The Experts below are selected from a list of 34812 Experts worldwide ranked by ideXlab platform
Jiang Wang - One of the best experts on this subject based on the ideXlab platform.
-
Stock Market Trading Volume
Handbook of Financial Econometrics: Applications, 2010Co-Authors: Jiang WangAbstract: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 chapter, 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.
-
a model of competitive stock Trading Volume
Journal of Political Economy, 1994Co-Authors: Jiang WangAbstract:A model of competitive stock Trading is developed in which investors are heterogeneous in their information and private investment opportunities and rationally trade for both informational and noninformational motives. I examine the link between the nature of heterogeneity among investors and the behavior of Trading Volume and its relation to price dynamics. It is found that Volume is positively correlated with absolute changes in prices and dividends. I show that informational Trading and noninformational Trading lead to different dynamic relations between Trading Volume and stock returns.
-
A Model of Competitive Stock Trading Volume
Journal of Political Economy, 1994Co-Authors: Jiang WangAbstract:A model of competitive stock Trading is developed in which investors are heterogeneous in their information and private investment opportunities and rationally trade for both informational and noninformational motives. The author examines the link between the nature of heterogeneity among investors and the behavior of Trading Volume and its relation to price dynamics. It is found that Volume is positively correlated with absolute changes in prices and dividends. The author shows that informational Trading and noninformational Trading lead to different dynamic relations between Trading Volume and stock returns. Copyright 1994 by University of Chicago Press.
George H K Wang - One of the best experts on this subject based on the ideXlab platform.
-
Trading Volume bid ask spread and price volatility in futures markets
Journal of Futures Markets, 2000Co-Authors: George H K WangAbstract:In this study, we examined the relations between Trading Volume, bid–ask spread, and price volatility on four financial and metal futures. Hausman’s (1978) tests of specification confirmed that Trading Volume, bid–ask spread, and price volatility are jointly determined. We estimated the parameters and elasticities of Trading Volume, bid–ask spread, and price volatility in a three‐equation structural model, using the generalized method of moments (GMM) procedure. Results indicate that there was a positive relationship between Trading Volume and price volatility but an inverse relationship between Trading Volume and bid–ask spread after we controlled for other factors. Furthermore, results show that price volatility had a positive relationship with bid–ask spread and a negative relationship with lagged Trading Volume. In addition, we found that the ordinary least‐squares parameter estimates of each equation model were often severely underestimated in comparison with those consistent estimates obtained from the GMM estimation. Results from this study have important policy implications. Our results indicate that a transaction tax, which is analogous to a greater bid–ask spread, will reduce Trading Volume, although the reduction is not as great as we previously estimated. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20:943–970, 2000
-
Trading Volume bid ask spread and price volatility in futures markets
Journal of Futures Markets, 2000Co-Authors: George H K Wang, Jot YauAbstract:In this study, we examined the relations between Trading Volume, bidn ask spread, and price volatility on four nancial and metal futures. Hausmanis (1978) tests of specication conrmed that Trading Volume, bidnask spread, and price volatility are jointly determined. We estimated the parameters and elasticities of Trading Volume, bidnask spread, and price volatility in a three-equation structural model, using the generalized method of moments (GMM) procedure. Results indicate that there was a positive relationship between Trading Volume and price volatility but an inverse relationship between Trading Volume and bidnask spread after we controlled for other factors. Furthermore, results show that price volatility had a positive relationship with bidnask spread and a negative relationship with lagged Trading
-
Trading Volume, bid–ask spread, and price volatility in futures markets
Journal of Futures Markets, 2000Co-Authors: George H K Wang, Jot YauAbstract:In this study, we examined the relations between Trading Volume, bid–ask spread, and price volatility on four financial and metal futures. Hausman’s (1978) tests of specification confirmed that Trading Volume, bid–ask spread, and price volatility are jointly determined. We estimated the parameters and elasticities of Trading Volume, bid–ask spread, and price volatility in a three‐equation structural model, using the generalized method of moments (GMM) procedure. Results indicate that there was a positive relationship between Trading Volume and price volatility but an inverse relationship between Trading Volume and bid–ask spread after we controlled for other factors. Furthermore, results show that price volatility had a positive relationship with bid–ask spread and a negative relationship with lagged Trading Volume. In addition, we found that the ordinary least‐squares parameter estimates of each equation model were often severely underestimated in comparison with those consistent estimates obtained from the GMM estimation. Results from this study have important policy implications. Our results indicate that a transaction tax, which is analogous to a greater bid–ask spread, will reduce Trading Volume, although the reduction is not as great as we previously estimated. © 2000 John Wiley & Sons, Inc. Jrl Fut Mark 20:943–970, 2000
Andrew F Siegel - One of the best experts on this subject based on the ideXlab platform.
