Matthew Pritsker

Evaluating Value at Risk Methodologies: Accuracy versus Computational Time

Recent research has shown that different methods of computing Value at Risk (VAR) generate widely varying results, suggesting the choice of VAR method is very important. This article examines six VAR methods, and compares their computational time requirements and their accuracy when the sole source of inaccuracy is errors in approximating nonlinearity. Simulations using portfolios of foreign exchange options showed fairly wide variation in accuracy and unsurprisingly wide variation in computational time. When the computational time and accuracy of the methods were examined together, four methods were superior to the others. The article also presents a new method for using order statistics to create confidence intervals for the errors and errors as a per cent of true value at risk for each VAR method. This makes it possible to easily interpret the implications of VAR errors for the size of shortfalls or surpluses in a firms risk-based capital.

Nonparametric Density Estimation and Tests of Continuous Time Interest Rate Models

Nonparametric kernel density estimation has recently been used to estimate and test short-term interest rate models, but inference has been based on asymptotics. We derive finite sample properties of kernel density estimates of the ergodic distribution of the short-rate when it follows a continuous time AR(1) as in Vasicek. We find that the asymptotic distribution substantially understates finite sample bias, variance, and correlation. Also, estimator quality and bandwidth choice depend strongly on the persistence of the interest rate process and on the span of the data, but not on sampling frequency. We also examine the size and power of one of Ait-Sahalias nonparametric tests of continuous time interest rate models. The test rejects too often. This is probably because the quality of the nonparametric density estimate depends on persistence, but the asymptotic distribution of the test does not. After critical values are adjusted for size, the test has low power in distinguishing between the Vasicek and Cox-Ingersoll-Ross models relative to a conditional moment-based specification test.

The Impacts of Securitization on US Bank Holding Companies

We use data from 2001-2007 to assess the impact of mortgage and other forms of asset securitization on the insolvency risk, profitability, and leverage ratios of US bank holding companies. Using 3 different estimation techniques, we find that banks use mortgage securitization to reduce insolvency risk and increase leverage. We also find that securitization techniques increase bank profitability. Our results suggest that securitization techniques have played a positive role. This suggests that the current turmoil in mortgage credit and securitization markets is related to recent excesses in those markets, and that securitization activity will resume after those excesses are cleared up.

Large Investors: Implications for Equilibrium Asset, Returns, Shock Absorption, and Liquidity

The growing share of financial assets that are held and managed by large institutional investors whose desired trades move asset prices is at odds with the traditional competitive assumption that investors are small and take prices as given. This paper relaxes the traditional price-taking assumption and instead presents a dynamic multiple asset model of imperfect competition in asset markets among large investors who differ in their risk aversion. The model is used to study asset price dynamics during an LTCM-like scenario in which market rumors of distressed asset sales are followed at a later date by the sales themselves. Using the model, it is shown that large investors front-run distressed sales; asset prices overshoot their long-run fundamentals; and asset pricing models experience temporary breakdown. During the period of model breakdown assets equilibrium returns are explained by the market portfolio and by transient liquidity factors.

Enhanced Stress Testing and Financial Stability

To date, regulatory stress testing in the United States has focused on ensuring the banking system is resilient to losses in one or a few stress scenarios that involve macro-economic weakness, but it is unclear how far this resilience extends beyond the stresses considered. In addition, a theory of which stress-scenarios should be chosen to achieve systemic-risk reduction objectives has not yet been developed. To improve stress testing practices, this paper proposes a framework for modeling systemic risk. The framework is used to analyze areas where current stress-testing practices can be improved. In addition, the paper proposes a new approach for systemic risk stress-testing and recapitalization policy that ensure the banking system is robust to a wide set of shocks, but minimizes the costs of achieving robustness through better sharing of risk.

Informational easing: improving credit conditions through the release of information

Economist Matthew Pritsker of the Board of Governors of the Federal Reserve System offers a theoretical view on how regulators can reduce uncertainty in the financial markets by improving the availability of information.

A Fully-Rational Liquidity-Based Theory of IPO Underpricing and Underperformance

I present a fully-rational symmetric-information model of an IPO, and a dynamic imperfectly competitive model of trading in the IPO aftermarket. The model helps to explain IPO underpricing, underperformance, and why share allocations favor large institutional investors. In the model, underwriters need to sell a fixed number of shares at the IPO or in the aftermarket. To maximize revenue and avoid selling into the aftermarket where they can be exploited by large investors, underwriters distort share allocations towards investors with market power, and set the IPO offer price below the aftermarket trading price. Large investors who receive IPO share allocations sell them slowly afterwards to reduce their trades price-impact. This curtails the shares that are available to small price-taking investors, causing them to bid up prices and bid down returns. In some simulations, the distorted share allocations and slow unwinding behavior generate post-IPO return underperformance that persists for several years.