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New Evidence of Psychological Barrier from the Oil Market

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  • Paresh Kumar Narayan
  • Kumari Ranjeeni
  • Deepa Bannigidadmath

Abstract

The authors examine how stock returns were affected when the oil price reached the psychological barrier of US$100 per barrel for the first time in history. Using an event study approach, 4 key results emerge. First, the authors show that a psychological barrier event in the oil market does affect stock returns. Second, they show that a psychological barrier event in the oil market is a source of return drift—a phenomenon well explained and understood with respect to nonoil news events. Third, the psychological barrier affects small/medium-sized stocks and not large stocks. Last, the authors show that successful trading strategies can be devised based on the information that the oil price psychological barrier significantly impacts the market and that it contributes to return drift.

Suggested Citation

  • Paresh Kumar Narayan & Kumari Ranjeeni & Deepa Bannigidadmath, 2017. "New Evidence of Psychological Barrier from the Oil Market," Journal of Behavioral Finance, Taylor & Francis Journals, vol. 18(4), pages 457-469, October.
    • Handle: RePEc:taf:hbhfxx:v:18:y:2017:i:4:p:457-469
    DOI: 10.1080/15427560.2017.1365235
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    Cited by:

    1. Huthaifa Sameeh Alqaralleh & Ahmad Al-Saraireh & Alessandra Canepa, 2021. "Energy Market Risk Management under Uncertainty: A VaR Based on Wavelet Approach," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 130-137.
    2. Batten, Jonathan A. & Kinateder, Harald & Szilagyi, Peter G. & Wagner, Niklas F., 2019. "Time-varying energy and stock market integration in Asia," Energy Economics, Elsevier, vol. 80(C), pages 777-792.
    3. Cong Chen & Changsheng Hu & Hongxing Yao, 2022. "Noise Trader Risk and Wealth Effect: A Theoretical Framework," Mathematics, MDPI, vol. 10(20), pages 1-18, October.
    4. Szymon Lis, 2022. "Investor Sentiment in Asset Pricing Models: A Review," Working Papers 2022-14, Faculty of Economic Sciences, University of Warsaw.
    5. Yi, Yongsheng & Ma, Feng & Zhang, Yaojie & Huang, Dengshi, 2018. "Forecasting the prices of crude oil using the predictor, economic and combined constraints," Economic Modelling, Elsevier, vol. 75(C), pages 237-245.
    6. Sun, Yiguo & Li, Delong & Suo, Chenyi & Wang, Yu, 2023. "A threshold effect of COVID-19 risk on oil price returns," Energy Economics, Elsevier, vol. 120(C).
    7. Naidu, Dharmendra & Ranjeeni, Kumari, 2021. "Effect of coronavirus fear on the performance of Australian stock returns: Evidence from an event study," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    8. 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).
    9. Smyth, Russell & Narayan, Paresh Kumar, 2018. "What do we know about oil prices and stock returns?," International Review of Financial Analysis, Elsevier, vol. 57(C), pages 148-156.
    10. Chang, Chiu-Lan, 2024. "Extreme events, economic uncertainty and speculation on occurrences of price bubbles in crude oil futures," Energy Economics, Elsevier, vol. 130(C).
    11. Zhang, Yixing & Jia, Qinmin & Chen, Chen, 2021. "Risk attitude, financial literacy and household consumption: Evidence from stock market crash in China," Economic Modelling, Elsevier, vol. 94(C), pages 995-1006.
    12. Dranev, Yury & Frolova, Ksenia & Ochirova, Elena, 2019. "The impact of fintech M&A on stock returns," Research in International Business and Finance, Elsevier, vol. 48(C), pages 353-364.
    13. Qiu, Hua & Sha, Yezhou & Zhang, Yixing, 2024. "Energy affordability and subjective well-being in China: Causal inference, heterogeneity, and the mediating role of disaster risk," Energy Economics, Elsevier, vol. 129(C).
    14. Kais Tissaoui & Taha Zaghdoudi & Abdelaziz Hakimi & Ousama Ben-Salha & Lamia Ben Amor, 2022. "Does Uncertainty Forecast Crude Oil Volatility before and during the COVID-19 Outbreak? Fresh Evidence Using Machine Learning Models," Energies, MDPI, vol. 15(15), pages 1-20, August.
    15. Gu, Xin & Zhang, Weiqiang & Cheng, Sang, 2021. "How do investors in Chinese stock market react to external uncertainty? An event study to the Sino-US disputes," Pacific-Basin Finance Journal, Elsevier, vol. 68(C).
    16. Szymon Lis, 2024. "Investor Sentiment in Asset Pricing Models: A Review of Empirical Evidence," Papers 2411.13180, arXiv.org.
    17. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

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