 10:41:00 CEST 2012
Ranking
54
Runs
11
Visits
270
Diversification and Value-at-Risk
Abstract
A pervasive and puzzling feature of banks’ Value-at-Risk (VaR) is its abnormally high level, which leads to excessive regulatory capital. A possible explanation for the tendency of commercial banks to overstate their VaR is that they incompletely account for the diversification effect among broad risk categories (e.g., equity, interest rate, commodity, credit spread, and foreign exchange). By underestimating the diversification effect, bank’s proprietary VaR models produce overly prudent market risk assessments. In this paper, we examine empirically the validity of this hypothesis using actual VaR data from major US commercial banks. In contrast to the VaR diversification hypothesis, we find that US banks show no sign of systematic underestimation of the diversification effect. In particular, diversification effects used by banks is very close to (and quite often larger than) our empirical diversification estimates. A direct implication of this finding is that individual VaRs for each broad risk category, just like aggregate VaRs, are biased risk assessments.
Perignon, C., and D. Smith, "Diversification and Value-at-Risk", Journal of Banking and Finance, 34.
Authors: Perignon
Smith
Coders: Perignon
Smith
Last update
Fri Nov 23 08:29:00 CET 2012
Ranking
9999
Runs
N.A.
Visits
45
The level and quality of Value-at-Risk disclosure by commercial banks
Abstract
In this paper we study both the level of Value-at-Risk (VaR) disclosure and the accuracy of the disclosed VaR figures for a sample of US and international commercial banks. To measure the level of VaR disclosures, we develop a VaR Disclosure Index that captures many different facets of market risk disclosure. Using panel data over the period 1996–2005, we find an overall upward trend in the quantity of information released to the public. We also find that Historical Simulation is by far the most popular VaR method. We assess the accuracy of VaR figures by studying the number of VaR exceedances and whether actual daily VaRs contain information about the volatility of subsequent trading revenues. Unlike the level of VaR disclosure, the quality of VaR disclosure shows no sign of improvement over time. We find that VaR computed using Historical Simulation contains very little information about future volatility.
Perignon, C., and D. Smith, "The level and quality of Value-at-Risk disclosure by commercial banks", Journal of Banking and Finance, 34.
Authors: Perignon
Smith
Coders: Perignon
Smith
Last update
Fri Nov 23 08:30:00 CET 2012
Ranking
9999
Runs
N.A.
Visits
25
A New Approach to Comparing VaR Estimation Methods
Abstract
We develop a novel backtesting framework based on multidimensional Value-at-Risk (VaR) that focuses on the left tail of the distribution of the bank trading revenues. Our coverage test is a multivariate generalization of the unconditional test of Kupiec (Journal of Derivatives, 1995). Applying our method to actual daily bank trading revenues, we find that non-parametric VaR methods, such as GARCH-based methods or filtered Historical Simulation, work best for bank trading revenues.
Perignon, C., and D. Smith, "A New Approach to Comparing VaR Estimation Methods", Journal of Derivatives, Winter.
Authors: Smith
Perignon
Coders: Perignon
Smith
Last update
Fri Nov 23 08:30:00 CET 2012
Ranking
9999
Runs
N.A.
Visits
43