Regulatory Evaluation of Value-at-Risk Models

Value-at-risk (VaR) models have been accepted by banking regulators as tools for setting capital requirements for market risk exposure. Three statistical methodologies for evaluating the accuracy of such models are examined; specifically, evaluation based on the binomial distribution, interval forecast evaluation as proposed by Christoffersen (1995), and distribution forecast evaluation as proposed by Crnkovic and Drachman (1995). These methodologies test whether the VaR forecasts in question exhibit properties characteristic of accurate VaR forecasts. However, the statistical tests used often have low power against alternative models. A new evaluation methodology, based on the probability forecasting framework discussed by Lopez (1995), is proposed. This methodology gauges the accuracy of VaR models using forecast evaluation techniques. It is argued that this methodology provides users, such as regulatory agencies, with greater flexibility to tailor the evaluations to their particular interests by defining the appropriate loss function. Simulation results indicate that this methodology is clearly capable of differentiating among accurate and alternative VaR models. This paper was presented at the Financial Institutions Center's October 1996 conference on "

Methods for evaluating value-at-risk estimates

This paper was presented at the conference "Financial services at the crossroads: capital regulation in the twenty-first century" as part of session 3, "Issues in value-at-risk modeling and evaluation." The conference, held at the Federal Reserve Bank of New York on February 26-27, 1998, was designed to encourage a consensus between the public and private sectors on an agenda for capital regulation in the new century.Bank capital ; Risk ; Bank investments

Is implied correlation worth calculating? Evidence from foreign exchange options and historical data

Implied volatilities, as derived from option prices, have been shown to be useful in forecasting the subsequently observed volatility of the underlying financial variables. In this paper, we address the question of whether implied correlations, derived from options on the exchange rates in a currency trio, are useful in forecasting the observed correlations. We compare the forecast performance of the implied correlations from two currency trios with markedly different characteristics against correlation forecasts based on historical, time-series data. For the correlations in the USD/DEM/JPY currency trio, we find that implied correlations are useful in forecasting observed correlations, but they do not fully incorporate all the information in the historical data. For the correlations in the USD/DEM/CHF currency trio, implied correlations are much less useful. In general, since the performance of implied correlations varies across currency trios, implied correlations may not be worth calculating in all instances.Options (Finance) ; Foreign exchange

Evaluating covariance matrix forecasts in a value-at-risk framework

Covariance matrix forecasts of financial asset returns are an important component of current practice in financial risk management. A wide variety of models, ranging from matrices of simple summary measures to covariance matrices implied from option prices, are available for generating such forecasts. In this paper, we evaluate the relative accuracy of different covariance matrix forecasts using standard statistical loss functions and a value-at-risk (VaR) framework. This framework consists of hypothesis tests examining various properties of VaR models based on these forecasts as well as an evaluation using a regulatory loss function. ; Using a foreign exchange portfolio, we find that implied covariance matrix forecasts appear to perform best under standard statistical loss functions. However, within the economic context of a VaR framework, the performance of VaR models depends more on their distributional assumptions than on their covariance matrix specification. Of the forecasts examined, simple specifications, such as exponentially-weighted moving averages of past observations perform best with regard to the magnitude of VaR exceptions and regulatory capital requirements. These results provide empirical support for the commonly-used VaR models based on simple covariance matrix forecasts and distributional assumptions.Financial markets ; Risk ; Econometric models ; Forecasting

Foreign entry into underwriting services: evidence from Japan's "Big Bang" deregulation

We examine the impact of foreign underwriting activity on bond markets using issue level data in the Japanese "Samurai" and euro-yen bond markets. Firms choosing Japanese underwriters tend to be Japanese, riskier, and smaller. We find that Japanese underwriting fees, while higher overall on average, are actually lower after conditioning for issuer characteristics. Moreover, firms tend to sort properly in their choice of underwriter, in the sense that a switch in underwriter nationality would be predicted to result in an increase in underwriting fees. Finally, we conduct a matching exercise to examine the 1995 liberalization of foreign access to the "Samurai" bond market, using yen-denominated issues in the euro-yen market as a control. Foreign entry led to a statistically and economically significant decrease in underwriting fees in the Samurai bond market, as spreads fell by an average of 23 basis points. Overall, our results suggest that the market for underwriting services is partially segmented by nationality, as issuers appear to have preferred habitats, but entry increases market competition.Japan

Supervisory information and the frequency of bank examinations

Bank supervisors need timely and reliable information about the financial condition and risk profile of banks. A key source of this information is the on-site, full-scope bank examination. This article evaluates the frequency with which supervisors examine banks by assessing the decay rate of the private supervisory information gathered during examinations. The analysis suggests that this information ceases to provide a useful picture of a bank's current condition after six to twelve quarters. The decay rate appears to be faster in years when the banking industry experiences financial difficulties, and it is significantly faster for troubled banks than for healthy ones. Thus, the analysis suggests that the annual examination frequency currently mandated by law is reasonable, particularly during times of financial stress for the banking industry.Bank supervision ; Banking law

EAD calibration for corporate credit lines

Managing the credit risk inherent to a corporate credit line is similar to that of a term loan, but with one key difference. For both instruments, the bank should know the borrower's probability of default (PD) and the facility's loss given default (LGD). However, since a credit line allows the borrowers to draw down the committed funds according to their own needs, the bank must also have a measure of the line's exposure at default (EAD). Our study, which is based on a census of all corporate lending within Spain over the last 20 years, provides the most comprehensive overview of corporate credit line use and EAD calculations to date. Our analysis shows that defaulting firms have significantly higher credit line usage rates and EAD values up to five years prior to their actual default. Furthermore, we find that there are important variations in EAD values due to credit line size, collateralization, and maturity. While our results are derived from data for a single country, they should provide useful benchmarks for further academic, business and policy research into this underdeveloped area of credit risk management.Commercial loans ; Bank loans ; Credit