Prediction of Mutual Funds: Use of Neural Network Technique

-- Prasant K Sahoo and Priti Ranjan Hathy

Financial and economic forecasters have spurted the recent development of a number of new forecasting models. In the hard sciences, `neural network' can be used in the context of statistical analysis such as regression analysis, time series analysis, moving averages, and smoothing methods, and numerous judgmental methods as an alternative. In addition, neural networks can also overcome many of the shortcomings of traditional techniques, analyzing noisy data and incomplete data.

© 2007 IUP . All Rights Reserved.

The Initial and Aftermarket Performance of Indian IPOs

-- Shikha Sehgal and Balwinder Singh

This paper investigates the initial and long-run performance of 438 IPOs listed on the BSE between June 1992 and March 2006. Underpricing of an IPO is measured as the return on the first day of trading (relative to the offering price). To examine the long-run performance of Indian IPOs, Buy-and-Hold Abnormal Returns (BHAR) and Cumulative Abnormal Returns (CARs) for 120 months of secondary market returns have been calculated. Benchmark-adjusted initial returns are found to be around 100%, which is in line with the previous researches in India. The underpricing also conforms to international evidence though the magnitude of initial return is higher than that of other countries. Buy-and-hold returns have been found to be negative between 18 and 40 months of holding; however, such underperformance disappears after 40 months, i.e., in India, underperformance persists for about one-and-a-half years subsequent to IPO to a little more than three years. To check the robustness of this result, CARs also exhibit the existence of underperformance in the second and third years. Thus, long-run underperformance in India appears in the second year and subsists till the third year, though it dies out in the fourth and fifth years.

© 2007 IUP . All Rights Reserved.

Effect of Negative Book Equity on the Fama French HML

-- Bo Li and Paul Lajbcygier

Approximately 5% of stocks have negative book equities. Such stocks have a greater chance of financial distress. Due to difficulties in sorting these stocks into portfolios, they are omitted from most existing research, and the most important Fama French's value premium, HML, is no exception. Accepting the value premium is generated because book-to-market ratio acts as a default risk, documented widely in the finance literature, exclusion of these negative book equity stocks from data sample may result in weakening modeling representative, to say the least, as there are no other stocks in greater default risk than these negative book equity stocks. This study takes the Fama and French (1993) as a benchmark. The study first replicates their portfolio construction and obtains the value premium. It then includes the negative book equity stocks by using a novel clustering model, Brown's GSC. The study allocates these negative book equity stocks into predetermined portfolios and reconstructs a new value premium. In doing so, it finds that the new HML factor is statistically, economically, and significantly different from the old HML. The new HML replicating portfolio has a higher annualized return, which means that a practitioner may trade these negative book equity stocks and obtain an enhanced return. The results of this study show that the value premium exhibits a downward trend in the 1990s, but contradicts its explanation as the value premium gradually increases beyond the 1990s.

© 2007 IUP . All Rights Reserved.

Financing Constraints and Industry Classification: Evidence from Omani Firm Level Data

-- Y Sree Rama Murthy

Oman is an oil-rich nation but many firms in the country show clear evidence of financial constraints. This is paradoxical because the country has large oil surpluses, and banks, financial institutions, and other institutional investors in the country are flush with funds. Financial constraint is a well-researched topic and a large number of empirical research papers have been published on the topic of financing constraints. Previous researchers have classified firms into discrete categories of financial constraint and relate these classifications to accounting variables. This study uses the famous KZ index and the methodology suggested by Kaplan and Zingales to look at the firm level data of Omani companies. The KZ Index serves as an indicator of the level of financial constraint under which a firm is operating, and the higher the index, the more constrained is the firm financially. All the active companies listed on the Muscat Securities Market were considered for the purpose of the study. Data related to three years2003, 2004, and 2005was used for the purpose of the study. The study shows that a majority of the firms in some industry groups are financially constrained. Macro level bank credit data also indicates a decline in credit to some industry groups. The study argues that financial constraints depend on the industry group to which a firm belongs, because bank lending practices depend on the nature of the business and the type of the security available.

© 2007 IUP . All Rights Reserved.

Factors Determining the Capital Structure of Pharmaceutical Companies in India

-- T Mallikarjunappa and Carmelita Goveas

Several competing theories have emerged, since Modigliani and Miller's famous propositions on the capital structure, to test the ground realities of capital market imperfections such as taxes, bankruptcy costs, agency costs, and information asymmetries. In practice, capital structure matters, because empirical evidence shows consistent pattern of leverage ratios, both across industries and for individual firms over time. Leverage ratios of specific industries have been documented by many researchers. Therefore, the determinants of the capital structure of companies have been debated for long in corporate finance. This debate has resulted in differing theories on capital structure. However, the debate on the determinants of the capital structure is an ongoing one. In the light of this debate, this paper attempts to test the important determinants of the capital structure of companies. Taking profitability, collateral value of assets, growth, debt service capacity, size, tax rate, non-debt tax shield, liquidity, uniqueness, and business risk as the determinants and the Debt-Equity Ratio (DER) as the dependent variable, multiple regression model is used for the pooled data of pharmaceutical companies in India. The period of study is from 1993 to 2002. The results indicate that the regression is a good fit and the independent variables together determine the capital structure of companies. Further, the results show that profitability, collateral value of assets, growth, size, tax rate and uniqueness do not have significant coefficients and therefore, are not the significant determinants of the capital structure of companies. The coefficients of the variables, debt service capacity, non-debt tax shield, liquidity and business risk are significant and, therefore, these variables are the important determinants of the capital structure of pharamaceutical companies in India.

© 2007 IUP . All Rights Reserved.