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Working Paper
Dealer polling in the presence of possibly noisy reporting
The value of a vast array of financial assets are functions of rates or prices determined in OTC, interbank, or other off-exchange markets. In order to price such derivative assets, underlying rate and price indexes are routinely sampled and estimated. To guard against misreporting, whether unintentional or for market manipulation, many standard contracts utilize a technique known as trimmed-means. This paper points out that this polling problem falls within the statistical framework of robust estimation. Intuitive criteria for choosing among robust valuation procedures are discussed. In ...
Working Paper
Dynamic equilibrium economies: a framework for comparing models and data
The authors propose a constructive, multivariate framework for assessing agreement between (generally misspecified) dynamic equilibrium models and data, which enables a complete second-order comparison of the dynamic properties of models and data. They use bootstrap algorithms to evaluate the significance of deviations between models and data, and they use goodness-of-fit criteria to produce estimators that optimize economically relevant loss functions. The authors provide a detailed illustrative application to modeling the U.S. cattle cycle.
Working Paper
How accurate are Value-at-Risk models at commercial banks?
In recent years, the trading accounts at large commercial banks have grown substantially and become progressively more diverse and complex. We provide descriptive statistics on the trading revenues from such activities and on the associated Value-at-Risk forecasts internally estimated by banks. For a sample of large bank holding companies, we evaluate the performance of banks' trading risk models by examining the statistical accuracy of the VaR forecasts. Although a substantial literature has examined the statistical and economic meaning of Value-at-Risk models, this article is the first to ...
Working Paper
Evaluating the forecasts of risk models
The forecast evaluation literature has traditionally focused on methods for assessing point-forecasts. However, in the context of risk models, interest centers on more than just a single point of the forecast distribution. For example, value-at-risk (VaR) models, which are currently in extremely wide, use form interval forecasts. Many other important financial calculations also involve estimates not summarized by a point-forecast. Although some techniques are currently available for assessing interval and density forecasts, none are suitable for sample sizes typically available. This paper ...
Working Paper
Bankruptcy exemptions and the market for mortgage loans
The recent explosion in personal bankruptcy filings has motivated research into whether credit markets are being adversely affected by generous legal provisions. Empirically, this question is examined by comparing credit conditions and bankruptcy exemptions across states. We note that the literature has focused on aggregate household credit, making no distinction between secured and unsecured credit. We argue that such aggregation obscures important differences in forms of credit. Most significantly, property exemptions do not prevent the home mortgage lender from foreclosing on the home if ...
Working Paper
A coherent framework for stress-testing
In recent months and years both practitioners and regulators have embraced the ideal of supplementing VaR estimates with "stress-testing". Risk managers are beginning to place an emphasis and expend resources on developing more and better stress-tests. In the present paper, we hold the standard approach to stress-testing up to a critical light. The current practice is to stress-test outside the basic risk model. Such an approach yields two sets of forecasts -- one from the stress-tests and one from the basic model. The stress scenarios, conducted outside the model, are never explicitly ...
Working Paper
On identification of continuous time stochastic processes
In this note we delineate conditions under which continuous time stochastic processes can be identified from discrete data. The identification problem is approached in a novel way. The distribution of the observed stochastic process is expressed as the underlying true distribution, f, transformed by some operator, T. Using a generalization of the Taylor series expansion, the transformed function T f can often be expressed as a linear combination of the original function f. By combining the information across a large number of such transformations, the original measurable function of interest ...
Working Paper
Generalized spectral estimation
This paper provides a framework for estimating parameters in a wide class of dynamic rational expectations models. The framework recognizes that RE models are often meant to match the data only in limited ways. In particular, interest may focus on a subset of frequencies. This paper designs a frequency domain version of GMM. The estimator has several advantages over traditional GMM. Aside from allowing band-restricted estimation, it does not require making arbitrary instrument or weighting matrix choices. The framework also includes least squares, maximum likelihood, and band restricted ...
Report
Dynamic equilibrium economies: a framework for comparing models and data
We propose a constructive, multivariate framework for assessing agreement between (generally misspecified) dynamic equilibrium models and data, a framework which enables a complete second-order comparison of the dynamic properties of models and data. We use bootstrap algorithms to evaluate the significance of deviations between models and data, and we use goodness-of-fit criteria to produce estimators that optimize economically relevant loss functions. We provide a detailed illustrative application to modeling the U.S. cattle cycle.