In this project, 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 (CRSP) from 1962 to 1996.
In Phase I we plan to derive the volume implications of classical static portfolio theory, i.e., mutual-fund separation theorems. We then use these implications to define appropriate measures of trading activity for individual securities and for portfolios. Once the definition of volume has been settled, we shall provide extensive descriptive statistics and data analysis that capture the historical behavior of the weekly volume/returns database extract that we have constructed from the CRSP Daily Master File. We then test the implications of mutual-fund separation theorems by examining the empirical properties of the cross section of volume. Given the far-reaching impact of mutual-fund separation theorems, e.g., the CAPM and APT, exploring their volume implications is particularly important because it provides new testable implications to these well-worn paradigms. In much the same way that asset-market models such as the CAPM have guided empirical investigations of the time-series and cross-sectional properties of asset returns, we show that the volume implications of these models provide similar guidelines for investigating the behavior of trading activity.
In Phase II we plan to develop and estimate the volume implications of dynamic equilibrium models of asset markets such as the Intertemporal Capital Asset Pricing Model (ICAPM). These implications include price/volume relations, volatility/volume relations, and the interaction between the time-series and cross-sectional properties of volume and returns. To the extent that both prices and trading are driven by changes in economic conditions, volume, in addition to prices, contains important information about such conditions. Popular asset-market models make specific predictions about how volume is related to changes in underlying economic variables. Testing these predictions allows us to establish the relation between volume and these economic variables. Using the volume data to identify these variables, we can better understand how these variables are driving asset prices.
In Phase III we will investigate the implications of heuristic investment strategies such as "technical" trading rules and other behavioral models of trading activity. While such rules are more difficult to rationalize within the standard economic paradigm, nevertheless they do provide some insight into the more practical aspects of trading activity. We plan to investigate these heuristics in several ways: theoretically (by developing more formal economic models that are consistent with these heuristics), empirically (by estimating the performance of these heuristics using historical data), and experimentally (by conducting controlled trading exercises in the MIT Sloan School's Trading Laboratory).
In Phase IV we will develop the necessary infrastructure to provide internet access to our volume/returns database extract of the CRSP data to all current subscribers of CRSP. This includes user-guide documentation, database construction sourcecode, and sample empirical analyses to facilitate research in this area. If resources permit, we also hope to establish a website for volume researchers which will archive research papers in this area and maintain various non-proprietary volume databases.
Lo, A. and J. Wang, 2001, "The Econometrics of Trading Volume," to appear in Handbook of Financial Econometrics, Amsterdam: North-Holland.
Lo, A. and J. Wang, 2001, "Trading Volume," to appear in Advances in Economic Theory: Eight World Congress (Econometric Society Monograph).
Lo, A. and J. Wang, 2000, "Trading Volume: Definitions, Data Analysis, and Implications of Portfolio Theory," Review of Financial Studies, 13, 257-300.
Lo, A. and J. Wang, 2001, "Trading Volume: Implications of an Intertemporal Capital Asset Pricing Model," LFE Working Paper No. LFE-1037-01.
Adamek, P., Lim, T., Lo, A. and J. Wang, 1998, "Trading Volume and the MiniCRSP Database: An Introduction and User's Guide'',LFE Working Paper No. LFE-1038-98.
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