Price Discovery and Volatility: A theoretical Approach
Keywords:
Price Discovery, Volatility, Stocks, Financial MarketsAbstract
In this paper we analyse and show how price discovery process influence the volatility of stocks. Using a theoretical approach, our initial analysis revealed that stocks experience ‘normal’ volatility as the price move from one equilibrium price to another as part of the price discovery process. Our further analysis revealed that, due to the inefficiency of financial markets, stocks also experience transitionary volatility which occurs when the price transition from one equilibrium price to another. The implication of these analytical findings means that the price discovery volatility effects can only be reduced by improving the efficiency of financial markets. Thus, we recommended that the financial microstructure be designed in a manner that promotes the efficiency of financial markets.
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Baillie, R. T., Geoffrey Booth, G., Tse, Y., and Zabotina, T. (2002). Price discovery and common factor models. Journal of Financial Markets, 5(3). http://dx.doi.org/10.1016/S1386-4181(02)00027-7
Bellia, M; Pelizzon, L and Subrahmanyam, Ma. G; Uno, J and Yuferova, D(2016).Low-Latency Trading and Price Discovery: Evidence from the Tokyo Stock Exchange in the Pre-Opening and Opening Periods(September 20, 2016). SAFE Working Paper No. 144. Available at SSRN: https://ssrn.com/abstract=2841242 or http://dx.doi.org/10.2139/ssrn.2841242
Bookstaber, R.M and Pomerantz, S(1989). An Information Based Model of Market Volatility. Financial Analysts Journal Vol. 45, No. 6 (Nov. - Dec., 1989), pp. 37-46
Brogaard, J ; Hendershott,T and Ryan Riordan, R(2013). High Frequency Trading and Price Discovery. ECB Publications. Working Paper SerieS No 1602 / November 2013Darolles, S and Gouriéroux, C and Le Fol,G (2000). Intraday Transaction Price Dynamics. Annals of Economics and Statistics, GENES, issue 60, pp 207-238.
Easterling , E(2017). Volatility In Perspective. Crestmont Research .January 4, 2017.
Edwards, T and Lazzara, C.J(2016).Realized Volatility Indices: Measuring Market Risk.CFA S&P Dow Jones Indices McGraw Hill Financial, January 2016
Gusev, M; Kroujiline, D ; Govorkov, B; Sharov, S.V ; Ushanov, D and Zhilyaev, M(2014). Predictable markets? A news-driven model of the stock market. Munich Personal RePEc Archive
Hanousek, J and Kocenda, E (2009). Intraday Price Discovery in Emerging European Stock Markets. CERGE-EI Working Papers wp 382. The Center for Economic Research and Graduate Education - Economics Institute, Prague
Larsen, J.I (2010). Predicting Stock Prices Using Technical Analysis and Machine Learning Norwegian University of Science and Technology
Mittermayer, M (2004). Forecasting Intraday Stock Price Trends with Text Mining Techniques.Proceedings of the 37th Hawaii International Conference on System Sciences, 10 pp..10.1109/HICSS.2004.1265201
Phylaktis, K and Korczak, P(2007). Specialist Trading and the Price Discovery Process of NYSE-Listed Non-US Stocks .Working Paper. Available at SSRN: http://ssrn.com/abstract=567104
Schreiber, P.S and Schwartz, R.A(1986). Price discovery in securities markets. The Journal of Portifolio Management, Vol 12(4) pp43-48. DOI: 10.3905/jpm.1986.409071
Strohsal, T and Weber, E(2015). Time-Varying International Stock Market Interaction and the Identification of Volatility Signals. Journal of Banking & Finance .Vol 56, July 2015, pp 28–36. http://dx.doi.org/10.1016/j.jbankfin.2015.01.020
Sterne, P(2012). An Alternative Stock Market Structure that Provides Automatic Liquidity and Reduced Volatility. Frankfurt Institute for Advanced Studies, July 11, 2012
Yan, B. and Zivot, E. (2007). The Dynamics of Price Discovery. University of Washington Working Paper Series.
Yoon, H (2013). A Change of Order Balance Implies Intraday Price Trend in Japanese Stock Market. IPSJ SIG Technical Report. Vol.2013-MPS-94 No 12
Zhang, Q and Jaffry, S (2015) . High frequency volatility spillover effect based on the Shanghai-Hong Kong Stock Connect Program. Investment Management and Financial Innovations, Volume 12, Issue 2, 2015 pp 8-15
Zhang, X.F(2006). Information Uncertainty and Stock Returns. Journal of Finance, vol. 61, issue 1, pp 105- 137
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