Combining momentum with reversal in commodity futures

Bianchi, Robert J.; Drew, Michael E.; Fan, John Hua

doi:10.1016/j.jbankfin.2015.07.006

Cited by 74 publications

(89 citation statements)

References 76 publications

(117 reference statements)

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“…Momentum suffered considerable losses following the GFC. Notably, the persistence of momentum post-2010 is in sharp contrast with the previous literature (Bianchi, Drew, & Fan, 2016;Bianchi et al, 2015), signaling a segmented market.…”

Section: Distant Contracts With Alleviated Limitscontrasting

confidence: 80%

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The untold story of commodity futures in China

Fan

Zhang

2019

Journal of Futures Markets

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We investigate the behavior of commodity futures risk premia in China. In the presence of retail‐dominance and barriers‐to‐entry, the term structure and momentum premia remain persistent, whereas hedging pressure, skewness, volatility, and liquidity premia are distorted by time‐varying margins and strict position limits. Furthermore, open interest, currency, and inflation premia are sensitive to institutional settings. The observed premia cannot be attributed to common risks, sentiment, transactions costs, or data‐snooping, but are related to liquidity, anchoring, and regulation‐induced limits‐to‐arbitrage. We highlight the distinctive features of Chinese futures markets and assess the challenges posed to theories of commodity risk premia.

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Section: Distant Contracts With Alleviated Limitscontrasting

confidence: 80%

“…The MOM strategy buys (sells) past winners (losers) based on the cumulative performance over the most recent 12 months. The existence of the momentum premium is documented extensively in the literature (Bakshi et al, 2019;Bianchi, Drew, & Fan, 2015;Miffre & Rallis, 2007).…”

Section: Term Structurementioning

confidence: 99%

The untold story of commodity futures in China

Fan

Zhang

2019

Journal of Futures Markets

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“…First, the set of test assets could be significantly extended. For example, it might be interesting to have a look at the performance of EVT-based VaR estimators for highly liquid individual stocks (such as the components of the Dow Jones Industrial Average; see Taylor, 2014;Auer and Schuhmacher, 2015) or futures (such as the subindices of the GSCI; see Auer, 2015;Bianchi et al, 2015) which are typical components of investors' portfolios. Second one might conduct a suitable simulation study in which our VaR estimators are compared in different settings.…”

Section: Resultsmentioning

confidence: 99%

How accurate are modern Value-at-Risk estimators derived from extreme value theory?

Mögel

Auer

2017

Rev Quant Finan Acc

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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. In this study, we compare the out-of-sample forecasting performance of several modern Valueat-Risk (VaR) estimators derived from extreme value theory (EVT). Specifically, in a multiasset study covering 30 years of stock, bond, commodity and currency market data, we analyse the accuracy of the classic generalised Pareto peak over threshold approach and three recently proposed methods based on the Box-Cox transformation, L-moment estimation and the Johnson system of distributions. We find that, in their unconditional form, some of the estimators are acceptable under current regulatory assessment rules but none of them can continuously pass more advanced tests of forecasting accuracy. In their conditional forms, forecasting power is significantly increased and the Box-Cox method proves to be the most promising estimator. However, it is also important to stress that the traditional historical simulation approach, which is currently the most frequently used VaR estimator in commercial banks, can not only keep up with the EVT-based methods but occasionally even outperforms them (depending on the setting: unconditional vs. conditional). Thus, recent claims to generally replace this simple method by theoretically more advanced EVT-based methods may be premature. Terms of use: Documents inJEL-Codes: G100, G110, G170.

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“…Chai, Limkriangkrai, and Ji () finds a relation between reversal and momentum in Australian stocks. Bianchi, Drew, and Fan () connect momentum and reversal patterns in commodity futures. However, to the best of our knowledge, no study has so far analyzed the coexistence and interaction of reversal and momentum for one of the most liquid markets, the European stock market.…”

Section: Introductionmentioning

confidence: 99%

Reversal and momentum patterns in weekly stock returns: European evidence

Hühn

Scholz

2018

Rev Financ Econ

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We analyze short‐term reversal and medium‐term momentum patterns in weekly stock returns in Europe. Focusing on raw and stock‐specific returns, our empirical results show for both return specifications (a) a negative relation between weekly past returns and future returns in the short run and (b) a positive relation in the medium run. However, returns from reversal and momentum strategies based on stock‐specific returns are less volatile. In further analyses, we find short‐term reversal and medium‐term momentum patterns to be connected to stock characteristics. Looking at the potential causes of these effects, our results do not support the idea that short‐term reversal in weekly stock returns is due to an over‐ or underreaction to firm‐specific news nor that it is mainly driven by illiquidity. Medium‐term momentum in weekly stock returns, on the other hand, can be connected to behavioral biases. Our concluding tests confirm that our findings are robust among industries, in subperiods, for the January effect and in varying market states. Finally, while medium‐term momentum strategies remain profitable after accounting for transaction costs, short‐term reversal strategies can be mainly explained by transaction costs due to their high turnover.

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Combining momentum with reversal in commodity futures

Cited by 74 publications

References 76 publications

The untold story of commodity futures in China

The untold story of commodity futures in China

How accurate are modern Value-at-Risk estimators derived from extreme value theory?

Reversal and momentum patterns in weekly stock returns: European evidence

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