Author

  • Semen Son Turan

    • MEF University, Istanbul, Turkey
    • Türkiye

Abstract

This study analyzes the relationship of the volatility ofstock returns and internet search volume (ISV). The dataset consists of 10 Turkish companies listed on the BIST-100 Index of Borsa Istanbul, and encompasses the period between January 2004 - September 2013. The GARCH (1,1) model is applied with two alternative mean specifications. The use of the novel exogenous variable ISV as proxy for investor sentimentis complemented through the inclusion of trading volume.Results show that as the GARCH (1,1) model becomes increasingly nested, volatility persistence declines with however no case of a vanishing G(ARCH) effect.

Keywords

References

  • Baklaci, H. F., Tunc, G.., Aydogan, B. & Vardar, G. (2011). The Impact of Firm-Specific Public News on Intraday Market Dynamics: Evidence from the Turkish Stock Market. Emerging Markets Finance and Trade , 47(6), 99-119.
  • Askitas, N. & Zimmermann, K. (2009). Google econometrics and unemployment forecasting. Applied Economics Quarterly, Duncker & Humblot, Berlin, 55(2), 107-120.
  • Bank, M., Larch, M. & Peter, G. (2011). Google search volume and its influence on liquidity and returns of German stocks. Financial markets and portfolio management , 25(3), 239-264.
  • Barber, B. M. & Odean, T. (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.
  • Barberis, N., Shleifer, A. & Vishny, R. (1998). A model of investor sentiment. Journal of Financial Economics , 49(3), 307-343.
  • Bordino, I., Battiston, S., Caldarelli, G., Cristelli, M., Ukkonen, A. & Weber, I. (2012). Web search queries can predict stock market volumes. PloS one , 7(7), e40014.
  • Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics , 31(3), 307-327.
  • Bollerslev, T. & Wooldridge, J. M. (1992). Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances. Econometric reviews , 11(2), 143-172.
  • Black, F. (1986). Noise. The Journal of Finance , 41(3), 529-543.
  • Clark, P. K. (1973). A subordinated stochastic process model with finite variance for speculative prices. Econometrica , 41, 135–156.
  • Da, Z., Engelberg, J. & Gao, P. (2011). In search of attention. The Journal of Finance , 66(5), 1461-1499.
  • Daniel, K. D., Hirshleifer, D. & Subrahmanyam, A. (2001). Overconfidence, arbitrage, and equilibrium asset pricing. The Journal of Finance , 56(3), 921-965.
  • DeLong, J. B., Shleifer, A., Summers, L. H. & Waldmann, R. J. (1990). Positive feedback investment strategies and destabilizing rational speculation. The Journal of Finance , 45(2), 379-395.
  • Dimpfl, T. & Jank, S. (2011). Can internet search queries help to predict stock market volatility? (No. 11-15). CFR Working Paper .
  • Engle, R. F. (1982). Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation. Econometrica: Journal of the Econometric Society , 3, 987-1007.
  • Epps, T. W. & Epps, M. L. (1976). The stochastic dependence of security price changes and transaction volumes: implications for the mixture of distributions hypothesis. Econometrica, 44(2), 305-321
  • Fama, E. F. (1965). The behavior of stock-market prices. The Journal of Business , 38(1), 34-105.
  • Fama, E. F., Fisher, L., Jensen, M. C. & Roll, R. (1969). The adjustment of stock prices to new information. International Economic Review , 10(1), 1-21
  • Festinger, L., Riecken, H. W. & Schachter, S. (1956). When prophecy fails. Minneapolis: University of Minnesota Press.
  • Fleming, J., Kirby, C. & Ostdiek, B. (2004). Stochastic volatility, trading volume, and the daily flow of information. Rice University, Jones Graduate School Working Paper.
  • Foucault, T., Sraer, D. & Thesmar, D. J. (2011). Individual investors and volatility. The Journal of Finance , 66(4), 1369-1406.
  • Grossman, S. J. & Stiglitz, J. E. (1980). On the impossibility of informationally efficient markets. The American Economic Review , 4, 393-408.
  • Gursoy, G., Yuksel, A. & Yuksel, A. (2008). Trading volume and stock market volatility: evidence from emerging stock markets. Investment Management and Financial Innovations , 5(4), 200-210.
