The Nexus between Trading Volume and Stock Prices: Panel Evidence from OECD Countries

Abstract

(ProQuest: ... denotes formulae omitted.)1. IntroductionMarket price of stock reflects the present value of net cash inflows of investors expect to get changes that it may occurs in the dynamic markets and investors behavior led to change in expectations. This situation occurs to be happened by coming the new information to markets. The market price of stock is sensitive to the information too and price changes take place by the arrival of new information to the market and investors make investment decisions in the light of new informations (Rashid, 2007). Reaching new information to the investors changes their expectations to create trading volume and so leads to price movements (Cukur et al., 2012). This can be seen in three ways. First, it is tought that the information reaches the market creates trading volume and then the influence reflects to the stock price. But on the contrary, in accordance with the positive feedback hypothesis, investors will buy or sell floowing the rise or fall of the prices and this would cause an increase in the trading volume is considered as a secondary effect. It is considered as third effect that there is a bidirectional relation between price and volume and the two variables act together (Elmas and Yildirim, 2010).Karpoff (1987) has stated that it is important to examine nexus between trading volume and price changes in many respects. Findings about this nexus is very important to be reference about issue such as information from financial markets, this information is distributed and how is reflected, market depth, size. On the other hand, this information helps understanding of empirical distribution of speculative prices (Badhani and Suyal, 2005). Investors can measure the variance changes on price process by considering the nexus between price-volume about distribution of speculative prices. This is important in terms of effectiveness of investment decisions. Finally, price-volume nexus is quite important for the futures markets. Variability on prices affects quietly the trading volume of future contracts. On the other hand, time for delivery of future contracts explains both trading volume and variability of rates (Badhani and Suyal, 2005).The nexus between volatility of stock return and trading volume has been based on the models to reaching market of information and modeling distribution of stock prices (Cukur et al., 2012). These are sequential arrival information and mixed distribution hypothesis. Sequential arrival information hypothesis is put forward first time by Copel (1976) and then developed by Jennings and Starks et al. (1981). This hypothesis forecast a positive causality between the two variables because of containing information for explanation to current trading volume of past period prices and current trading prices of past period values on trading volume (Yilanci and Bozoklu, 2014). Model based on asymmetric information approach, all market participants weren't detected the informations simultaneously from new market. Moreover, this perception process refers to a sequential process that followed. Therefore, according to the successive information hypothesis, absolute lagged returns have the power to predict today's trading volume. On the other hand, the opposite situation may be possible. This situation has been developed by Mixed Distribution Hypothesis (Clark, 1973; Epps and Epps, 1976). The model also assumes that new information led to a change in the price reach simultaneously for market participants.Because of change in price and trading volume are based on a common process it is considered that they are in a positive synchronous nexus. However there is also Boisterous Processors hypothesis developed by De Long et. al. (1990). They do not have the necessary information about the market and they are influenced from past positive returns and set going future prices by increasing their trading volumes. Therefore, there is a bidirectional positive causality between stock returns and trading volume resulting from behavioral finance (Umutlu, 2008). …