RT Report
T1 An entropy based analysis of the relationship between the DOW JONES Index and the TRNA Sentiment series
A1 Allen, David E.
A1 McAleer, Michael
A1 Singh, Abhay K.
AB This paper features an analysis of the relationship between the DOW JONES Industrial Average Index (DJIA) and a sentiment news series using daily data obtained from the Thomson Reuters News Analytics (TRNA)1 provided by SIRCA (The Securities Industry Research Centre of the Asia Pacic). The recent growth in the availability of on-line financial news sources such as internet news and social media sources provides instantaneous access to financial news. Various commercial agencies have started developing their own filtered financial news feeds which are used by investors and traders to support their algorithmic trading strategies. Thomson Reuters News Analytics (TRNA)2 is one such data set. In this study we use the TRNA data set to construct a series of daily sentiment scores for Dow Jones Industrial Average (DJIA) stock index component companies. We use these daily DJIA market sentiment scores to study the relationship between financial news sentiment scores and the stock prices of these companies using entropy measures. The entropy and Mutual Information (MI) statistics permit an analysis of the amount of information within the sentiment series, its relationship to the DJIA and an indication of how the relationship changes over time.
PB Facultad de Ciencias Económicas y Empresariales. Instituto Complutense de Análisis Económico (ICAE)
SN 2341-2356
YR 2017
FD 2017
LK https://hdl.handle.net/20.500.14352/22873
UL https://hdl.handle.net/20.500.14352/22873
LA eng
NO Allen, D.E., M. McAleer and A.K. Singh, (2015) “Machine News and Volatility: The Dow Jones Industrial Average and the TRNA Real-Time High Frequency Sentiment Series”, published as chapter 19 in, Hand book of High Frequency Trading, Ed. G. Gregoriou, Academic Press, Elsevier, ISBN: 978-0-12-802205-4, pp. 327-344.Allen, D. E., M. McAleer, and A.K. Singh (2014) “Daily Market News Sentiment and Stock Prices”, Tinbergen Institute Discussion Paper, TI 2015-090/III.Barber, B. M., and T. Odean (2008) “All that glitters: The effect of attention and news on the buying behavior of individual and institutional investors”. Review of Financial Studies, 21 (2), 785-818.Bera, A.K. and S. Y. Park (2008) “Optimal Portfolio Diversification Using the Maximum Entropy Principle”, Econometric Reviews, 27:4-6, 484-512.Borovkova, S., and D. Mahakena (2013) “News, Volatility and Jumps: The Case of Natural Gas Futures”. Working Paper. Retrieved From : http://ssrn.com/abstract=2334226.Chaitin, G. J. (1969) "On the Simplicity and Speed of Programs for Computing Infinite Sets of Natural Numbers", Journal of the ACM 16 (3): 407.Chao,A., and T. J. Shen (2003) “Nonparametric estimation of Shannon's index of diversity when there are unseen species”, Environ. Ecol. Stat., 10:429_443, 2003.Ebrahimi, N., E. Maasoumi, E. Soofi (1999) Journal of Econometrics, 90, 2, 317-336.Golan, A. (2002) "Information and Entropy Econometrics - Editor's view," Journal of Econometrics, 107, 1-2 (2002), 1-15.Golan. A., and E. Maasoumi (2008) “Information Theoretic and Entropy Methods: An Overview”, Econometric Reviews, 27:4-6,317-328.Granger, C., E. Maasoumi, and J. Racine (2004) “A dependence metric for possibly nonlinear time series”, Journal of Time Series Analysis 25(5), 649-669.Groÿ-Kluÿmann, A., and N. Hautsch (2011) “When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions”. Journal of Empirical Finance, 18 (2), 321-340.Hayfield,T., and J.S. Racine (2008) “Nonparametric Econometrics: The np Package”, Journal of Statistical Software, 27,5, 1-32.Hausser, J., and K. Strimmer (2012) Package 'entropy', Repository CRAN, http://www.r-project.org/.Hausser, J., and K. Strimmer (2009)  “Entropy Inference and the James-Stein Estimator, with Application to Nonlinear Gene Association Networks”, Journal of Machine Learning Research, 10,1469-1484.Holste, D., I. Groÿe, and H. Herzel (1998) “Bayes' estimators of generalized