Asymmetric effect of basis on dynamic futures hedging: Empirical evidence from commodity markets

Lien, Donald; Yang, Li

doi:10.1016/j.jbankfin.2007.01.026

Cited by 93 publications

(35 citation statements)

References 42 publications

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“…It is not surprising that most of the previous studies have focused predominantly on the firm's foreign currency risk (Hagelin 2003;Allayannis and Ofek, 2001;Géczy et al 1997), besides interest rate risk (Graham and Rogers, 2000;Carcano and Foresi, 1997;Mian 1996). And recently other market risks such as commodity risk, (see e.g., Lien and Yang, 2008;Alizadeh, Nomikos, and Pouliasis, 2008) and other non-financial risks such as information processing, technological, strategic and leadership risk (Linsley and Shrives, 2006) has become centre of attention. However, this empirical evidence regarding the choice of hedging instruments and determinants of foreign exchange risk hedging seems to reflect decision making of managers in the developed countries context which have found to have less information asymmetry, efficient market for corporate control, better institutional and legal systems.…”

Section: Introductionmentioning

confidence: 99%

Determinants of Corporate Hedging Practices in Malaysia

Ameer¹

2010

IBR

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This paper examines the impact of the firm specific factors on the use of derivative instruments for Malaysia firms. We find that there is a significant relationship between the use of derivatives and foreign sales, liquidity, firm growth, managerial ownership and size. Our findings suggest that only a few listed Malaysian firms have appropriate understanding of the derivatives instruments to mitigate risks in international business environment. Most Malaysian managers seem to be risk averse and do not understand the upside of taking position in the derivatives markets.

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Section: Introductionmentioning

confidence: 99%

Determinants of Corporate Hedging Practices in Malaysia

Ameer¹

2010

IBR

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“…For example, Driesprong, Jacobsen, and Maat (2008) use a standard OLS regression model to document a relationship between oil futures and world stock market returns. Lien and Yang (2008) demonstrate that the minimum variance hedge ratio for a given commodity is affected differently by a positive basis (i.e., backwardation) than a negative basis (i.e., contango). Trolle and Schwartz (2009) demonstrate that volatility for the derivatives of a given commodity may have both spanned and unspanned components, and that both types of volatility must be accounted for when estimating the instantaneous volatility for option contracts and futures curve dynamics.…”

Section: Introductionmentioning

confidence: 85%

“…It is noted that this study is limited by the inability of the model to account for volume or other external factors (such as contango or backwardation in the futures curve for each commodity) driving the spillover effects. Future studies in this area could apply foreign exchange-to-commodity spillover effects to hedging models such as the minimum variance hedge ratio examined by Lien and Yang (2008) and asset pricing models such as the Kalman filter model used by Cortazar and Severino (2008).…”

Section: Notesmentioning

confidence: 99%

Does FX Volatility Affect the Distributions of Commodity Futures Returns?

Grieb¹

2013

International Journal of Financial Research

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This paper employs a two-step GARCH-M procedure to study price and volatility spillover effects from a series of foreign exchange rate returns to CME Group commodities in the grains, livestock, and energy complexes. Exchange rates are purported to have supply and demand effects on commodity prices and we hypothesize that this translates into transmissions of distributional shocks from currency returns to commodity returns distributions. The currencies are segregated into three groups: large GDP economies and major US trade partners, emerging economies, and pacific rim countries. Our results show that exchange rates for the EU, Canada, Mexico, Brazil, and Australia have the strongest and broadest transmissions of mean innovations to the observed commodities. These are all either major trade partners with the US and/or major exporters of agricultural commodities. Volatility transmissions are much less pronounced and tend to occur for lower liquidity commodities. These results have implications for models considering asset pricing, price discovery, and hedging applications for commodity returns.

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“…4 Another difference between our model and the MRS-TVC-GARCH model is that we use Engle's (2002) DCC approach to model the condition correlations, while Lee and Yoder (2007b) and futures carbon prices is incorporated in the return process and the coefficient of the longrun relationship is allowed to be state-dependent. Lien and Yang (2008) argue that the lagged basis can help to determine the movement of spot and futures prices and facilitate the mean-reverting process, and therefore can serve as the proxy for the long-run relationship. Kroner and Sultan (1993) and Lai and Sheu (2010), among others, also use the lagged basis as the proxy for the long-run relationship.…”

Section: Introductionmentioning

confidence: 99%

Optimal Hedging in Carbon Emission Markets Using Markov Regime Switching Models

Philip

Shi

2014

SSRN Journal

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(2016) 'Optimal hedging in carbon emission markets using Markov regime switching models.', Journal of international nancial markets, institutions and money., 43 . pp. 1-15. Further information on publisher's website: Use policyThe full-text may be used and/or reproduced, and given to third parties in any format or medium, without prior permission or charge, for personal research or study, educational, or not-for-prot purposes provided that:• a full bibliographic reference is made to the original source • a link is made to the metadata record in DRO • the full-text is not changed in any way The full-text must not be sold in any format or medium without the formal permission of the copyright holders.Please consult the full DRO policy for further details. AbstractThis paper proposes a Markov regime switching framework for modeling carbon emission (CO 2 ) allowances that combines a regime switching behavior and disequilibrium adjustments in the mean process, along with a state-dependent dynamic volatility process. We find that all regime switching based hedging strategies significantly outperform single regime hedging strategies (both in-sample and out-of-sample), with the newly proposed framework providing the greatest variance reduction and the best hedging performance. Our results indicate that risk managers using state-dependent hedge ratios to manage portfolio risks in carbon emission markets will achieve superior hedging returns.JEL Classification: G13, G32, Q47

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Asymmetric effect of basis on dynamic futures hedging: Empirical evidence from commodity markets

Cited by 93 publications

References 42 publications

Determinants of Corporate Hedging Practices in Malaysia

Determinants of Corporate Hedging Practices in Malaysia

Does FX Volatility Affect the Distributions of Commodity Futures Returns?

Optimal Hedging in Carbon Emission Markets Using Markov Regime Switching Models

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