Now showing 1 - 10 of 13
  • Publication
    Financial risks and the Pension Protection Fund : can it survive them?
    (University College Dublin. School of Business. Centre for Financial Markets, 2006-11) ; ;
    This paper discusses the financial risks faced by the UK Pension Protection Fund (PPF) and what, if anything, it can do about them. It draws lessons from the regulatory regimes under which other financial institutions, such as banks and insurance companies, operate and asks why pension funds are treated differently. It also reviews the experience with other government-sponsored insurance schemes, such as the US Pension Benefit Guaranty Corporation, upon which the PPF is modelled. We conclude that the PPF will live under the permanent risk of insolvency as a consequence of the moral hazard, adverse selection, and, especially, systemic risks that it faces.
      381
  • Publication
    Estimating financial risk measures for futures positions : a non-parametric approach
    (University College Dublin. School of Business. Centre for Financial Markets, 2006-12-23) ;
    This paper presents non-parametric estimates of spectral risk measures applied to long and short positions in 5 prominent equity futures contracts. It also compares these to estimates of two popular alternative measures, the Value-at-Risk (VaR) and Expected Shortfall (ES). The spectral risk measures are conditioned on the coefficient of absolute risk aversion, and the latter two are conditioned on the confidence level. Our findings indicate that all risk measures increase dramatically and their estimators deteriorate in precision when their respective conditioning parameter increases. Results also suggest that estimates of spectral risk measures and their precision levels are of comparable orders of magnitude as those of more conventional risk measures.
      335
  • Publication
    The 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.
      277
  • Publication
    Evaluating the precision of estimators of quantile-based risk measures
    (University College Dublin. School of Business. Centre for Financial Markets, 2007-05) ;
    This paper examines the precision of estimators of Quantile-Based Risk Measures (Value at Risk, Expected Shortfall, Spectral Risk Measures). It first addresses the question of how to estimate the precision of these estimators, and proposes a Monte Carlo method that is free of some of the limitations of existing approaches. It then investigates the distribution of risk estimators, and presents simulation results suggesting that the common practice of relying on asymptotic normality results might be unreliable with the sample sizes commonly available to them. Finally, it investigates the relationship between the precision of different risk estimators and the distribution of underlying losses (or returns), and yields a number of useful conclusions.
      275
  • Publication
    Spectral 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.
      264
  • Publication
    How unlucky is 25-Sigma?
    (University College Dublin. School of Business. Centre for Financial Markets, 2008-03-24) ; ; ;
      1052
  • Publication
    Intra-day seasonality in foreign exchange market transactions
    (University College Dublin. School of Business. Centre for Financial Markets, 2007-05-18) ;
    This paper examines the intra-day seasonality of transacted limit and market orders in the DEM/USD foreign exchange market. Empirical analysis of completed transactions data based on the Dealing 2000-2 electronic inter-dealer broking system indicates significant evidence of intraday seasonality in returns and return volatilities under usual market conditions. Moreover, analysis of realised tail outcomes supports seasonality for extraordinary market conditions across the trading day.
      285
  • Publication
    U.S. core inflation : a wavelet analysis
    (University College Dublin. School of Business. Centre for Financial Markets, 2006-09-10) ;
    This paper proposes the use of wavelet methods to estimate U.S. core inflation. It explains wavelet methods and suggests they are ideally suited to this task. Comparisons are made with traditional CPI-based and regression-based measures for their performance in following trend inflation and predicting future inflation. Results suggest that wavelet-based measures perform better, and sometimes much better, than the Traditional approaches. These results suggest that wavelet methods are a promising avenue for future research on core inflation.
      353
  • Publication
    Extreme 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.
      439
  • Publication
    Spectral risk measures : properties and limitations
    (University College Dublin. School of Business. Centre for Financial Markets, 2008-04-18) ; ;
    Spectral risk measures (SRMs) are risk measures that take account of user risk aversion, but to date there has been little guidance on the choice of utility function underlying them. This paper addresses this issue by examining alternative approaches based on exponential and power utility functions. A number of problems are identified with both types of spectral risk measure. The general lesson is that users of spectral risk measures must be careful to select utility functions that fit the features of the particular problems they are dealing with, and should be especially careful when using power SRMs.
      400