This section contains information about articles under review and waiting for publication in next issues of the journal.

The relation between changes in the information content of earnings and expected stock returns: empirical evidence for Japan

Andreas Charitou, Professor of Accounting and Finance, University of Cyprus, Cyprus
Eleni Constantinidis, Ph.D. in Finance, University of Cyprus, Cyprus
Christodoulos Louca, Lecturer, Cyprus University of Technology and University of Durham, UK

Abstract. This paper examines the relationship between changes in the information content of earnings with expected stock returns for the Japanese market during the period 1991-2001. Results show that a mimickingportfolio return that relates to changes in the information content of earnings, explain a portion of the cross sectional variation in expected returns. Particularly, investors lower (appreciate) firms' stock price whenever firms experience decreases (increases) in the information content of earnings, to enable them to earn higher (lower) expected returns. This relation remains robust to the inclusion of market, size, and book to market factors. In addition, we investigate the extent to which changes in the information content of earnings relate systematically with size and book to market factors. Neither the size effect nor the book-to-market effects are found within the changes in the information content of earnings effect. Overall, our findings suggest that changes in the information content of earnings, is a unique effect not captured by the Fama and French (1992) three-factor model. 

An evidence-based investigation into the implications of socio-economic factors for private investment decision-making in the context of India

Vijayabanu Chidambaram, Assistant Professor, School of Management, SASTRA University, India
Amudha Ramachandran, Assistant Professor, School of Management, SASTRA University, India
Senthil Kumar Kesavan, Research Scholar, School of Management, SASTRA University, India

Abstract. People who save money with a high confidence level mainly characterize India. The success of investment prospects in India depends on the precise estimation of its potential. With a population of more than one billion strong work ethic, high levels of education, democracy, communication skills and an entrepreneurial culture, India is poised to dominate the global economy in the next 20 years. Investment is the sacrifice of certain present value for an uncertain future reward. It involves arriving at a number of decisions such as type, mix, amount, timing and grade of investment and disinvestments. Moreover, such decision-making has not only to be continuous but rational too. Broadly speaking, an investment decisions is trade off between risk and return. Since investments in securities are revocable, investment ends are transient and investment environment is fluid. The reliable bases of reasoned expectations become vague as one conceives uncertainty of the distant future. Investors will, therefore, from time to time, reappraise and reevaluate their various investment commitments in the light of new information and changed expectations. Investing has been considered as an activity confined to the rich and business class in the past. This can be attributed to the fact that availability of investible funds is a pre-requisite to deployment of funds. But, today, the investment has become a household word and is very popular with people from all walks of life. This study has been aimed to get more insight on the investment behavior of individuals based on their demographic factors like age, gender, income, educational qualification, place and occupational pattern.

The outcome of backdating investigations: economic consequences, market overreaction and management motives

Jingyu Li, Brock University, Canada
Fayez A. Elayan, Brock University, Canada
Thomas O. Meyer, Southeastern Louisiana University, USA
Parunchana Pacharn, Brock University, Canada

Abstract. Prior studies on option backdating have focused exclusively on initial backdating investigation announcements. Our major contribution is to account for the investigation outcome which no previous study examines. We provide evidence on market overreaction to the initial investigation announcement. We find 48 percent of firms are unintentional backdaters and their stock price losses are largely reversed at outcome announcements. By not accounting for ackdating outcomes previous studies overestimate backdating losses. 

Regimes in Australian pension fund returns: a hidden semi-Markov approach

Robert J. Bianchi, Senior Lecturer in Finance, Griffith Business School, Griffith University, Australia
Michael E. Drew, Professor of Finance, Senior Lecturer in Finance, Griffith Business School, Griffith University, Australia
Adam N. Walk, Ph.D. candidate, Griffith Business School, Griffith University, Australia

Abstract. Regimes are of interest to investors as they describe periods of episodic changes in returns and volatility caused by the non-normality and non-linearity characteristics of financial returns. The literature to date has examined regimes in single asset classes with little emphasis on the regime behavior of diversified (i.e. multi-asset investment) portfolios. This study examines whether lowering risk or increasing asset diversification are valid methods for investors to temper the regime behavior of their portfolios. Using a hidden semi-Markov model, we analyze the returns of two pension (i.e. superannuation) fund investment portfolios at opposite ends of the risk spectrum, namely a low risk cash-based portfolio and a moderate-to-high risk, but highly diversified, balanced portfolio. The findings show that asset class diversification does not appear to offer any noticeable benefits in relation to managing the regime behavior of investment portfolios. The findings also reveal that risk-reduction towards a cash based investment does not mitigate regimes in diversified portfolios.

