IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v47y2015icp121-128.html
   My bibliography  Save this article

Forecasting ability of the investor sentiment endurance index: The case of oil service stock returns and crude oil prices

Author

Listed:
  • He, Ling T.
  • Casey, K.M.

Abstract

Using a binomial probability distribution model this paper creates an endurance index of oil service investor sentiment. The index reflects the probability of the high or low stock price being the close price for the PHLX Oil Service Sector Index. Results of this study reveal the substantial forecasting ability of the sentiment endurance index. Monthly and quarterly rolling forecasts of returns of oil service stocks have an overall accuracy as high as 52% to 57%. In addition, the index shows decent forecasting ability on changes in crude oil prices, especially, WTI prices. The accuracy of 6-quarter rolling forecasts is 55%. The sentiment endurance index, along with the procedure of true forecasting and accuracy ratio, applied in this study provides investors and analysts of oil service sector stocks and crude oil prices as well as energy policy-makers with effective analytical tools.

Suggested Citation

  • He, Ling T. & Casey, K.M., 2015. "Forecasting ability of the investor sentiment endurance index: The case of oil service stock returns and crude oil prices," Energy Economics, Elsevier, vol. 47(C), pages 121-128.
    • Handle: RePEc:eee:eneeco:v:47:y:2015:i:c:p:121-128
    DOI: 10.1016/j.eneco.2014.11.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S014098831400276X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2014.11.005?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. 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.
    2. Ling T. He, 2012. "The investor sentiment endurance index and its forecasting ability," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 3(1), pages 61-70.
    3. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    4. De Long, J Bradford & Andrei Shleifer & Lawrence H. Summers & Robert J. Waldmann, 1990. "Noise Trader Risk in Financial Markets," Journal of Political Economy, University of Chicago Press, vol. 98(4), pages 703-738, August.
    5. Mark J. Kamstra & Lisa A. Kramer & Maurice D. Levi, 2003. "Winter Blues: A SAD Stock Market Cycle," American Economic Review, American Economic Association, vol. 93(1), pages 324-343, March.
    6. Swaminathan, Bhaskaran, 1996. "Time-Varying Expected Small Firm Returns and Closed-End Fund Discounts," Review of Financial Studies, Society for Financial Studies, vol. 9(3), pages 845-887.
    7. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    8. Neal, Robert & Wheatley, Simon M., 1998. "Do Measures of Investor Sentiment Predict Returns?," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 33(4), pages 523-547, December.
    9. Changyun Wang, 2001. "Investor Sentiment and Return Predictability in Agricultural Futures Markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(10), pages 929-952, October.
    10. Fama, Eugene F & French, Kenneth R, 1996. "Multifactor Explanations of Asset Pricing Anomalies," Journal of Finance, American Finance Association, vol. 51(1), pages 55-84, March.
    11. Daniel, Kent & Titman, Sheridan, 1997. "Evidence on the Characteristics of Cross Sectional Variation in Stock Returns," Journal of Finance, American Finance Association, vol. 52(1), pages 1-33, March.
    12. Michael Lemmon & Evgenia Portniaguina, 2006. "Consumer Confidence and Asset Prices: Some Empirical Evidence," Review of Financial Studies, Society for Financial Studies, vol. 19(4), pages 1499-1529.
    13. Gregory W. Brown & Michael T. Cliff, 2005. "Investor Sentiment and Asset Valuation," The Journal of Business, University of Chicago Press, vol. 78(2), pages 405-440, March.
    14. Mustafa Sayim & Pamela D. Morris & Hamid Rahman, 2013. "The effect of US individual investor sentiment on industry‐specific stock returns and volatility," Review of Behavioral Finance, Emerald Group Publishing Limited, vol. 5(1), pages 58-76, September.
    15. Fama, Eugene F. & French, Kenneth R., 1997. "Industry costs of equity," Journal of Financial Economics, Elsevier, vol. 43(2), pages 153-193, February.
    16. Jose A. Scheinkman & Wei Xiong, 2003. "Overconfidence and Speculative Bubbles," Journal of Political Economy, University of Chicago Press, vol. 111(6), pages 1183-1219, December.
    17. Fama, Eugene F. & French, Kenneth R., 1993. "Common risk factors in the returns on stocks and bonds," Journal of Financial Economics, Elsevier, vol. 33(1), pages 3-56, February.
    18. Brown, Gregory W. & Cliff, Michael T., 2004. "Investor sentiment and the near-term stock market," Journal of Empirical Finance, Elsevier, vol. 11(1), pages 1-27, January.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Jiang, Zhe & Zhang, Lin & Zhang, Lingling & Wen, Bo, 2022. "Investor sentiment and machine learning: Predicting the price of China's crude oil futures market," Energy, Elsevier, vol. 247(C).
    3. Duangnate, Kannika & Mjelde, James W., 2017. "Comparison of data-rich and small-scale data time series models generating probabilistic forecasts: An application to U.S. natural gas gross withdrawals," Energy Economics, Elsevier, vol. 65(C), pages 411-423.
    4. Yajie Qi & Huajiao Li & Sui Guo & Sida Feng, 2019. "Dynamic Transmission of Correlation between Investor Attention and Stock Price: Evidence from China’s Energy Industry Typical Stocks," Complexity, Hindawi, vol. 2019, pages 1-15, December.
    5. Jiang, He & Hu, Weiqiang & Xiao, Ling & Dong, Yao, 2022. "A decomposition ensemble based deep learning approach for crude oil price forecasting," Resources Policy, Elsevier, vol. 78(C).
    6. Ouyang, Zi-sheng & Liu, Meng-tian & Huang, Su-su & Yao, Ting, 2022. "Does the source of oil price shocks matter for the systemic risk?," Energy Economics, Elsevier, vol. 109(C).
    7. 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.

