IDEAS home Printed from https://ideas.repec.org/a/eee/ecofin/v63y2022ics1062940822001656.html
   My bibliography  Save this article

Investor sentiment and energy futures predictability: Evidence from Feasible Quasi Generalized Least Squares

Author

Listed:
  • Fasanya, Ismail
  • Adekoya, Oluwasegun
  • Oyewole, Oluwatomisin
  • Adegboyega, Soliu

Abstract

Contributing to the budding literature on how emotional and sentimental actions impact the performance of financial markets, this study examines the predictability of energy futures prices with investors’ sentiments. In particular, we examine which of the three (neutral, bear and bull) investors’ sentiments offer accurate forecast information on four energy futures prices. Using the predictability test proposed by Westerlund and Narayan (2015), we discover that all the forms of investors’ sentiments are significant predictors of the movements in energy futures prices. However, the bear sentiments outshine other variants in the forecast of crude oil futures prices, while the bull sentiments provide the most accurate forecast information for the remaining energy futures prices, namely heating oil, gasoline and natural gas. We also find this evidence consistent even when asymmetries are considered in the predictability models. Among other implications of these findings, investors in energy futures and portfolio managers are expected to consider often emotional perceptions in their portfolio constructions and the predictability of future gains.

Suggested Citation

  • Fasanya, Ismail & Adekoya, Oluwasegun & Oyewole, Oluwatomisin & Adegboyega, Soliu, 2022. "Investor sentiment and energy futures predictability: Evidence from Feasible Quasi Generalized Least Squares," The North American Journal of Economics and Finance, Elsevier, vol. 63(C).
  • Handle: RePEc:eee:ecofin:v:63:y:2022:i:c:s1062940822001656
    DOI: 10.1016/j.najef.2022.101830
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1062940822001656
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.najef.2022.101830?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Batten, Jonathan A. & Ciner, Cetin & Lucey, Brian M., 2017. "The dynamic linkages between crude oil and natural gas markets," Energy Economics, Elsevier, vol. 62(C), pages 155-170.
    2. Ding, Zhihua & Liu, Zhenhua & Zhang, Yuejun & Long, Ruyin, 2017. "The contagion effect of international crude oil price fluctuations on Chinese stock market investor sentiment," Applied Energy, Elsevier, vol. 187(C), pages 27-36.
    3. Tiwari, Aviral Kumar & Mukherjee, Zinnia & Gupta, Rangan & Balcilar, Mehmet, 2019. "A wavelet analysis of the relationship between oil and natural gas prices," Resources Policy, Elsevier, vol. 60(C), pages 118-124.
    4. Joakim Westerlund & Paresh Narayan, 2015. "Testing for Predictability in Conditionally Heteroskedastic Stock Returns," Journal of Financial Econometrics, Oxford University Press, vol. 13(2), pages 342-375.
    5. Koop, Gary & Korobilis, Dimitris, 2011. "UK macroeconomic forecasting with many predictors: Which models forecast best and when do they do so?," Economic Modelling, Elsevier, vol. 28(5), pages 2307-2318, September.
    6. Karali, Berna & Ramirez, Octavio A., 2014. "Macro determinants of volatility and volatility spillover in energy markets," Energy Economics, Elsevier, vol. 46(C), pages 413-421.
    7. Bahloul, Walid & Bouri, Abdelfettah, 2016. "The impact of investor sentiment on returns and conditional volatility in U.S. futures markets," Journal of Multinational Financial Management, Elsevier, vol. 36(C), pages 89-102.
    8. Malcolm Baker & Jeffrey Wurgler, 2006. "Investor Sentiment and the Cross‐Section of Stock Returns," Journal of Finance, American Finance Association, vol. 61(4), pages 1645-1680, August.
    9. Bouri, Elie & Gabauer, David & Gupta, Rangan & Tiwari, Aviral Kumar, 2021. "Volatility connectedness of major cryptocurrencies: The role of investor happiness," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).
    10. Qadan, Mahmoud & Nama, Hazar, 2018. "Investor sentiment and the price of oil," Energy Economics, Elsevier, vol. 69(C), pages 42-58.
    11. Deeney, Peter & Cummins, Mark & Dowling, Michael & Bermingham, Adam, 2015. "Sentiment in oil markets," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 179-185.
    12. He, Zhifang, 2022. "Asymmetric impacts of individual investor sentiment on the time-varying risk-return relation in stock market," International Review of Economics & Finance, Elsevier, vol. 78(C), pages 177-194.
    13. Xu, Hai-Chuan & Zhou, Wei-Xing, 2018. "A weekly sentiment index and the cross-section of stock returns," Finance Research Letters, Elsevier, vol. 27(C), pages 135-139.
    14. Changyun Wang, 2003. "Investor sentiment, market timing, and futures returns," Applied Financial Economics, Taylor & Francis Journals, vol. 13(12), pages 891-898.