  • Daniel, K., Hirshleifer, D. & Subrahmanyam, A. (1998). Investor psychology and security market under-and overreactions. The Journal of Finance , 53(6), 1839-1885.
  • Jensen, M. C. (1968). The performance of mutual funds in the period 1945–1964. The Journal of Finance , 23(2), 389-416.
  • Joseph, K., Babajide-Wintoki, M. & Zhang, Z. (2011). Forecasting abnormal stock returns and trading volume using investor sentiment: Evidence from online search. International Journal of Forecasting , 27(4), 1116-1127.
  • Kahneman, D. & Tversky, A. (1973). On the psychology of prediction. Psychological review , 80(4), 237.
  • Kahneman, D. & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica: Journal of the Econometric Society , 3, 263-291.
  • Keynes, J. M. (1937). The general theory of employment. The Quarterly Journal of Economics , 51(2), 209223.
  • Kyle, A. S. (1985). Continuous auctions and insider trading. Econometrica: Journal of the Econometric Society , 3, 1315-1335.
  • Lamoureux, C. G. & Lastrapes, W. D. (1990). Heteroskedasticity in stock return data: Volume versus GARCH effects. TheJournal of Finance , 45, 221–229.
  • Latoeiro, P., Ramos, S. B. & Veiga, H. (2013). Predictability of stock market activity using Google search queries. Working Paper 13-06. Universidad Carlos III de Madrid.
  • LeRoy, S. F. (1973). Risk aversion and the martingale property of stock prices. International Economic Review , 5, 436-446.
  • LeRoy, S. F. & Porter, R. D. (1981). The present-value relation: Tests based on implied variance bounds. Econometrica: Journal of the Econometric Society , 4, 555-574.
  • Mandelbrot, B. (1963). The variation of certain speculative prices. J ournal of Business , 36, 394-419.
  • March, J. G. & Simon, H. A. (1958). Organizations. Wiley.
  • Markowitz, H. (1952). Portfolio selection*. The Journal of Finance , 7(1), 77-91.
  • Markowitz, H. (1959). Portfolio selection: Efficient diversificationof investments. Wiley, New York .
  • Omran, M. F. & McKenzie, E. (2000). Heteroscedasticity in stock returns data revisited: volume versus GARCH effects. Applied Financial Economics , 10(5), 553-560.
  • Roll, R. (1977). A critique of the asset pricing theory's tests Part I: On past and potential testability of the theory. Journal of Financial Economics , 4(2), 129-176.
  • Samuelson, P. A. (1963). Risk and uncertainty-a fallacy of large numbers. Scientia , 98(612), 108.
  • Shefrin, H. (2000). Börsenerfolg mit behavioral finance. Schäffer-Pöschel.
  • Shiller, R. J. (1981). The Use of Volatility Measures in Assessing Market Efficiency. The Journal of Finance , 36(2), 291-304.
  • Shiller, R. J. (2000). Measuring bubble expectations and investor confidence. The Journal of Psychology and Financial Markets , 1(1), 49-60.
  • Schwert, G. W. (1989). Why does stock market volatility change over time? The journal of finance , 44(5), 1115-1153.
  • Simon, H. A. (1955). A behavioral model of rational choice. The Quarterly Journal of Economics , 69(1), 99118.
  • Tauchen, G. E. & Pitts, M. (1983). The price variability-volume relationship on speculative markets. Econometrica: Journal of the Econometric Society , 4, 485-505.
  • Tversky, A. & Kahneman, D. (1973). Availability: A heuristic for judging frequency and probability. Cognitive Psychology , 5(2), 207-232.
  • Vlastakis, N. & Markellos, R. N. (2012). Information demand and stock market volatility. Journal of Banking & Finance , 36(6), 1808-1821.
  • Von Neumann, L. & Morgenstern, O. J. (1947). Theory of games and economic behavior . (2nd Ed.) Princeton: Princeton University Press.

Downloads

No downloads have been recorded for this article yet. Figures appear here once readers begin downloading the full text.

How to Cite

Turan, S. S. (2014). Internet Search Volume and Stock Return Volatility: The Case of Turkish Companies. Information Management and Business Review, 6(6), 317-328. https://doi.org/10.22610/imbr.v6i6.1130

Share this article

Section

Research Paper

Published

2014-12-30

Submissions

Have research to publish? Information Management and Business Review welcomes submissions.

Make a Submission