Time series and neural network forecasts of daily stock prices

K. C. Tseng, Professor of Finance, California State University, USA
Ojoung Kwon, Professor of Information System, California State University, USA
Luna C. Tjung, MFP, CVM, CPEP and CHP; Director of Business Consulting and Investment Research at Fide Consultant Group, Singapore

Abstract. Time series analysis is somewhat parallel to technical analysis, but it differs from the latter by using different statistical methods and models to analyze historical stock prices and predict the future prices. With the rapid increases in algorithmic or high frequency trading in which trader make trading decisions by analyzing data patterns rather than fundamental factors affecting stock prices, both technical analyses and time series analyses become more relevant. In this study we apply the traditional time series decomposition (TSD), Holt/Winters (H/W) models, Box-Jenkins (B/J) methodology, and neural network (NN) to 50 randomly selected stocks from September 1, 1998 to December 31, 2010 with a total of 3105 observations for each company's close stock price. This sample period covers high tech boom and bust, the historical 9/11 event, housing boom and bust, and the recent serious recession and current slow recovery. During this exceptionally uncertain period of global economic and financial crises, it is expected that stock prices are extremely difficult to predict. All three time series approaches fit the data extremely well with R2 being around 0.995. For the hold-out period or out-of-sample forecasts over 60 trading days, the forecasting errors measured in terms of mean absolute percentage errors (MAPE) are lower for B/J, H/W, and normalized NN model, but forecasting errors are quite large for time series decomposition and non-normalized NN models.

What is a good investment measure?

Ping Hsiao, San Francisco State University, USA
Donglin Li, San Francisco State University, USA

Abstract. Capital investment should be correlated with investment opportunity sets, future realized growth, and contemporary employee turnover, thus capital investment proxies could be validated against these benchmarks. We find that the choice of deflator is important to the performance of capital-expenditure-based proxies that are commonly applied in the literature. In addition, capital-expenditure-based proxies often underperform investment proxies constructed on some simple accounting information. R&D responds well to investment opportunities in some industries but appears to be a poor indicator of firm growth in other industries. We explore some sources of the difference in performance across various investment proxies. 

Short-term prior return patterns in stocks and sector returns: evidence for BRICKS markets

Sanjay Sehgal, Professor of Finance, Department of Financial Studies, University of Delhi, India
Sakshi Jain, Research Associate, Department of Financial Studies, University of Delhi, India
Laurence Porteu de la Morandiere, Professor of Finance, ESC PAU Group, France

Abstract. In this paper, we examine if there are any prior return patterns in stock returns for BRICKS markets. Employing 6-6 portfolio formation/holding strategies, we observe strong momentum patterns for the sample markets with the exception of China. These momentum patterns disappear and in fact there are return reversals for some countries, as one elongates portfolio formation and holding windows to 12 months except for Indian market. Prior return patterns are not fully captured by CAPM as well as the Fama French three-factor model, especially for 6-6 strategy. There are prior return patterns in sector returns as was observed in case of stock returns. Hence, we augment the F-F model by including a sector momentum factor which is formed on basis of economic argument of Liu and Zhang (2008). The four-factor model is found to be a better descriptor of asset pricing but some unexplained returns may warrant a behavioral explanation for India and Russia. Our findings are relevant for global portfolio managers who are on the look out for portfolio trading strategies especially for emerging markets given their low degree of co-relation with the mature markets. The study contributes to the asset pricing anomaly literature especially for emerging markets. 

Aggregation of an FX order book based on complex event processing

Barret Shao, Applied Mathematics and Statistics, Stony Brook University, Stony Brook, USA
Greg Frank, Presagium LLC, USA

Abstract. Aggregating liquidity across diverse trading venues into a single consolidated order book is important for financial institutions that trade foreign exchange. But doing so poses several challenges, including stable latency performance under spurious bursts in message rate. Complex Event Processing offers an approach to this problem that yields performance and maintainability advantages over thread-based approaches. 

Is the progress of financial innovations a continuous spiral process?

Dionisis Th. Philippas, Department of Business Administration, University of Patras, Greece
Costas Siriopoulos, Department of Business Administration, University of Patras, Greece

Abstract. We herein examine the progress of financial innovations over the past 30 years, beginning with how they have influenced the financial system. We adopt a framework of classification that provides an overview of previous findings to examine the continuity of financial innovations. We find that the progress of financial innovations is discontinuous and is characterised by isolation and limited research studies. Finally, we highlight the main reasons why the previous literature in this area is limited and how financial innovations have not yet reached the point of diminishing returns.