We extend Kyle's (1985) model of insider trading to the case where noise trading volatility follows a general stochastic process. We determine conditions under which, in equilibrium, price impact and price volatility are both stochastic, driven by shocks t ...
Many data-intensive applications require real-time analytics over streaming data. In a growing number of domains -- sensor network monitoring, social web applications, clickstream analysis, high-frequency algorithmic trading, and fraud detections to name a ...
We develop an econometric method to detect "abnormal trades" in option markets, i.e., trades which are not driven by liquidity motives. Abnormal trades are characterized by unusually large increments in open interest, trading volume, and option returns, an ...
This thesis examines the effects of financing frictions on corporate decisions using dynamic models. Accounting for financing frictions helps reconcile a number of regularities that are hard to explain within the Modigliani-Miller framework. For instance, ...
Applications ranging from algorithmic trading to scientific data analysis require real-time analytics based on views over databases receiving thousands of updates each second. Such views have to be kept fresh at millisecond latencies. At the same time, the ...
The objective of this research is to examine the efficiency of EUR/USD market through the application of a trading system. The system uses a genetic algorithm based on technical analysis indicators such as Exponential Moving Average (EMA), Moving Average C ...
Using a comprehensive sample of trades by Schedule 13D filers, who possess valuable private information when they accumulate stocks of targeted companies, this paper studies whether several liquidity measures reveal the presence of informed trading. The ev ...