Information Systems and Stock Return Volatility

Measuring Information Systems (IS) value has been constantly attracting much attention and debate within the IS research community. Since information systems effects are often difficult to quantify, traditional payoff evaluation methods often yield conflicting results. In this paper we suggest that some information systems can be evaluated on the basis of their effect on stock return volatility. Systems which facilitate information sharing and decision-making can improve the quality of company information to stakeholders, thus reducing surprise levels in financial markets. Specifically, these systems can lead to more consistent and predictable company performance. Hence, we hypothesize that information systems can help to reduce a company’s stock return volatility. To test this hypothesis, we have conducted an empirical analysis on a sample of firms that have deployed a Business Intelligence (BI) system. The results indicate a significant reduction in stock return volatility after BI deployment

How volatilities nonlocal in time affect the price dynamics in complex financial systems

What is the dominating mechanism of the price dynamics in financial systems is of great interest to scientists. The problem whether and how volatilities affect the price movement draws much attention. Although many efforts have been made, it remains challenging. Physicists usually apply the concepts and methods in statistical physics, such as temporal correlation functions, to study financial dynamics. However, the usual volatility-return correlation function, which is local in time, typically fluctuates around zero. Here we construct dynamic observables nonlocal in time to explore the volatility-return correlation, based on the empirical data of hundreds of individual stocks and 25 stock market indices in different countries. Strikingly, the correlation is discovered to be non-zero, with an amplitude of a few percent and a duration of over two weeks. This result provides compelling evidence that past volatilities nonlocal in time affect future returns. Further, we introduce an agent-based model with a novel mechanism, that is, the asymmetric trading preference in volatile and stable markets, to understand the microscopic origin of the volatility-return correlation nonlocal in time.Comment: 16 pages, 7 figure

Agent-based model with asymmetric trading and herding for complex financial systems

Background: For complex financial systems, the negative and positive return-volatility correlations, i.e., the so-called leverage and anti-leverage effects, are particularly important for the understanding of the price dynamics. However, the microscopic origination of the leverage and anti-leverage effects is still not understood, and how to produce these effects in agent-based modeling remains open. On the other hand, in constructing microscopic models, it is a promising conception to determine model parameters from empirical data rather than from statistical fitting of the results. Methods: To study the microscopic origination of the return-volatility correlation in financial systems, we take into account the individual and collective behaviors of investors in real markets, and construct an agent-based model. The agents are linked with each other and trade in groups, and particularly, two novel microscopic mechanisms, i.e., investors' asymmetric trading and herding in bull and bear markets, are introduced. Further, we propose effective methods to determine the key parameters in our model from historical market data. Results: With the model parameters determined for six representative stock-market indices in the world respectively, we obtain the corresponding leverage or anti-leverage effect from the simulation, and the effect is in agreement with the empirical one on amplitude and duration. At the same time, our model produces other features of the real markets, such as the fat-tail distribution of returns and the long-term correlation of volatilities. Conclusions: We reveal that for the leverage and anti-leverage effects, both the investors' asymmetric trading and herding are essential generation mechanisms. These two microscopic mechanisms and the methods for the determination of the key parameters can be applied to other complex systems with similar asymmetries.Comment: 17 pages, 6 figure

The Impact of the Sarbanes-Oxley Act (SOX) on the Cost of Equity Capital of S&P Firms

This study examines the impact of SOX on the cost of equity capital for small and large S&P firms. The provisions of SOX aim to improve internal control systems and reduce information asymmetry by improving corporate governance systems and increasing transparency. Using a fixed-effects regression model, our findings suggest that the cost of equity capital has decreased post-SOX for the overall sample of firms, but more specifically for the small firms, which are usually associated with poor internal control systems and high information asymmetry. Collectively, our results provide evidence that SOX has had a positive impact on firms

Does Intellectual Capital Affect the Volatility of Returns? An Empirical Investigation on Italian Listed Companies

In modern information economies, economic success increasingly depends on the ability to apply knowledge and to transform it into firm value. While intellectual capital plays a critical role in firm success, it is an intangible asset that is difficult to measure and that is unrecorded by the firm. Difficulties in measuring intellectual capital, as well as the dynamic nature of the firms that rely on it, may lead to greater stock market volatility/risk. Consistent with this expectation, in statistical tests we find that intellectual capital, measured by VAIC, positively relates to the volatility of stock returns section among Italian listed companies. We find this positive relation for two components of a firm’s risk: systematic risk and specific risk. The finding is relevant to both investors concerned with understanding the risk/reward balance of particular investments and regulators concerned with market stability