    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. Corredor, Pilar & Ferrer, Elena & Santamaria, Rafael, 2013. "Investor sentiment effect in stock markets: Stock characteristics or country-specific factors?," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 572-591.
    2. Sayim, Mustafa & Rahman, Hamid, 2015. "An examination of U.S. institutional and individual investor sentiment effect on the Turkish stock market," Global Finance Journal, Elsevier, vol. 26(C), pages 1-17.
    3. David C. Ling & Andy Naranjo & Benjamin Scheick, 2014. "Investor Sentiment, Limits to Arbitrage and Private Market Returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(3), pages 531-577, September.
    4. Tiwari, Aviral Kumar & Abakah, Emmanuel Joel Aikins & Bonsu, Christiana Osei & Karikari, Nana Kwasi & Hammoudeh, Shawkat, 2022. "The effects of public sentiments and feelings on stock market behavior: Evidence from Australia," Journal of Economic Behavior & Organization, Elsevier, vol. 193(C), pages 443-472.
    5. Yiannis Karavias & Stella Spilioti & Elias Tzavalis, 2021. "Investor sentiment effects on share price deviations from their intrinsic values based on accounting fundamentals," Review of Quantitative Finance and Accounting, Springer, vol. 56(4), pages 1593-1621, May.
    6. Malcolm Baker & Jeffrey Wurgler, 2007. "Investor Sentiment in the Stock Market," Journal of Economic Perspectives, American Economic Association, vol. 21(2), pages 129-152, Spring.
    7. Seok, Sang Ik & Cho, Hoon & Ryu, Doojin, 2019. "Firm-specific investor sentiment and daily stock returns," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    8. Corredor, Pilar & Ferrer, Elena & Santamaria, Rafael, 2014. "Is cognitive bias really present in analyst forecasts? The role of investor sentiment," International Business Review, Elsevier, vol. 23(4), pages 824-837.
    9. Shen, Junyan & Yu, Jianfeng & Zhao, Shen, 2017. "Investor sentiment and economic forces," Journal of Monetary Economics, Elsevier, vol. 86(C), pages 1-21.
    10. Stambaugh, Robert F. & Yu, Jianfeng & Yuan, Yu, 2012. "The short of it: Investor sentiment and anomalies," Journal of Financial Economics, Elsevier, vol. 104(2), pages 288-302.
    11. Muhammad Zia Ur Rehman & Zain ul Abidin & Faisal Rizwan & Zaheer Abbas & Sajjad Ahmad Baig, 2017. "How investor sentiments spillover from developed countries to developing countries?," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1309096-130, January.
    12. Kim Kaivanto & Peng Zhang, 2019. "Investor Sentiment as a Predictor of Market Returns," Working Papers 268005798, Lancaster University Management School, Economics Department.
    13. Hou, Yang & Meng, Jiayin, 2018. "The momentum effect in the Chinese market and its relationship with the simultaneous and the lagged investor sentiment," MPRA Paper 94838, University Library of Munich, Germany.
    14. Al-Nasseri, Alya & Menla Ali, Faek & Tucker, Allan, 2021. "Investor sentiment and the dispersion of stock returns: Evidence based on the social network of investors," International Review of Financial Analysis, Elsevier, vol. 78(C).
    15. Utku Uygur & Oktay Taş, 2014. "The impacts of investor sentiment on returns and conditional volatility of international stock markets," Quality & Quantity: International Journal of Methodology, Springer, vol. 48(3), pages 1165-1179, May.
    16. Ramiah, Vikash & Xu, Xiaoming & Moosa, Imad A., 2015. "Neoclassical finance, behavioral finance and noise traders: A review and assessment of the literature," International Review of Financial Analysis, Elsevier, vol. 41(C), pages 89-100.
    17. Yang, Yan & Copeland, Laurence, 2014. "The Effects of Sentiment on Market Return and Volatility and The Cross-Sectional Risk Premium of Sentiment-affected Volatility," Cardiff Economics Working Papers E2014/12, Cardiff University, Cardiff Business School, Economics Section.
    18. Li, Xiao & Shen, Dehua & Xue, Mei & Zhang, Wei, 2017. "Daily happiness and stock returns: The case of Chinese company listed in the United States," Economic Modelling, Elsevier, vol. 64(C), pages 496-501.
    19. Rakovská, Zuzana, 2021. "Composite survey sentiment as a predictor of future market returns: Evidence for German equity indices," International Review of Economics & Finance, Elsevier, vol. 73(C), pages 473-495.
    20. Mahmoudi, Nader & Docherty, Paul & Melia, Adrian, 2022. "Firm-level investor sentiment and corporate announcement returns," Journal of Banking & Finance, Elsevier, vol. 144(C).

    More about this item

    Keywords

    Endurance index of oil service investor sentiment; Forecasting ability; Rolling forecast; Accuracy ratio;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation
    • M21 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - Business Economics

    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:eneeco:v:47:y:2015:i:c:p:121-128. 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/eneco .

    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.