TAILIEUCHUNG - Stock Market Trading Volume

Chong and Koh’s (2003) results were similar: they showed that stock prices, economic activities, real interest rates and real money balances in Malaysia were linked in the long run both in the pre- and post capital control sub periods. Mukherjee and Naka (1995) applied Johansen’s (1998) VECM to analyze the relationship between the Japanese Stock Market and exchange rate, inflation, money supply, real economic activity, long-term government bond rate, and call money rate. They concluded that a cointegrating relation indeed existed and that stock prices contributed to this relation. Maysami and Koh (2000) examined such relationships in Singapore. They. | Stock Market Trading Volume Andrew W. Lo and Jiang Wang First Draft September 5 2001 Abstract If price and quantity are the fundamental building blocks of any theory of market interactions the importance of trading volume in understanding the behavior of financial markets is clear. However while many economic models of financial markets have been developed to explain the behavior of prices predictability variability and information content far less attention has been devoted to explaining the behavior of trading volume. In this article we hope to expand our understanding of trading volume by developing well-articulated economic models of asset prices and volume and empirically estimating them using recently available daily volume data for individual securities from the University of Chicago s Center for Research in Securities Prices. Our theoretical contributions include 1 an economic definition of volume that is most consistent with theoretical models of trading activity 2 the derivation of volume implications of basic portfolio theory and 3 the development of an intertemporal equilibrium model of asset market in which the trading process is determined endogenously by liquidity needs and risk-sharing motives. Our empirical contributions include 1 the construction of a volume returns database extract of the CRSP volume data 2 comprehensive exploratory data analysis of both the time-series and cross-sectional properties of trading volume 3 estimation and inference for price volume relations implied by asset-pricing models and 4 a new approach for empirically identifying factors to be included in a linear-factor model of asset returns using volume data. MIT Sloan School of Management 50 Memorial Drive Cambridge MA 02142-1347 and NBER. Financial support from the Laboratory for Financial Engineering and the National Science Foundation Grant No. SBR-9709976 is gratefully acknowledged. Contents 1 Introduction 1 2 Measuring Trading Activity 3 Notation. 5 .

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