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Dowd, Kevin
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Dowd, Kevin
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Dowd, Kevin
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Now showing 1 - 6 of 6
- PublicationExtreme measures of agricultural financial riskThe agricultural marketing environment is inherently risky. Having accurate measures of risk helps farmers policy makers and financial institutions make better informed decisions about how to deal with this risk. This paper examines three tail quantile-based risk measures applied to the estimation of extreme agricultural financial risk for corn and soybean production in the US: Value at Risk (VaR), Expected Shortfall (ES) and Spectral Risk Measures (SRMs). We use Extreme Value Theory (EVT) to model the tail returns and present results for these three different risk measures using agricultural futures market returns data. We compare estimated risk measures in terms of size and precision, and find that they are all considerably higher than Normal estimates. The estimated risk measures are also quite imprecise, and become more so as the risks involved become more extreme.
449Scopus© Citations 18 - PublicationExtreme global equity market riskExtreme asset price movements appear to be more pronounced over time and have major consequences for an economy’s financial stability and monetary policies. This article investigates the extreme behaviour of equity market returns and quantifies the probabilities of these losses. Taking 14 major equity markets, the study illustrates similarities and divergences in the tail returns from around the world. To do so, it applies extreme value theory to equity indexes representing American, Asian and European markets. The article finds that all markets tail realisations are adequately modelled with the fat-tailed Fréchet distribution. Furthermore, tail realisations associated with the downside of a distribution are greater than those associated with the upside, and extreme returns for Asian markets are usually larger than their European and American counterparts.
374 - PublicationExtreme spectral risk measures : an application to futures clearinghouse margin requirements(University College Dublin. School of Business. Centre for Financial Markets, 2005-12-14)
; This paper applies the Extreme-Value (EV) Generalised Pareto distribution to the extreme tails of the return distributions for the S&P500, FT100, DAX, Hang Seng, and Nikkei225 futures contracts. It then uses tail estimators from these contracts to estimate spectral risk measures, which are coherent risk measures that reflect a user’s risk-aversion function. It compares these to VaR and Expected Shortfall (ES) risk measures, and compares the precision of their estimators. It also discusses the usefulness of these risk measures in the context of clearinghouses setting initial margin requirements, and compares these to the SPAN measures typically used.353 - PublicationSpectral risk measures with an application to futures clearinghouse variation margin requirements(University College Dublin. School of Business. Centre for Financial Markets, 2006-10-31)
; This paper applies an AR(1)-GARCH (1, 1) process to detail the conditional distributions of the return distributions for the S&P500, FT100, DAX, Hang Seng, and Nikkei225 futures contracts. It then uses the conditional distribution for these contracts to estimate spectral risk measures, which are coherent risk measures that reflect a user’s risk-aversion function. It compares these to more familiar VaR and Expected Shortfall (ES) measures of risk, and also compares the precision and discusses the relative usefulness of each of these risk measures in setting variation margins that incorporate time-varying market conditions. The goodness of fit of the model is confirmed by a variety of backtests.267 - PublicationExtreme measures of agricultural financial risk(University College Dublin. School of Business. Centre for Financial Markets, 2008-10-06)
; ; Risk is an inherent feature of agricultural production and marketing and accurate measurement of it helps inform more efficient use of resources. This paper examines three tail quantile-based risk measures applied to the estimation of extreme agricultural financial risk for corn and soybean production in the US: Value at Risk (VaR), Expected Shortfall (ES) and Spectral Risk Measures (SRMs). We use Extreme Value Theory (EVT) to model the tail returns and present results for these three different risk measures using agricultural futures market data. We compare the estimated risk measures in terms of their size and precision, and find that they are all considerably higher than normal estimates; they are also quite uncertain, and become more uncertain as the risks involved become more extreme.445 - PublicationThe tail risks of FX return distributions : a comparison of the returns associated with limit orders and market orders(University College Dublin. School of Business. Centre for Financial Markets, 2007-05-18)
; This paper measures and compares the tail risks of limit and market orders using Extreme Value Theory. The analysis examines realised tail outcomes using the Dealing 2000-2 electronic broking system based on completed transactions rather than the more common analysis of indicative quotes. In general, limit and market orders exhibit broadly similar tail behaviour, but limit orders have significantly heavier tails and larger tail quantiles than market orders.280