Optimal Dynamic Hedging via Copula-Threshold-GARCH Models

Lai, YiHao; Chen, Cathy W. S.; Gerlach, Richard

doi:10.2139/ssrn.1410558

Cited by 16 publications

(24 citation statements)

References 26 publications

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“…The elliptical form of dependence inherent in a bivariate normal cannot capture the co-movement phenomenon commonly observed in the financial markets (Lai et al, 2007;Rodriguez, 2007). Instead, Gumbel and Clayton copulas exhibit, respectively, the upper tail dependence and the lower tail dependence and the mixture of Gumbel and Clayton copulas captures both these tail dependences and hence the co-movement phenomenon observed in the financial markets.…”

Section: Leementioning

confidence: 98%

“…Patton (2006a,b) introduced the concept of conditional copula to capture the time shifts in the dependence structure. This study also allows and to be time varying by defining and (Nelsen, 1999), where t t is the time-varying scaled invariant dependence measure Kendall's t, which is given by (Lai et al, 2007). The dependence process is specified as (21) where parameters u 1 and u 2 are assumed non-negative and (Tse & Tsui, 2002).…”

Section: Leementioning

confidence: 99%

“…To solve this path-dependency problem, previous regime-switching GARCH hedging models use Gray's (1996) 1 Symmetric tail dependence restricts that extremely favorable or unfavorable market conditions drive the dependency by the same magnitude, but there is mounting evidence that although financial markets are more likely to collapse or to boom together, the magnitude might not be the same or even similar (Lai, Chen, & Gerlach, 2007;Rodriguez, 2007). Therefore, Gumbel and Clayton copulas are chosen in this study because of their ability in capturing asymmetries in tail dependence.…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, Gumbel and Clayton copulas are chosen in this study because of their ability in capturing asymmetries in tail dependence. Dias and Embrechts (2004), Lai et al (2007), and Rodriguez (2007), among others, also apply the mixture of Gumbel and Clayton copulas to the empirical finance.…”

Section: Introductionmentioning

confidence: 99%

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A copula‐based regime‐switching GARCH model for optimal futures hedging

Lee

2009

Journal of Futures Markets

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The article develops a regime-switching Gumbel-Clayton (RSGC) copula GARCH model for optimal futures hedging. There are three major contributions of RSGC. First, the dependence of spot and futures return series in RSGC is modeled using switching copula instead of assuming bivariate normality. Second, RSGC adopts an independent switching Generalized Autoregressive Conditional Heteroscedasticity (GARCH) process to avoid the path-dependency problem. Third, based on the assumption of independent switching, a formula is derived for calculating the minimum variance hedge ratio. Empirical investigation in agricultural commodity markets reveals that RSGC provides good out-of-sample hedging effectiveness, illustrating importance of modeling regime shift and asymmetric dependence for futures hedging.

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Section: Leementioning

confidence: 98%

Section: Leementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A copula‐based regime‐switching GARCH model for optimal futures hedging

Lee

2009

Journal of Futures Markets

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“…Finally, Lai et al (2009) employed copula methodologies and DCC-Garch and concluded that hedge ratios constructed by a Gaussian or Mixture copula are the best-performed in variance reduction for all markets except Japan and Singapore, and provide close to the best returns on a hedging portfolio over the sample period.…”

Section: Literature Reviewmentioning

confidence: 99%

Hedging Effectiveness in Energy Market during Economic Crisis: Better Way to Integration

Samitas¹,

Tsakalos²,

Eriotis³

2011

JEI

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This paper investigates hedging and risk management options in the energy sector. Energy firms tend to adopt risk management tools in order to cover their financial exposure. Taking into consideration that current crisis has a significant effect on their value; we check whether energy firms actually have better output when they use hedging tools. In order to measure the effectiveness of this strategy in the energy industry, we adopt Tobin's Q methodology. The sample of this study consists energy firms on a worldwide basis. The empirical evidence of this research confirms that energy firms may avoid huge economic problems when they adopt risk management methods. It is better enery market integration.• JEL Classification: G14, G15

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Volatility spillovers between food and energy markets: A semiparametric approach

Serra

2011

Energy Economics

180

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Previous literature on volatility links between food and energy prices is scarce and mainly based on parametric approaches. We assess this issue by using a semiparametric GARCH model recently proposed by Long et al. (2009), which is essentially a nonparametric correction of the parametric conditional covariance function. We focus on price links between crude oil, ethanol and sugar prices in Brazil. Results suggest strong volatility links between the prices studied. They also suggest that parametric approximations of the conditional covariance matrix may lead to misleading results and can be improved using nonparametric techniques.

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Optimal Dynamic Hedging via Copula-Threshold-GARCH Models

Cited by 16 publications

References 26 publications

A copula‐based regime‐switching GARCH model for optimal futures hedging

A copula‐based regime‐switching GARCH model for optimal futures hedging

Hedging Effectiveness in Energy Market during Economic Crisis: Better Way to Integration

Volatility spillovers between food and energy markets: A semiparametric approach

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