Asymmetric information models predict comovements among trade characteristics such as returns, bid-ask spread, and trade volume on one hand and the trading intensity on the other hand. In this paper we investigate empirically the two-sided causality between trade characteristics and trading intensity. We apply a VAR-model for returns, bid-ask spread, trade volume, and trading intensity to trans...

In this paper, we use high-frequency data on five frequently traded stocks listed on the New York Stock Exchange (NYSE) in the year 1999 to examine the price impact of trades and its relation to the trading intensity. We show that the distribution of the absolute price change with fast trading firstorder stochastically dominates the distribution of the absolute price change with slow trading. M...

This paper examines the relationships between Internet message-board activity and abnormal stock returns and between Internet message-board activity and abnormal trading volume. This study focuses on RagingBull.com and Internet service sector stocks. I choose RagingBull.com because its format enables me to measure investor opinion objectively. I find that on days with abnormally high message ac...

This paper is to explore the possibility to use alternative data and artificial intelligence techniques to trade stocks. The efficacy of the daily Twitter sentiment on predicting the stock return is examined using machine learning methods. Reinforcement learning(Q-learning) is applied to generate the optimal trading policy based on the sentiment signal. The predicting power of the sentiment sig...

We find that weekend, holiday and overnight trading breaks generate excessive perceived risk in the option markets, presumably due to asymmetric information, which, in turn, encourages uninformed option traders to postpone trading. This perceived risk subsides after two days accompanied by an increase in the option trading volume and the underlying index’s actual price volatility. These results...

This paper examines the choice of trading venue by dealers in U.S. Treasury securities to determine when services provided by human intermediaries are difficult to replicate in fully automated trading systems. When Treasury securities go “off the run” their trading volume drops by more than 90%. This decline in trading volume allows us to test whether intermediaries’ knowledge of the market and...

We investigate the impact of dark trading on adverse selection in an aggregate market for UK stocks. Dark is linked to lower risk and improved informational efficiency liquidity market, even as declines lit with trading. However, there a value-based threshold when starts induce selection. estimate that this varies from around 9% most liquid stocks 25% least The overall average 288 FTSE 350 our ...

Stocks with better past returns crash more than other stocks on May 6, 2010. I find evidence that this is related to such stocks being unattractive to contrarian buyers. This suggests the importance of contrarian investors in stabilizing price fluctuations. However, the glass is half full---that the contrarian investors shun certain types of stocks limits the extent of price stability that reli...

We examine whether short sellers predominantly target stocks with recent price declines, amplifying the price decline and resulting in prices falling below fundamental values, or target apparently overpriced stocks facilitating prices that reflect fundamental values. We find evidence of short-sellers holding significant positions in stocks following price declines, and of short-sellers increasi...

Researchers often refer to investment habitats/categories to explain the patterns of comovement in asset returns that cannot be fully clarified by fundamentals. Many factors determine these habitats including investor preferences to size, industry, price-levels and risk-levels. This paper investigates a unique method to explore investment habitat based on the search behavior of investors on the...