We study the strategic interaction between fundamental informed trading and order-flow informed trading. In a standard two-period Kyle (1985) model, we add a “back-runner” who observes, ex post and potentially with noise, the order flow of the fundamental informed investor in the first period. Learning from orderflow information, the back-runner competes with the fundamental investor in the sec...

Developing short-term stockmarket trading systems is a complex process, as there is a great deal of random noise present in the time series data of individual securities. The primary difficulty in training neural networks to identify return expectations is to find variables to help identify the signal present in the data. In this paper, the authors follow the previously published Vanstone and F...

We study the causal effect of trading on stock market liquidity. We exploit episodes of sensational news (exogenous to the market) that distract retail investors. On “distraction days” we find that trading activity, liquidity, and volatility all decline among stocks owned predominantly by retail investors. These findings, complemented by additional tests, establish that retail investors contrib...

The last decade has witnessed a dramatic increase in both the number and the market share of screen-based trading systems. Electronic trading systems do offer lower operating costs and the possibility of remote access to the market. On the other hand, arguments based on the anonymity of electronic trading systems suggest that adverse selection may be a more severe problem and that, therefore, b...

Motivated by previous findings that discretization of financial time series can effectively filter the data and reduce the noise, this experimental study compares the trading performance of predictive models based on different modelling paradigms in a realistic setting. Different methods ranging from real-valued time series models to predictive models on a symbolic level are applied to predict ...

this paper investigates the informational content of abnormal volume trading of shares listed at tehran stock exchange (tse) using an event study methodology. the results for a sample of 48 iranian firms during 1385-1388 show that there are abnormal returns before and after the abnormal trading volume dates. regression analysis also shows that there is a significant relationship between trading...

Chaos theory, originally a branch of modern physics holding that there is pattern to the seeming randomness of physical events occurring in the universe, is emerging as one of the mostdiscussed new paradigms in contemporary American thought, both legal and otherwise. ... Thus, any price change can only be the result of new information, the production of which is itself assumed to be random. ......

We investigate how distraction affects the trading behavior of retail investors, and ultimately market liquidity. Exploiting episodes of sensational news exogenous to the stock market, we first document that investors stop trading altogether when they are distracted. We report further that these effects are more pronounced for more overconfident–i.e., single-male and active–investors, who are t...

Employing Random Matrix Theory and Principal Component Analysis techniques, we enlarge our work on the individual and cross-sectional intraday statistical properties of trading volume in financial markets to the study of collective intraday features of that financial observable. Our data consist of the trading volume of the Dow Jones Industrial Average Index components spanning the years betwee...