    15. Fasanya, Ismail O. & Awodimila, Crystal P., 2020. "Are commodity prices good predictors of inflation? The African perspective," Resources Policy, Elsevier, vol. 69(C).
    16. Zachary McGurk & Adam Nowak & Joshua C. Hall, 2020. "Stock returns and investor sentiment: textual analysis and social media," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 44(3), pages 458-485, July.
    17. Yang, Cai & Gong, Xu & Zhang, Hongwei, 2019. "Volatility forecasting of crude oil futures: The role of investor sentiment and leverage effect," Resources Policy, Elsevier, vol. 61(C), pages 548-563.
    18. Yang, Chunpeng & Zhou, Liyun, 2015. "Investor trading behavior, investor sentiment and asset prices," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 42-62.
    19. Zhifang He & Fangzhao Zhou & Xiaohua Xia & Fenghua Wen & Yiyuan Huang, 2019. "Interaction between Oil Price and Investor Sentiment: Nonlinear Causality, Time- Varying Influence, and Asymmetric Effect," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(12), pages 2756-2773, September.
    20. Narayan, Paresh Kumar & Gupta, Rangan, 2015. "Has oil price predicted stock returns for over a century?," Energy Economics, Elsevier, vol. 48(C), pages 18-23.
    21. Akihiro Omura & Neda Todorova, 2019. "The quantile dependence of commodity futures markets on news sentiment," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(7), pages 818-837, July.
    22. Steven J. Nooijen & Simon A. Broda, 2016. "Predicting Equity Markets with Digital Online Media Sentiment: Evidence from Markov-switching Models," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 17(4), pages 321-335, October.
    23. Daskalaki, Charoula & Kostakis, Alexandros & Skiadopoulos, George, 2014. "Are there common factors in individual commodity futures returns?," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 346-363.
    24. Smales, Lee A., 2015. "Asymmetric volatility response to news sentiment in gold futures," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 161-172.
    25. Radetzki, Marian, 2006. "The anatomy of three commodity booms," Resources Policy, Elsevier, vol. 31(1), pages 56-64, March.
    26. Salisu, Afees A. & Isah, Kazeem O., 2018. "Predicting US inflation: Evidence from a new approach," Economic Modelling, Elsevier, vol. 71(C), pages 134-158.
    27. Robert I. Webb & David P. Simon & Roy A. Wiggins III, 2001. "S&P futures returns and contrary sentiment indicators," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(5), pages 447-462, May.
    28. Ismail Fasanya & Oluwatomisin Oyewole, 2021. "Infectious Diseases-Energy Futures Nexus - A Quantile-on-Quantile Approach," Energy RESEARCH LETTERS, Asia-Pacific Applied Economics Association, vol. 1(1), pages 1-4.
    29. Ismail O. Fasanya & Oluwatomisin J. Oyewole & Johnson A. Oliyide, 2021. "Can Uncertainty Due to Pandemic Predict Asia-Pacific Energy Stock Markets?," Asian Economics Letters, Asia-Pacific Applied Economics Association, vol. 2(1), pages 1-7.
    30. Lutz Kilian & Bruce Hicks, 2013. "Did Unexpectedly Strong Economic Growth Cause the Oil Price Shock of 2003–2008?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 385-394, August.
    31. Maghyereh, Aktham & Abdoh, Hussein, 2020. "The tail dependence structure between investor sentiment and commodity markets," Resources Policy, Elsevier, vol. 68(C).
    32. Belousova, Julia & Dorfleitner, Gregor, 2012. "On the diversification benefits of commodities from the perspective of euro investors," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2455-2472.
    33. Ismail Olaleke Fasanya, 2022. "Pandemic uncertainty and sectoral stock returns predictability in South Africa," African Journal of Economic and Management Studies, Emerald Group Publishing Limited, vol. 14(1), pages 53-69, August.
    34. Ji, Qiang & Li, Jianping & Sun, Xiaolei, 2019. "Measuring the interdependence between investor sentiment and crude oil returns: New evidence from the CFTC's disaggregated reports," Finance Research Letters, Elsevier, vol. 30(C), pages 420-425.
    35. Baruník, Jozef & Kočenda, Evžen & Vácha, Lukáš, 2016. "Gold, oil, and stocks: Dynamic correlations," International Review of Economics & Finance, Elsevier, vol. 42(C), pages 186-201.
    36. Ding Du & Xiaobing Zhao, 2017. "Financial investor sentiment and the boom/bust in oil prices during 2003–2008," Review of Quantitative Finance and Accounting, Springer, vol. 48(2), pages 331-361, February.
    37. Susan Sunila Sharma, 2019. "WHICH VARIABLES PREDICT INDONESIA’s INFLATION?," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 22(1), pages 1-16.
    38. Stoll, Hans R. & Whaley, Robert E., 1990. "The Dynamics of Stock Index and Stock Index Futures Returns," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 25(4), pages 441-468, December.
    39. Kang, Sang Hoon & McIver, Ron & Yoon, Seong-Min, 2017. "Dynamic spillover effects among crude oil, precious metal, and agricultural commodity futures markets," Energy Economics, Elsevier, vol. 62(C), pages 19-32.