-
do upgrades matter evidence from Trading Volume
Journal of Financial Markets, 2019Co-Authors: Jonathan Brogaard, Jennifer L Koski, Andrew F SiegelAbstract:Abstract Prior researchers document no significant abnormal returns around upgrades of credit ratings, suggesting upgrades convey no new information. These studies are limited by lack of data, liquidity screens, and ambiguous predictions. We extend the literature using Trading Volume. Because Trading Volume is highly non-normally distributed (especially bond market Volume), we derive a new, more powerful nonparametric test statistic that can be used in other applications. Abnormal Volume is significant in the stock and bond markets around upgrades and downgrades. Some abnormal Volume is attributable to credit ratings-based regulations. Controlling for other effects, we find evidence that upgrade announcements contain information.
-
do upgrades matter evidence from Trading Volume
2017Co-Authors: Jonathan Brogaard, Jennifer L Koski, Andrew F SiegelAbstract:Prior research examines the information content of credit rating changes using returns in stock, bond or credit default swap markets. Results are mixed, generally showing a significant reaction to downgrades with much weaker results for upgrades. We extend prior research using abnormal Trading Volume. Because Trading Volume is highly non-normally distributed (especially in the bond market), we derive a new nonparametric test statistic that can be used to test abnormal Volume in other applications. Our results show significant abnormal Volume in both stock and bond markets around upgrades and downgrades, consistent with the hypothesis that credit rating changes are informative.
Carlos Velasco - One of the best experts on this subject based on the ideXlab platform.
-
Long Memory in Stock-Market Trading Volume
Journal of Business & Economic Statistics, 2000Co-Authors: Ignacio N. Lobato, Carlos VelascoAbstract:This article examines consistent estimation of the long-memory parameters of stock-market Trading Volume and volatility. The analysis is carried out in the frequency domain by tapering the data instead of detrending them. The main theoretical contribution of the article is to prove a central limit theorem for a multivariate two-step estimator of the memory parameters of a nonstationary vector process. Using robust semiparametric procedures, the long-memory properties of Trading Volume for the 30 stocks in the Dow Jones Industrial Average index are analyzed. Two empirical results are found. First, there is strong evidence that stock-market Trading Volume exhibits long memory. Second, although it is found that volatility and Volume exhibit the same degree of long memory for most of the stocks, there is no evidence that both processes share the same long-memory component.
Jonathan Brogaard - One of the best experts on this subject based on the ideXlab platform.
-
do upgrades matter evidence from Trading Volume
Journal of Financial Markets, 2019Co-Authors: Jonathan Brogaard, Jennifer L Koski, Andrew F SiegelAbstract:Abstract Prior researchers document no significant abnormal returns around upgrades of credit ratings, suggesting upgrades convey no new information. These studies are limited by lack of data, liquidity screens, and ambiguous predictions. We extend the literature using Trading Volume. Because Trading Volume is highly non-normally distributed (especially bond market Volume), we derive a new, more powerful nonparametric test statistic that can be used in other applications. Abnormal Volume is significant in the stock and bond markets around upgrades and downgrades. Some abnormal Volume is attributable to credit ratings-based regulations. Controlling for other effects, we find evidence that upgrade announcements contain information.
-
do upgrades matter evidence from Trading Volume
2017Co-Authors: Jonathan Brogaard, Jennifer L Koski, Andrew F SiegelAbstract:Prior research examines the information content of credit rating changes using returns in stock, bond or credit default swap markets. Results are mixed, generally showing a significant reaction to downgrades with much weaker results for upgrades. We extend prior research using abnormal Trading Volume. Because Trading Volume is highly non-normally distributed (especially in the bond market), we derive a new nonparametric test statistic that can be used to test abnormal Volume in other applications. Our results show significant abnormal Volume in both stock and bond markets around upgrades and downgrades, consistent with the hypothesis that credit rating changes are informative.
