Skip to main content
Log in

News sentiment to market impact and its feedback effect

  • Published:
Environment Systems and Decisions Aims and scope Submit manuscript

Abstract

Although market feedback on investor sentiment effect has been conceptually identified in the existing finance literature and investment strategies have been designed to explore this effect, there lacks systematic analysis in a quantified manner on such effect. Digitization of news articles and the advancement of computational intelligence applications have led to a growing influence of news sentiment over financial markets in recent years. News sentiment has often been used as a proxy for gauging investor sentiment and reflecting the aggregate confidence of the society toward future market. Previous studies have primarily focused on elucidating the unidirectional impact of news sentiment on market returns and not vice versa. In this study, we analyze more than 12 millions of news articles and document the presence of a significant feedback effect between news sentiment and market returns across the major indices in the US financial market. More specifically, we find that news sentiment exhibits a lag-5 effect on market returns and conversely market returns elicit consistent lag-1 effects on news sentiment. This aligns well with our intuition that news sentiment drives trading activity and investment decisions. In turn, heightened investment activity further stimulates involuntary responses, which manifest in the form of more news coverage and publications. The evidence presented highlights the strong correlation between news sentiment and market returns and demonstrates the benefits of advancing knowledge in data-driven modeling and its interaction with market movements.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Aboura S, Chevallier J (2013) Leverage versus feedback: Which Effect drives the oil market? Financ Res Lett 10(3):131–141

    Article  Google Scholar 

  • Antoniou A, Koutmos G, Pericli A (2005) Index futures and positive feedback trading: evidence from major stock exchanges. J Empir Financ 12(2):219–238. http://doi.org/10.1016/j.jempfin.2003.11.003

  • Arnold LG, Brunner S (2014) The economics of rational speculation in the presence of positive feedback trading. Q Rev Econ Financ 57:161–174. http://econpapers.repec.org/article/eeequaeco/v_3a57_3ay_3a2015_3ai_3ac_3ap_3a161-174.htm

    Article  Google Scholar 

  • Baccianella S, Esuli A, Sebastiani F (2010) SentiWordNet 3.0: an enhanced lexical resource for sentiment analysis and opinion mining. In: Calzolari N, Choukri K, Maegaard B, Mariani J, Odijk J, Piperidis S et al (eds), Proceedings of the seventh international conference on language resources and evaluation (LREC’10) (pp 2200–2204). European Language Resources Association (ELRA)

  • Chan WS (2003) Stock price reaction to news and no-news: drift and reversal after headlines. J Financ Econ 70(2):223–260. http://doi.org/10.1016/S0304-405X(03)00146-6

  • Chau F, Deesomsak R (2015) Business cycle variation in positive feedback trading: evidence from the G-7 economies. J Int Financ Mark, Inst Money 35:147–159

    Article  Google Scholar 

  • Hirshleifer D, Subrahmanyam A, Titman S (2006) Feedback and the success of irrational investors. J Financ Econ 81(2):311–338

    Article  Google Scholar 

  • Ho K-Y, Shi Y, Zhang Z (2013) How does news sentiment impact asset volatility? Evidence from long memory and regime-switching approaches. North Am J Econ Financ 26:436–456

    Article  Google Scholar 

  • Hou Y, Li S (2014) The impact of the CSI 300 stock index futures: positive feedback trading and autocorrelation of stock returns. Int Rev Econ Financ 33:319–337

    Article  Google Scholar 

  • İnkaya A, Yolcu Okur Y (2014) Analysis of volatility feedback and leverage effects on the ISE30 index using high frequency data. J Comput Appl Math 259:377–384

    Article  Google Scholar 

  • Johnson B (2010) Algorithmic trading & DMA: an introduction to direct access trading strategies. 4Myeloma Press, London, p 574

    Google Scholar 

  • Khanna N, Sonti R (2004) Value creating stock manipulation: feedback effect of stock prices on firm value. J Financ Mark 7(3):237–270

    Article  Google Scholar 

  • Laopodis NT (2005) Feedback trading and autocorrelation interactions in the foreign exchange market: further evidence. Econ Model 22(5):811–827

    Article  Google Scholar 

  • Li Q, Wang T, Li P, Liu L, Gong Q, Chen Y (2014a) The effect of news and public mood on stock movements. Inf Sci 278:826–840

    Article  Google Scholar 

  • Li X, Xie H, Chen L, Wang J, Deng X (2014b) News impact on stock price return via sentiment analysis. Knowl-Based Syst 69:14–23

    Article  Google Scholar 

  • Medhat W, Hassan A, Korashy H (2014) Sentiment analysis algorithms and applications: a survey. Ain Shams Eng J 5(4):1093–1113

    Article  Google Scholar 

  • Moreo A, Romero M, Castro JL, Zurita JM (2012) Lexicon-based comments-oriented news sentiment analyzer system. Expert Syst Appl 39(10):9166–9180

    Article  Google Scholar 

  • Salm CA, Schuppli M (2010) Positive feedback trading in stock index futures: international evidence. Int Rev Financ Anal 19(5):313–322

    Article  Google Scholar 

  • Schumaker RP, Chen H (2009) A quantitative stock prediction system based on financial news. Inf Process Manag 45(5):571–583

    Article  Google Scholar 

  • Schumaker RP, Zhang Y, Huang C-N, Chen H (2012) Evaluating sentiment in financial news articles. Decis Support Syst 53(3):458–464

    Article  Google Scholar 

  • Smales L (2014a) News sentiment and the investor fear gauge. Financ Res Lett, 11(2):122–130. http://doi.org/10.1016/j.frl.2013.07.003

  • Smales L (2014b) News sentiment in the gold futures market. J Bank Financ 49:275–286

    Article  Google Scholar 

  • Tetlock PC, Saar-Tsechansky M, MacKassy S (2008) More than words: quantifying language to measure firms’ fundamentals. J Financ 63(3):1437–1467

    Article  Google Scholar 

  • Wuthrich B, Cho V, Leung S, Permunetilleke D, Sankaran K, Zhang J (1998) Daily stock market forecast from textual web data. In: SMC’98 conference proceedings. 1998 IEEE international conference on systems, man, and cybernetics (Cat. No.98CH36218), vol 3. IEEE, pp 2720–2725

  • Yu L-C, Wu J-L, Chang P-C, Chu H-S (2013) Using a contextual entropy model to expand emotion words and their intensity for the sentiment classification of stock market news. Knowl-Based Syst, 41:89–97. http://doi.org/10.1016/j.knosys.2013.01.001

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Sheung Yin Kevin Mo, Anqi Liu or Steve Y. Yang.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Mo, S.Y.K., Liu, A. & Yang, S.Y. News sentiment to market impact and its feedback effect. Environ Syst Decis 36, 158–166 (2016). https://doi.org/10.1007/s10669-016-9590-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10669-016-9590-9

Keywords

Navigation