William Perraudin

Predicting Emerging Market Currency Crashes

This paper assesses the extent to which crashes in emerging market currencies are predictable using simple logit models based on lagged macroeconomic and financial data. To evaluate our model, we calculate trading strategies in which an investor goes long or short in the currency depending on whether crash probabilities are low or high. When we estimate the model on part of the data and then use the parameter estimates to generate predictions for the remainder of the sample, we find that substantial profits may be made. Furthermore, the model correctly forecasts major crashes even on an out-of-sample basis.

The estimation of transition matrices for sovereign credit ratings

Rating transition matrices for sovereigns are an important input to risk management of portfolios of emerging market credit exposures. They are widely used both in credit portfolio management and to calculate future loss distributions for pricing purposes. However, few sovereigns and almost no low credit quality sovereigns have ratings histories longer than a decade, so estimating such matrices is difficult. This paper shows how one may combine information from sovereign defaults observed over a longer period and a broader set of countries to derive estimates of sovereign transition matrices.

Predicting emerging market currency crashes

This paper assesses the extent to which crashes in emerging market currencies are predictable using simple logit models based on lagged macroeconomic and financial data. To evaluate our model, we calculate trading strategies in which an investor goes long or short in the currency depending on whether crash probabilities are low or high. When we estimate the model on part of the data and then use the parameter estimates to generate predictions for the remainder of the sample, we find that substantial profits may be made. Furthermore, the model correctly forecasts major crashes even on an out-of-sample basis.

The demand for risky assets: Sample selection and household portfolios

Abstract We estimate a microeconomic model of household asset demands that allows for the fact that households typically have zero holdings of most assets. The adjustments for non-observed heterogeneity generalize methods developed by Dubin and McFadden (1984. Econometrica 52, 345–362). Simulating our model using a random sample of US households, we examine distributional and demographic effects on macroeconomic demands for money, stocks and bonds.

Value at Risk for Derivatives

Value at Risk is close to becoming the method of choice for assessing risk exposures faced by financial firms. The assets and liabilities in the firms risk portfolio are mapped onto a smaller set of standard factors, whose variances and correlations are given (estimated) The returns variance for the entire position is computed and the desired cutoff value for the lower tail of the portfolios returns distribution, under the typical assumption of joint lognormality, gives an estimate of the Value at Risk. But this procedure runs into large problems when derivatives with non-linear payoffs are included in the portfolio, an it also can be very difficult to implement with non-Gaussian returns. El Jahel, Perraudin, and Sellin present a new technique that greatly extends the range of assets and returns distribution that can be handled conveniently in a VaR calculation. For example, their framework easily accommodates non-linear payoffs, fat-tailed returns distributions, and stochastic volatility. It begins by computing the characteristic function for the whole portfolio, which is used to determine the first four moments of the returns distribution. Finally, an approximating distribution selected from a general family of distributions is fitted to these moments, and becomes the distribution used for VaR calculations. As the article shows, the results are distinctly more accurate than standard approaches.

A Continuous-Time Arbitrage-Pricing Model With Stochastic Volatility and Jumps

The authors formulate and test a continuous time asset pricing model using U.S. equity market data. They assume that stock returns are driven by common factors including random jump-size Poisson processes and Brownian motions with stochastic volatility. The model places over-identifying restrictions on the mean returns allowing one to identify risk neutral probability distributions useful in pricing derivative securities. The authors test for the restrictions and decompose moments of the asset returns into the contributions made by different factors. Their econometric methods take full account of time aggregation.

An Extreme Analysis of VaRs for Emerging Market Benchmark Bonds

This paper examines the practical usefulness of Extreme Value Theory (EVT) techniques for estimating Value-at-Risk (VaR). Unlike most past studies, the performance of EVT estimators of empirical return distributions. We show that for confidence levels similar to those commonly used in market risk calculations, EVT and naive estimators yield almost identical results when applied to one-day emerging estimators yield different results on actual data but differences disappear in a Monte Carlo exercises assuming t-distributed return innovations.

Introduction: Banks and systemic risk

The papers in this special issue were presented at a conference on Banks and Systemic Risk held at the Bank of England from 23–25 May 2001. 1 The papers covered three broad areas – banks and systemic risk; theory and evidence of market discipline and signals of bank fragility; and capital requirements and crisis prevention. The view that weakness in the banking sector may have serious systemic effects on the economy more generally hinges on several issues. Since the early 19th century (Thornton, 1802), it has been recognised that problems in one bank can spill over into more widespread difficulties in the sector. The nature of the contracts banks hold (short-term deposits and longer-term loans) exposes them to the possibility of runs; and linkages between banks combined with information asymmetries between counterparties and banks make them vulnerable to contagion. A number of papers have focussed on bank runs (e.g. Diamond and Dybvig, 1983) and the transmission mechanism of problems from one bank to others (e.g. Freixas et al., 2000). Other papers (e.g. Bernanke, 1983) have focussed on the wider costs to the economy if banks fail. This reflects the central position of banks in the payments system and their special role in intermediating flows of funds to small firms and the retail sector. One issue addressed at the conference was whether banking crises do in fact impose externalities on the system. It has been suggested that, with the growth of substitutes for bank intermediation particularly through the development of securities markets, bank failures may not impose substantial costs on economies. Hoggarth, Reis and Saporta (‘Costs of banking system instability: some empirical evidence’) review the estimates of fiscal costs incurred in dealing with a banking crisis and also Journal of Banking & Finance 26 (2002) 819–823

Banking Policy and the Pricing of Deposit Guarantees: A New Approach

This paper describes a new approach to pricing government deposit guarantees that uses techniques of stochastic process switching employed in the recent literature on exchange rate determination. Our model avoids inconsistent assumptions about the information available to investors and the government common in previous work based on an option pricing approach. We derive actuarially fair deposit insurance premia and optimal financial reorganization rules and examine the role of banking policies such as capital requirements.