Foundations of Technical Analysis: Computational Algorithms, Statistical Inference, and Empirical Implementation

Technical analysis, also known as 'charting,' has been a part of financial practice for many decades, but this discipline has not received the same level of academic scrutiny and acceptance as more traditional approaches such as fundamental analysis. One of the main obstacles is the highly subjective nature of technical analysis—the presence of geometric shapes in historical price charts is often in the eyes of the beholder. In this paper, we propose a systematic and automatic approach to technical pattern recognition using nonparametric kernel regression, and we apply this method to a large number of U.S. stocks from 1962 to 1996 to evaluate the effectiveness of technical analysis. By comparing the unconditional empirical distribution of daily stock returns to the conditional distribution—conditioned on specific technical indicators such as head-and-shoulders or double bottoms—we find that over the 31-year sample period, several technical indicators do provide incremental information and may have some practical value.     

An empirical study of voluntary transfer pricing disclosures in China

This paper empirically investigates the factors that affect the management’s voluntary disclosures of the transfer pricing details of related-party transactions. Using Chinese data from 2004 and 2005, we hypothesize and find that firms that make voluntary disclosures of the pricing methods of related-party transactions are negatively associated with (i) a higher level of earnings management (as captured by abnormal related-party transactions) and (ii) its underlying incentives (as captured by the management’s performance-linked bonuses and the firm’s incentives to achieve earnings targets); further, they are positively associated with (i) a higher percentage of independent directors and (ii) a higher percentage of government ownership. Overall, our findings suggest that earnings management and its incentives, board composition, and ownership structure significantly influence the voluntary disclosure decisions of managers.     

Maintaining cost and ruin probability

Review of Quantitative Finance and Accounting - Specialized funds such as charitable trusts do not attach much value to consumption, instead, they pursue to maintain a satisfactory level of...     

What do analysts do? Discussion of “Information interpretation or information discovery: which role of analysts do investors value more?”

Three decades of accounting and finance research has extensively studied the outputs from financial analysts. However, there is sparse systematic evidence on what analysts do to generate their outputs in the form of forecasts, recommendations, and research reports. Livnat and Zhang (Rev Account Stud, 2012) provide interesting new evidence regarding the relative amount of value added that analysts produce by examining investors?? reaction to analysts?? forecast revisions issued promptly after firms?? public disclosures compared with those issued at other times. Their analysis shows that prompt revisions are associated with larger returns, which the authors interpret as evidence that analysts?? ability to interpret public disclosures is more valuable to investors. Three issues bear consideration in the interpretation of these findings.     

Lucky lots and unlucky investors

Review of Quantitative Finance and Accounting - The number 8 is considered lucky under the Chinese culture. This paper tries to examine whether investors hold such superstitious belief in the Hong...     

Deviations from Purchasing Power Parity

This study uses univariate and multivariate unit root tests to analyze the random walk behavior of real exchange rates for the period 1979–1989. The univariate test fails to reject the random walk model, but the multivariate test indicates that part of the real exchange rates is predictable, a result supporting purchasing power parity. Further analysis of the random walk component in real exchange rates shows that it is quite persistent: for all currencies it takes about five to eight years for this shock to diminish to half its size.     

Can not-for-profits learn from for-profits?

Marketing management will help you maintain service quality, keep donors satisfied and generate a dependable source of income. For-profits survive on these activities.     

An Open Innovation Decision Support System to Select a Biopharmaceutical R&D Portfolio

Drugs available in the market today, selected several years ago under very uncertain future scenario, have experienced a long and expensive process of research and development carried out following both a closed and an open innovation path. To support this critical selection process, we propose a Decision Support System, able to choose among different candidates the most promising drugs along their best development path. The Decision Support System, based on a real options portfolio optimization model, mapping tools, and what‐if rules as well, has been applied to a numerical example available in literature, and the research findings show interesting managerial and academic implications. Copyright © 2015 John Wiley & Sons, Ltd.     

Assessing systemic risks and predicting systemic events

The paper develops a framework for assessing systemic risks and for predicting systemic events, i.e. periods of extreme financial instability with potential real costs. It contributes to the literature on the prediction of financial crises mainly in two ways: first, it uses a Financial Stress Index for identifying the starting date of systemic financial crises. Second, it uses discrete choice models that combine both domestic and global indicators of macro-financial vulnerabilities to predict systemic financial crises. The performance of the models is evaluated in a framework that takes into account policy maker’s preferences between missing crises and issuing false alarms. Our analysis shows that combining indicators of domestic and global macro-financial vulnerabilities substantially improves the models’ ability to forecast systemic financial crises. Our framework also displays a good out-of-sample performance in predicting the ongoing Global Financial Crisis.