Now showing 1 - 10 of 13
  • Publication
    Performance of Utility Based Hedges
    (University College Dublin. Geary Institute, 2014-03-04) ;
    Hedgers as investors are concerned with both risk and return; however the literature has generally neglected the role of both returns and investor risk aversion by its focus on minimum variance hedging. In this paper we address this by using utility based performance metrics to evaluate the hedging effectiveness of utility based hedges for hedgers with both moderate and high risk aversion together with the more traditional minimum variance approach. We apply our approach to two asset classes, equity and energy, for three different hedging horizons, daily,weekly and monthly. We find significant differences between the minimum variance and utility based hedges and their attendant performance in-sample for all frequencies. However out of sample performance differences persist for the monthly frequency only.
      260
  • Publication
    Time-varying risk aversion : an application to energy hedging
    (Elsevier, 2010-03) ;
    Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison.
      483
  • Publication
    Hedging effectiveness under conditions of asymmetry
    (Taylor & Francis, 2012-01-31) ;
    We examine whether hedging effectiveness is affected by asymmetry in the return distribution by applying tail specific metrics, for example, Value at Risk, to compare the hedging effectiveness of short and long hedgers. Comparisons are applied to a number of hedging strategies including OLS, and both symmetric and asymmetric GARCH models. We apply our analysis to a dataset consisting of S&P500 index cash and futures containing symmetric and asymmetric return distributions chosen ex-post. Our findings show that asymmetry reduces out-of-sample hedging performance and that significant differences occur in hedging performance between short and long hedgers.
      345Scopus© Citations 23
  • Publication
    Hedging and risk aversion constraints
    (University College Dublin. School of Business. Centre for Financial Markets, 2005) ;
    We examine whether hedging effectiveness is affected by asymmetry in the return distribution by applying tail specific metrics to compare the hedging effectiveness of short and long hedgers using crude oil futures contracts. The metrics used include Lower Partial Moments (LPM), Value at Risk (VaR) and Conditional Value at Risk (CVAR). Comparisons are applied to a number of hedging strategies including OLS and both Symmetric and Asymmetric GARCH models. Our findings show that asymmetry reduces in-sample hedging performance and that there are significant differences in hedging performance between short and long hedgers. Thus, tail specific performance metrics should be applied in evaluating hedging effectiveness. We also find that the Ordinary Least Squares (OLS) model provides consistently good performance across different measures of hedging effectiveness and estimation methods irrespective of the characteristics of the underlying distribution.
      134
  • Publication
    Hedging your bets
    (Euromoney Institutional Investor PLC., 2006-06) ;
      161
  • Publication
    Re-evaluating hedging performance
    (University College Dublin. School of Business. Centre for Financial Markets, 2005-07-24) ;
    Mixed results have been documented for the performance of hedging strategies using futures. This paper reinvestigates this issue using an extensive set of performance evaluation metrics across seven international markets. We compare the hedging performance of short and long hedgers using traditional variance based approaches together with modern risk management techniques including Value at Risk, Conditional Value at Risk and approaches based on Downside Risk. Our findings indicate that using these metrics to evaluate hedging performance, yields differences in terms of best hedging strategy as compared with the traditional variance measure. We also find significant differences in performance between short and long hedgers. These results are observed both in-sample and out-of-sample.
      372
  • Publication
    Hedging : scaling and the investor horizon
    (University College Dublin. School of Business. Centre for Financial Markets, 2009-08) ;
    This paper examines the volatility and covariance dynamics of cash and futures contracts that underlie the Optimal Hedge Ratio (OHR) across different hedging time horizons. We examine whether hedge ratios calculated over a short term hedging horizon can be scaled and successfully applied to longer term horizons. We also test the equivalence of scaled hedge ratios with those calculated directly from lower frequency data and compare them in terms of hedging effectiveness. Our findings show that the volatility and covariance dynamics may differ considerably depending on the hedging horizon and this gives rise to significant differences between short term and longer term hedges. Despite this, scaling provides good hedging outcomes in terms of risk reduction which are comparable to those based on direct estimation.
      469
  • Publication
    Hedging effectiveness under conditions of asymmetry
    (University College Dublin. School of Business. Centre for Financial Markets, 2007) ;
    We examine whether hedging effectiveness is affected by asymmetry in the return distribution by applying tail specific metrics to compare the hedging effectiveness of short and long hedgers using crude oil futures contracts. The metrics used include Lower Partial Moments (LPM), Value at Risk (VaR) and Conditional Value at Risk (CVAR). Comparisons are applied to a number of hedging strategies including OLS and both Symmetric and Asymmetric GARCH models. Our findings show that asymmetry reduces in-sample hedging performance and that there are significant differences in hedging performance between short and long hedgers. Thus, tail specific performance metrics should be applied in evaluating hedging effectiveness. We also find that the Ordinary Least Squares (OLS) model provides consistently good performance across different measures of hedging effectiveness and estimation methods irrespective of the characteristics of the underlying distribution.
      260
  • Publication
    Time varying risk aversion : an application to energy hedging
    Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison.
      923
  • Publication
    Time varying risk aversion : an application to energy hedging
    (University College Dublin. School of Business. Centre for Financial Markets, 2009-08) ;
    Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison.
      365