We develop a dynamic model in which traders have differential information about the true value of the risky asset and trade the risky asset with proportional transaction costs. We show that without additional assumption, trading volume can not totally remove the noise in the pricing equation. However, because trading volume increases in the absolute value of noisy per capita supply change, it provides useful information on the asset fundamental value which cannot be inferred from the equilibrium price.We further investigate the relation between trading volume, price autocorrelation, return volatility and proportional transaction costs. Firstly, trading volume decreases in proportional transaction costs and the influence of proportional transaction costs decreases at the margin. Secondly, price autocorrelation can be generated by proportional transaction costs: under no transaction costs, the equilibrium prices at date 1 and 2 are not correlated; however under proportional transaction costs, they are correlated - the higher (lower) the equilibrium price at date 1, the lower (higher) the equilibrium price at date 2. Thirdly, we show that return volatility may be increasing in proportional transaction costs, which is contrary to Stiglitz 1989, Summers amp; Summers 1989's reasoning but is consistent with Umlauf 1993 and Jones amp; Seguin 1997's empirical results.

The relationship of stock returns and trading volume is the focus of much recent interest. I examine an economic model of a rational trader who operates in a market with transactions costs and noise trading. The level of trading affects the rational trader’s marginal cost of transacting; as a result, trading volume is a source of risk. This engenders an equilibrium relationship between returns and volume. The model also provides a simple way to scrutinize this relationship empirically. Empirical evidence supports the implications of the model.

The relationship of stock returns and trading volume is the focus of much recent interest. I examine an economic model of a rational trader who operates in a market with transactions costs and noise trading. The level of trading affects the rational trader`s marginal cost of transacting; as a result, trading volume is a source of risk. This engenders an equilibrium relationship between returns and volume. The model also provides a simple way to scrutinize this relationship empirically. Empirical evidence supports the implications of the model.

Prior work with competitive rational expectations equilibrium models indicates that there should be a positive relation between trading volume and differences in beliefs or information among traders. We show that this result is sensitive to whether and how transaction costs are modeled. In a specialist market with endogenous transaction costs we show that trading volume can be negatively related to the degree of informational asymmetry in the market. Our analysis highlights the dependence of volume on market structure, and our results suggest that the quot;volume effectsquot; of corporate or macroeconomic events reflect a decrease, rather than an increase, in heterogeneity of beliefs or asymmetry of information.

Written by a number of authors, this text is aimed at market practitioners and applies the latest stochastic volatility research findings to the analysis of stock prices. It includes commentary and analysis based on real-life situations.

The widespread availability of high-quality, high-frequency data has revolutionised the study of financial markets. By describing not only asset prices, but also market participants' actions and interactions, this wealth of information offers a new window into the inner workings of the financial ecosystem. In this original text, the authors discuss empirical facts of financial markets and introduce a wide range of models, from the micro-scale mechanics of individual order arrivals to the emergent, macro-scale issues of market stability. Throughout this journey, data is king. All discussions are firmly rooted in the empirical behaviour of real stocks, and all models are calibrated and evaluated using recent data from Nasdaq. By confronting theory with empirical facts, this book for practitioners, researchers and advanced students provides a fresh, new, and often surprising perspective on topics as diverse as optimal trading, price impact, the fragile nature of liquidity, and even the reasons why people trade at all.