Investor Pessimism and the German Stock Market: Exploring Google Search Queries

We analyze the relationship of retail investor sentiment and the German stock market by introducing four distinct investor pessimism indices (IPIs) based on selected aggregate Google search queries. We assess the predictive power of weekly changes in sentiment captured by the IPIs for contemporaneous and future DAX returns, volatility and trading volume. The indices are found to have individually varying, but overall remarkably high explanatory power. An increase in retail investor pessimism is accompanied by decreasing contemporaneous market returns and an increase in volatility and trading volume. Future returns tend to increase while future volatility and trading volume decrease. The outcome is in line with the conjecture of correction effects. Overall, the results are well in line with modern investor sentiment theory.     

Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific

In this paper, we focus on the question to what extent machine learning (ML) tools can be used to support systematic literature reviews. We apply a ML approach for topic detection to analyze emerging topics in the literature—our context is accounting and finance research in the Asia–Pacific region. To evaluate the robustness of the approach, we compare findings from the automated ML approach with the results from a manual analysis of the literature. The automated approach uses a keyword algorithm detection mechanism whereby the manual analysis uses common techniques for qualitative data analysis, that is, triangulation between researchers (expert judgement). From our paper, we conclude that both methods have strengths and weaknesses. The automated analysis works well for large corpora of text and provides a very standardized and non-biased way of analyzing the literature. However, the human researcher is potentially better equipped to evaluate current issues and future trends in the literature. Overall, the best results might be achieved when a variety of tools are used together.     

Do Mothers Matter? A Comparison of Models of the Influence of Mothers' and Fathers' Educational and Occupational Status on Children's Educational Attainment

The first objective of this article is to clarify which model best captures the structure and trend of the influence of social origin on children's education. The second objective is to analyse how general conclusions on historical trends in educational reproduction change if we add mother's status background to the model. Six contrasting hypotheses are derived fromthe body of literature dealing with models on families' socioeconomic status. All hypotheses are translated into empirical models and their explained variance is compared. A pooled data set is used that contains data from the Netherlands, West Germany, and the USA. The Modified Dominance Model, that distinguishes the influence of the highest from thelowest status parent, has the best model fit. Regarding the second objective we see that adding the mother's influence to that of the father's does not change general conclusions on trends in educational reproduction. Over time the influence of both parents decreases continuously. However, the influence of the mother's education and occupational status on children's educational attainment is substantive.     

神府—东胜矿区沙漠化趋势预测与防治措施

神府－东胜矿区在特定的自然地质环境和人为因素的影响下，土地沙漠化呈不断扩展的演化趋势。矿区大规模的开发建设，更加速了沙漠化进展。本文利用典型地段的沙漠化发展速率，依据矿区总体设计规模，对矿区自然沙漠化趋势和开矿新增沙漠化土地面积进行了定量预测，并提出了相应的防治措施。     

美国农业补贴政策的演变趋势分析

从1933年第一部系统的农业法开始实行以来,美国先后出台了数十个有关农业补贴的法律,对农业进行了长期高强度的补贴,形成了有特色的补贴体系.     

未来三十年我国及省际人口变动趋势

分析了我国人口的变动特点,并对未来三十年我国及省际人口的变动趋势作了预测,论述了我国未来人口的空间分布变动特点。     

Prizes for basic research: Human capital,economic might and the shadow of history

We study the distribution of basic scientific research across countries and time, and explain the process that resulted in the United States becoming the undisputed leader in basic research. Our study is based on the records of scientific awards, and on the data of global economic trends. We investigate the degree to which scale/threshold effects account for the number of prizes won. We constructed a stylized model, predicting a non-linear relationship with lagged relative GDP as an important explanatory variable of a country’s share of prizes. Our empirical research findings find support for these predictions and the presence of a “winner-takes-all” effect.      

The Evidence on Product-Market Diversifying Acquisitions and Joint Ventures by U.S. Banks

We examine the acquisition and joint venture strategies of U.S. banks from 1980 to 1998 to diversify into non-banking sectors. We find that the market responds favorably to both types of expansions, with the gains being shared between acquiring banks and their targets and venture banks and their non-bank partners, respectively. Acquisitions expose acquiring banks to significant increases in nonsystematic, market, and total risk, while joint ventures result in significant decreases in the nonsystematic and total risk measures for participating banks. Our results suggest that product-market expansions, in general, provide U.S. banks with value-enhancing opportunities, and that joint ventures may improve both the return and risk characteristics of the partner banks.     

The use of open source internet to analysis and predict stock market trading volume

The objective of this paper is to evaluate the impact of information demand and supply on stock market trading volume. Few studies have demonstrated the role of Google search data in analyzing trading volume activity. In this study, we employ a proxy for information demand which is derived from weekly internet search volume. The latest is from Google Trends database, for 25 of the largest stocks traded on CAC40 index, between April 2007 and March 2014. We use news headlines as a proxy for information supply. We use Garch model to analyze and predict trading volume.The empirical results present new evidences. First, information supply has an impact on trading volume but information demand's impact is much more important. Secondly, by applying MCA to results found, it could be concluded that the impact of public information on transaction volume is conditioned by two elements: the firm and market news disclosure and the second element relates to the characteristics of the market participants, more precisely their news interpretations and their risk aversion. Thirdly, we used Chow structural break test to verify the stability of our model. We found that for securities with structural changes, information demand is the responsible variable of the change in our model. Finally, we found that information variables have a predictive power on transaction volume.This paper contributes to existing literature by incorporating open source internet-based data into the analysis and prediction of transaction volume. Using internet information about the stock market, which has appeared recently as an interesting research for financial empiricists, computer scientists and practitioners, will have a very important utility because quantifying demand and supply of information becomes possible.     

Current issues and research trends on open-source software communities

Open source software (OSS) projects represent a new paradigm of software creation and development based on hundreds or even thousands of developers and users organised in the form of a virtual community. The success of an OSS project is closely linked to the successful organisation and development of the virtual community of support group. This paper reviews different fields and research topics related to the OSS communities such as collective intelligence, the structure of OSS communities, their success, communities as virtual organisations, motivation, shared knowledge, innovation and learning. The main challenges, results obtained, and the knowledge areas are detailed for each topic.