entropies”, J. Phys. A: Math. Gen., 31:2551_2566.Huskaj, B. (2009) “A value-at-risk analysis of VIX futures: Long memory, heavy tails, and asymmetry”. Available at SSRN: http://ssrn.com/abstract=1495229.Huynh, T. D., and D.R. Smith (2013). News Sentiment and Momentum.FIRN Research Paper.Jaynes, E.T., (1957) “Information Theory and Statistical Mechanics. II,” Physical. Review, 108, 2, 171-190.Jaynes, E. T. (2003) Probability Theory: The Logic of Science. Cambridge University Press, ISBN 0-521- 59271-2.Jeffreys, H., (1946) “An invariant form for the prior probability in estimation problems,” Proc. Royal. Society (Lond.) A,186:453-461.Kolmogorov, A.N. (1965) "Three Approaches to the Quantitative Definition of Information", Problems Inform. Transmission 1 (1):1-7.Kolmogorov, A.N. and V. A. Uspensky (1987) “Algorithms and randomness”, SIAM J. Theory of Probability and Its Applications,vol. 32 389-412.Krichevsky, R.E., and V. K. Trofimov (1981) “The performance of universal encoding”. IEEE Trans. Inf. Theory, 27:199_207.Leinweber, D., and J. Sisk (2011) Relating news analytics to stock returns The Handbook of News Analytics in Finance (pp. 147-172): John Wiley & Sons, Ltd.Maasoumi, E. (1993) “A Compendium to Information Theory in Economics and Econometrics”, Econometric Reviews, , 12, 2, 137-181.Maasoumi, E., and Racine (2002) “Entropy and Predictability of Stock Market Returns,” Journal of Econometrics, 107(2), 291_312.Miller, G.A. (1955) “Note on the bias of information estimates”, In H. Quastler, editor, Information Theory in Psychology II-B, pages 95-100. Free Press, Glencoe, IL.Mitra, L., Mitra, G., and D. diBartolomeo (2009) Equity portfolio risk (volatility) estimation using market information and sentiment. Quantitative Finance, 9 (8), 887-895.National Science Foundation, Report of the National Science Foundation Workshop on Information Theory and Computer Science Interface, Workshop, October 17-18, 2003 Chicago, Illinois.Perks W., (1947) “Some observations on inverse probability including a new indifference rule”, J. Inst. Actuaries, 73:285-334.Pincus, S. (2008) “Approximate Entropy as an Irregularity Measure for Financial Data”, Econometric Reviews, 27:4-6, 329-362.Racine, J.S. (2008) “Nonparametric Econometrics: A Primer”, Foundations and Trends in Econometrics, 3, 1, 1-88 [34] Shannon, C.E. (1948) “A Mathematical Theory of Communication”, The Bell System Technical Journal, Vol. 27, pp. 379-423,623-656.Schürmann, T., and P. Grassberger (1996) “Entropy estimation of symbol sequences”, Chaos, 6:414_427.Sinha, N. (2011) Underreaction to news in the US stock market. Working Paper. Retrieved From: http://ssrn.com/abstract=1572614.Sims, C.A. (2005) “Rational Inattention: A Research Agenda”, Deutsche Bundesbank Discussion Paper Series 1: Economic Studies No 34/2005.Smales, L. A. (2013). News Sentiment in the Gold Futures Market. Working Paper, Curtin University of Techonology.Soofi, E.. (1997) “Information Theoretic Regression Methods”. In: Advances in Econometrics - Applying Maximum Entropy to Econometric Problems, Fomby, T. and R. Carter Hill eds. Vol. 12. Jai Press Inc., London.Solomonoff, R. (1960) "A Preliminary Report on a General Theory of Inductive Inference", Report V-131 (Cambridge, Ma.: Zator Co.). revision, Nov., 1960.Storkenmaier, A., Wagener, M., and C. Weinhardt (2012) “Public information in fragmented markets”. Financial Markets and Portfolio Management, 26 (2), 179-215.Tetlock, P.C. (2007) “Giving content to investor sentiment: the role of media in the stock market”. Journal of Finance 62, 1139_1167.Tetlock, P.C. (2010) “Does public financial news resolve asymmetric information?” Review of Financial Studies 23, 3520_3557.Tetlock, P.C., Macskassy, S.A., and M. Saar-Tsechansky (2008) “More than words: quantifying language to measure firms' fundamentals “. Journal of Finance 63, 1427-1467.Thode Jr., H.C. (2002) Testing for Normality, Marcel Dekker, New York.Trybula, S. (1958) “Some problems of simultaneous Minimax Estimation”, Ann. Math. Statist. 29, 245-253.
DS Docta Complutense
RD 27 abr 2024