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Extracting Knowledge from Technical Reports for the Valuation of West Texas Intermediate Crude Oil Futures

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  • Joseph D. Prusa

    (Florida Atlantic University)

  • Ryan T. Sagul

    (Florida Atlantic University)

  • Taghi M. Khoshgoftaar

    (Florida Atlantic University)

Abstract

This paper proposes and demonstrates an approach for the often-attempted problem of market prediction, framed as classification task. We restrict our study to a widely purchased and well recognized commodity, West Texas Intermediate crude oil, which experiences significant volatility. For this purpose, nine learners using features extracted from monthly International Energy Agency (IEA) reports to predict undervalued, overvalued, and accurate valuation of the oil futures between 2003 and 2015. The often touted “Efficient Market Hypothesis” (EMH) suggests that it is impossible for individual investors to “beat the market” as market and external forces, such as geopolitical crises and natural disasters, are nearly impossible to predict. However, four algorithms were statistically better at the 95% confidence interval than “Zero-Rule” and “Random-Guess” strategies which are expected to pseudo-reflect the EMH. Furthermore, the addition of text features can significantly improve performance compared to only using price history from the oil futures data, challenging the validity of the semi-strong versions of the EMH in the crude oil market.

Suggested Citation

  • Joseph D. Prusa & Ryan T. Sagul & Taghi M. Khoshgoftaar, 2019. "Extracting Knowledge from Technical Reports for the Valuation of West Texas Intermediate Crude Oil Futures," Information Systems Frontiers, Springer, vol. 21(1), pages 109-123, February.
    • Handle: RePEc:spr:infosf:v:21:y:2019:i:1:d:10.1007_s10796-018-9859-2
    DOI: 10.1007/s10796-018-9859-2
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    1. Michael C. Jensen, 1968. "The Performance Of Mutual Funds In The Period 1945–1964," Journal of Finance, American Finance Association, vol. 23(2), pages 389-416, May.
    2. Graham, John R. & Harvey, Campbell R., 1996. "Market timing ability and volatility implied in investment newsletters' asset allocation recommendations," Journal of Financial Economics, Elsevier, vol. 42(3), pages 397-421, November.
    3. Kenneth A. Froot & Jeffrey A. Frankel, 1989. "Forward Discount Bias: Is it an Exchange Risk Premium?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 104(1), pages 139-161.
    4. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    5. Zhang, Jin-Liang & Zhang, Yue-Jun & Zhang, Lu, 2015. "A novel hybrid method for crude oil price forecasting," Energy Economics, Elsevier, vol. 49(C), pages 649-659.
    6. Burton G. Malkiel, 2005. "Reflections on the Efficient Market Hypothesis: 30 Years Later," The Financial Review, Eastern Finance Association, vol. 40(1), pages 1-9, February.
    7. Kaufmann, Robert K. & Ullman, Ben, 2009. "Oil prices, speculation, and fundamentals: Interpreting causal relations among spot and futures prices," Energy Economics, Elsevier, vol. 31(4), pages 550-558, July.
    8. Choi, Kyongwook & Hammoudeh, Shawkat, 2010. "Volatility behavior of oil, industrial commodity and stock markets in a regime-switching environment," Energy Policy, Elsevier, vol. 38(8), pages 4388-4399, August.
    9. Sun, Andrew & Lachanski, Michael & Fabozzi, Frank J., 2016. "Trade the tweet: Social media text mining and sparse matrix factorization for stock market prediction," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 272-281.
    10. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    11. David Laibson, 1997. "Golden Eggs and Hyperbolic Discounting," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 112(2), pages 443-478.
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    Cited by:

    1. Marcus Vinicius Santos & Fernando Morgado-Dias & Thiago C. Silva, 2023. "Oil Sector and Sentiment Analysis—A Review," Energies, MDPI, vol. 16(12), pages 1-29, June.
    2. Benjamin Clapham & Michael Siering & Peter Gomber, 2021. "Popular News Are Relevant News! How Investor Attention Affects Algorithmic Decision-Making and Decision Support in Financial Markets," Information Systems Frontiers, Springer, vol. 23(2), pages 477-494, April.

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