    40. Sercan Demiralay & Nikolaos Hourvouliades & Athanasios Fassas, 2020. "Dynamic co-movements and directional spillovers among energy futures," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 37(4), pages 673-696, June.
    41. repec:eme:sef000:sef-09-2019-0374 is not listed on IDEAS
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wang, Lu & Ma, Feng & Niu, Tianjiao & Liang, Chao, 2021. "The importance of extreme shock: Examining the effect of investor sentiment on the crude oil futures market," Energy Economics, Elsevier, vol. 99(C).
    2. He, Zhifang, 2020. "Dynamic impacts of crude oil price on Chinese investor sentiment: Nonlinear causality and time-varying effect," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 131-153.
    3. Atri, Hanen & Kouki, Saoussen & Gallali, Mohamed imen, 2021. "The impact of COVID-19 news, panic and media coverage on the oil and gold prices: An ARDL approach," Resources Policy, Elsevier, vol. 72(C).
    4. Chen, Rongda & Bao, Weiwei & Jin, Chenglu, 2021. "Investor sentiment and predictability for volatility on energy futures Markets: Evidence from China," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 112-129.
    5. Yousaf, Imran & Youssef, Manel & Goodell, John W., 2022. "Quantile connectedness between sentiment and financial markets: Evidence from the S&P 500 twitter sentiment index," International Review of Financial Analysis, Elsevier, vol. 83(C).
    6. Chen, Qitong & Zhu, Huiming & Yu, Dongwei & Hau, Liya, 2022. "How does investor attention matter for crude oil prices and returns? Evidence from time-frequency quantile causality analysis," The North American Journal of Economics and Finance, Elsevier, vol. 59(C).
    7. Chen, Rongda & Wang, Shengnan & Ye, Mengya & Jin, Chenglu & Ren, He & Chen, Shu, 2022. "Cross-Market Investor Sentiment of Energy Futures and Return Comovements," Finance Research Letters, Elsevier, vol. 49(C).
    8. Akyildirim, Erdinc & Cepni, Oguzhan & Pham, Linh & Uddin, Gazi Salah, 2022. "How connected is the agricultural commodity market to the news-based investor sentiment?," Energy Economics, Elsevier, vol. 113(C).
    9. Maghyereh, Aktham & Awartani, Basel & Abdoh, Hussein, 2020. "The effects of investor emotions sentiments on crude oil returns: A time and frequency dynamics analysis," International Economics, Elsevier, vol. 162(C), pages 110-124.
    10. Gao, Bin & Liu, Xihua, 2020. "Intraday sentiment and market returns," International Review of Economics & Finance, Elsevier, vol. 69(C), pages 48-62.
    11. Zhou, Liyun & Huang, Jialiang, 2020. "Contagion of future-level sentiment in Chinese Agricultural Futures Markets," Pacific-Basin Finance Journal, Elsevier, vol. 61(C).
    12. Yue-Jun Zhang & Shu-Hui Li, 2019. "The impact of investor sentiment on crude oil market risks: evidence from the wavelet approach," Quantitative Finance, Taylor & Francis Journals, vol. 19(8), pages 1357-1371, August.
    13. Mbarki, Imen & Khan, Muhammad Arif & Karim, Sitara & Paltrinieri, Andrea & Lucey, Brian M., 2023. "Unveiling commodities-financial markets intersections from a bibliometric perspective," Resources Policy, Elsevier, vol. 83(C).
    14. Ma, Feng & Liu, Jing & Wahab, M.I.M. & Zhang, Yaojie, 2018. "Forecasting the aggregate oil price volatility in a data-rich environment," Economic Modelling, Elsevier, vol. 72(C), pages 320-332.
    15. Maghyereh, Aktham & Abdoh, Hussein, 2020. "The tail dependence structure between investor sentiment and commodity markets," Resources Policy, Elsevier, vol. 68(C).
    16. Devpura, Neluka & Narayan, Paresh Kumar & Sharma, Susan Sunila, 2019. "Structural instability and predictability," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 63(C).
    17. Sharma, Susan Sunila & Phan, Dinh Hoang Bach & Iyke, Bernard, 2019. "Do oil prices predict Indonesian macroeconomy?," Economic Modelling, Elsevier, vol. 82(C), pages 2-12.
    18. Zhifang He & Fangzhao Zhou, 2018. "Time-varying and asymmetric effects of the oil-specific demand shock on investor sentiment," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-18, August.
    19. Chen, Rongda & Wei, Bo & Jin, Chenglu & Liu, Jia, 2021. "Returns and volatilities of energy futures markets: Roles of speculative and hedging sentiments," International Review of Financial Analysis, Elsevier, vol. 76(C).
    20. Gao, Bin & Yang, Chunpeng, 2017. "Forecasting stock index futures returns with mixed-frequency sentiment," International Review of Economics & Finance, Elsevier, vol. 49(C), pages 69-83.

    More about this item

    Keywords

    Energy futures; Investors sentiment; Forecast evaluation; Asymmetries; Behavioural finance;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecofin:v:63:y:2022:i:c:s1062940822001656. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620163 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.