Philip A. Stork

Differences between foreign exchange rate regimes: The view from the tails

In the literature on the empirical unconditional distribution of forein exchange rate returns there is indication that the type of distribution function is related to the form of the exchange rate regime. The analysis has been hampered by the nonnestedness of the alternative distribution models. The paper investigates the issue by means of extremal analysis which allows for a unified treatment. In particular, we try to sort out whether apparent distributional differences are due to differences in techniques or regimes.

Bank Size and Systemic Risk

The global financial crisis that started in mid-2007 illustrates the relevance of systemic risk. One key driver of the systemic instability that materialized in the crisis was the elevated level of stress in large banks. We use EVT to analyse the effect of size on banks’ univariate and systemic risk across ten countries as well as across the EU. Our findings show that size has little impact on banks’ univariate risk (as measured by VaR), but that large banks have significantly higher systemic risk. Furthermore, systemic risk has significantly increased for banks of all sizes since the beginning of the crisis.

An EMS Target Zone Model in Discrete Time

The discrete time analogue of the continuous time Krugman target zone model is developed in order to capture the typical volatility clusters and fat-tailed distributed innovations of exchange rates. It is shown that under these more general stochastic conditions the S-shaped relation between exchange rate and fundamentals is preserved, but is less pronounced. The model is tested for its S-shape and stochastic properties. Two clearly distinct sets of EMS currencies are detected on the basis of the curvature features. One-step-ahead realignment probabilities are used as an alternative evaluation method.

New Evidence On The Effectiveness Of Foreign Exchange Market Intervention

This paper compares foreign exchange market intervention in case there is no uncertainty about the extent of an imperfectly sustainable target zone and where there is uncertainty. A well-known example of the first case was the European Monetary System between 1979 and 1992. An example of the latter is the dirty floating of the dollar against the Dmark and yen after the so-called Louvre Accord in 1987. The analysis shows that the instantaneous effectiveness of intervention tends to be larger the more implicit the band policy is. Our empirical results which use Belgian and US intervention data support this claim.

Short-Selling, Leverage, and Systemic Risk

During the Global Financial Crisis, regulators imposed short-selling bans to protect financial institutions. The rationale behind the bans was that “bear raids”, driven by short-sellers, would increase the individual and systemic risk of financial institutions, especially for institutions with high leverage. This study uses Extreme Value Theory to estimate the effect of short-selling on financial institutions’ individual and systemic risks in France, Italy and Spain; it also analyses the relationship between financial institutions’ leverage and short-selling. The results show that short-sellers appear to specifically target institutions with lower capital levels. Furthermore, institutions’ risk-levels and changes in short-selling positions tend to move in tandem.

A Trustee Guide to Factor Investing

Factor investing is rapidly becoming mainstream in the investment community. Although the technique has progressed impressively, the governance to implement it successfully has lagged behind. In this article, the authors analyze how pension funds and institutional investors implement new insights into factor investing and how they work with the factors that drive asset returns as a portfolio construction tool. The authors review hurdles in the implementation process, analyze the reasons behind them, and then develop a checklist with eight recommendations to consider when implementing factor investing. Looking forward, the authors explore three emerging approaches to factor investing and examine how these approaches could be implemented.

On Agricultural Commodities' Extreme Price Risk

Price risk is among the most substantial risk factors for farmers. Through a two-sector general equilibrium model, we describe how fat tails in agricultural prices may occur endogenously as a result of productivity shocks. Using thirty years of daily futures price data, we show that the returns of all agricultural commodities in our sample closely follow a power law in the tail of their distributions. We apply Extreme Value Theory to estimate the size and likelihood of the highest losses a farmer may encounter. Back-testing verifies the validity of these risk measurement methods.

Tail Risk Reduction Strategies

We analyze a number of systematic investment strategies that intend to reduce tail risk. Using Extreme Value Theory, we calculate Value at Risk and Expected Shortfall measures. A CAPM and down- and upside beta framework is used to study investment returns over different asset classes. We find that some mechanical strategies generate average compounded returns similar to those of the buy-and-hold strategy, and that tail risks are indeed reduced significantly.

An Empirical Note on US Stock Split Announcements, 2000-2009

This article analyses the market reaction to stock splits announcements, using a unique US sample over the period 2000 to 2009. Our event study finds a significantly positive Cumulative Average Abnormal Return (CAAR) around the announcement date. Liquidity increases lead to higher stock price changes, which supports the liquidity improvement hypothesis. Further, firm size and abnormal returns are inversely related, which is in line with the attention hypothesis.

Policy optimization by lexicographic preference ordering

A lexicographic preference ordering of policy objectives is used to define the policymakers choice among alternatives. It is shown how the constrained multiple goal problem can be placed in a one-to-one relationship with multidimensional utility analysis. The method is applied to a model of the Dutch economy and it is shown that is has good potential as a policy optimization method, its strengths being its ease of use and the quality of its results.