Futures hedging with basis risk and expectation dependence

Бролл, Удо; Welzel, Peter; Wong, Kit Pong

doi:10.1007/s12232-015-0240-1

Cited by 8 publications

(2 citation statements)

References 19 publications

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“…Fama & French (2015) [6] found that the interest rate change, storage costs, and opportunity costs have different effects on the basis volatility for commodity futures. Broll, Welzel & Wong (2015) [7] pointed out that if the random price is negatively correlated with the expected value of the basis risk, then partial hedging is optimal; if there is a positive correlation, then excessive hedging is optimal, and the optimal position will be uncertain. Zhuang et al (2016) [8] explored the basis risk for the hedging in the steel futures market and analyzed the impact of macroeconomic factors and micromarket factors on the basis risk empirically, and it was found that the VaR of basis provides a foundation for hedging the risks with parametric, semiparametric, and nonparametric GARCH methods.…”

Section: Introductionmentioning

confidence: 99%

Research on the Value at Risk of Basis for Stock Index Futures Hedging in China Based on Two-State Markov Process and Semiparametric RS-GARCH Model

Wang

Qin

et al. 2019

Discrete Dynamics in Nature and Society

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This article aims to investigate the Value at Risk of basis for stock index futures hedging in China. Since the RS-GARCH model can effectively describe the state transition of variance in VaR and the two-state Markov process can significantly reduce the dimension, this paper constructs the parameter and semiparametric RS-GARCH models based on two-state Markov process. Furthermore, the logarithm likelihood function method and the kernel estimation with invariable bandwidth method are used for VaR estimation and empirical analysis. It is found that the three fitting errors (MSE, MAD, and QLIKE) of conditional variance calculated by semiparametric model are significantly smaller than that of the parametric model. The results of Kupiec backtesting on VaR obtained by the two models show that the failure days of the former are less than or equal to that of the latter, so it can be inferred that the semiparametric RS-GARCH model constructed in this paper is more effective in estimating the Value at Risk of the basis for Chinese stock index futures. In addition, the mean value and standard deviation of VaR obtained by the semiparametric RS-GARCH model are smaller than that of the parametric method, which can prove that the former model is more conservative in risk estimation.

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Section: Introductionmentioning

confidence: 99%

Research on the Value at Risk of Basis for Stock Index Futures Hedging in China Based on Two-State Markov Process and Semiparametric RS-GARCH Model

Wang

Qin

et al. 2019

Discrete Dynamics in Nature and Society

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“…The commonly used approach is confined to choosing only futures for hedging risk, from which two celebrated theorems (separation theorem and full-hedging theorem) emanate, see e.g., [4][5][6]). …”

Section: Introductionmentioning

confidence: 99%

Optimal Hedging with Options and Futures against Price Risk and Background Risk

Sun

2017

MCA

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On the condition that both futures and options exist in the markets for hedging, this paper examines the optimal hedging strategy under price risk and background risk. Compared with the previous research, which has studied options hedging against basis risk and production risk being extended to options and futures hedging against price risk and background risk, we proposed a model and have taken the budget of buying options into consideration. The model is fairly general and some existing models are special cases of it. We firstly derive the necessary and sufficient conditions that guarantee the optimality of an under-hedge, a full-hedge and an over-hedge of futures for the risk-averse utility. Then, sufficient conditions are stipulated under which an over-hedge is optimal. Furthermore, we propose a program minimizing of tail conditional expectation (TCE), which is inherently equivalent to the risk measure of expected shortfall risk (ES) or the conditional VaR (CVaR) under the continuous-time framework. Finally, we find that ES, in our proposed model, is significantly smaller than the one in the model of options hedging only. Therefore, the results emphasize the need for combining futures hedging and options hedging, and it also shows that imposing background risk, whether it be additive or multiplicative, always has a great impact on the hedging efficiency. We also present some sensitivities of the relevant parameters to provide some suggestions for the investors.

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The impact of inflation risk on forward trading and production

Бролл

Wong

2015

Port Econ J

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. This note examines the behavior of a competitive firm that faces joint price and inflation risk. Given that the price risk is negatively correlated with the inflation risk in the sense of expectation dependence, the firm optimally opts for an overhedge if the firm's coefficient of relative risk aversion is everywhere no greater than unity. Furthermore, banning the firm from forward trading may induce the firm to produce more or less, depending on whether the price risk premium is positive or negative, respectively. While the price risk premium is unambiguously negative in the absence of the inflation risk, it is not the case when the inflation risk prevails. In contrast to the conventional wisdom, forward hedging needs not always promote production should firms take in inflation seriously. Terms of use: Documents in

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Futures hedging with basis risk and expectation dependence

Cited by 8 publications

References 19 publications

Research on the Value at Risk of Basis for Stock Index Futures Hedging in China Based on Two-State Markov Process and Semiparametric RS-GARCH Model

Research on the Value at Risk of Basis for Stock Index Futures Hedging in China Based on Two-State Markov Process and Semiparametric RS-GARCH Model

Optimal Hedging with Options and Futures against Price Risk and Background Risk

The impact of inflation risk on forward trading and production

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