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Full-Text Articles in Business
Legal Risk And Insider Trading, Marcin Kacperczyk, Emiliano Sebastian Pagnotta
Legal Risk And Insider Trading, Marcin Kacperczyk, Emiliano Sebastian Pagnotta
Research Collection Lee Kong Chian School Of Business
Do illegal insiders internalize legal risk? We address this question with hand-collected data from 530 SEC (the U.S. Securities and Exchange Commission) investigations. Using two plausibly exogenous shocks to expected penalties, we show that insiders trade less aggressively and earlier and concentrate on tips of greater value when facing a higher risk. The results match the predictions of a model where an insider internalizes the impact of trades on prices and the likelihood of prosecution and anticipates penalties in proportion to trade profits. Our findings lend support to the effectiveness of U.S. regulations' deterrence and the long-standing hypothesis that insider …
The Effects Of Conflict Type And Conflict Expression Intensity On Conflict Management, Gergana Todorova, Kenneth T. Goh, Laurie Weingart
The Effects Of Conflict Type And Conflict Expression Intensity On Conflict Management, Gergana Todorova, Kenneth T. Goh, Laurie Weingart
Research Collection Lee Kong Chian School Of Business
Purpose: This paper aims to add to the current knowledge about conflict management by examining the relationships between conflict type, conflict expression intensity and the use of the conflict management approach. Design/methodology/approach: The authors test theory-based hypotheses using a field study of new product development teams in an interdisciplinary Masters program (Study 1) and an experimental vignette study (Study 2). Findings: Results show that people are more likely to respond to task conflict and conflicts expressed with less intensity using collectivistic conflict management approaches (i.e. problem-solving, compromising and yielding), and to relationship conflicts and conflicts expressed with higher intensity through …
Speed Acquisition, Shiyang Huang, Bart Zhou Yueshen
Speed Acquisition, Shiyang Huang, Bart Zhou Yueshen
Research Collection Lee Kong Chian School Of Business
Speed is a salient feature of modern financial markets. This paper studies investors' speed acquisition together with their information acquisition. Speed heterogeneity arises in equilibrium, fragmenting the information aggregation process with a nonmonotone impact on price informativeness. Various competition effects drive speed and information to be either substitutes or complements. The model cautions the possible dysfunction of price discovery: An improving information technology might complement speed acquisition, which shifts the concentration of price discovery over time, possibly hurting price informativeness. Novel predictions are discussed regarding investor composition and their investment performance.
Center Of Volume Mass: Does Options Trading Predict Stock Returns?, Gennaro Bernile, Fei Gao, Jianfeng Hu
Center Of Volume Mass: Does Options Trading Predict Stock Returns?, Gennaro Bernile, Fei Gao, Jianfeng Hu
Research Collection Lee Kong Chian School Of Business
We examine whether the distribution of trades along the set of strike prices of option contracts on the same stock contains information about underlying price discovery. We show that option traders' demand for delta exposure drives the volume-weighted average strike-spot price ratio (VWKS). In turn, we find that VWKS predicts underlying returns and anticipates the flow of fundamental information about the stock. The return predictability is greater but not limited to stocks with higher information asymmetries and arbitrage costs, and becomes stronger ahead of value relevant news. Overall, options trading appears to play an important informational role for underlying markets.
Textual Analysis And Machine Leaning: Crack Unstructured Data In Finance And Accounting, Li Guo, Feng Shi, Jun Tu
Textual Analysis And Machine Leaning: Crack Unstructured Data In Finance And Accounting, Li Guo, Feng Shi, Jun Tu
Research Collection Lee Kong Chian School Of Business
In finance and accounting, relative to quantitative methods traditionally used, textual analysis becomes popular recently despite of its substantially less precise manner. In an overview of the literature, we describe various methods used in textual analysis, especially machine learning. By comparing their classification performance, we find that neural network outperforms many other machine learning techniques in classifying news category. Moreover, we highlight that there are many challenges left for future development of textual analysis, such as identifying multiple objects within one single document.