On the Extent of Speculative Activity in the Indian Stock Market during Badla and Post-badla Period

-- Harminder Singh and Vijaya B Marisetty

The authors test the existence of speculative activity in the Indian stock market during badla and post-badla period. They further investigate whether speculative activity migrated to single stocks futures market after banning of badla system. In both the tests it is found that there is no evidence of strong speculative activity in the Indian market. The research raises some questions on the regulators decision of banning badla system and sheds some light on the future decisions with respect to single stock futures market.

© 2005 IUP. All Rights Reserved.

A Suitable Volatility Measure in Indian Stock Market

-- Golaka C Nath and Manoj Dalvi

Indian stock market has seen many microstructure changes during last one decade or so that has helped its exponential growth. The equity market has crashed few times but settlement has passed off without any hitch. Volatility including intra-day volatility has been a major issue for the market. The paper tries to search for a suitable volatility measure for Indian stock market using tick level data and estimates six different kind volatility measures and compares them to understand which one performs best. The realized volatility estimates using the sum of squared returns from high frequency data performs better than the currently used IGARCH model by stock exchanges. The result is in agreement with the findings from developed markets.

© 2005 IUP. All Rights Reserved.

Is the Divisia Stock Index an Alternative Stock Index? An Evaluation

-- S Venkata Seshaiah

The main thrust of this paper is to propose the Divisia stock index as an alternative to the available stock market indices in the literature. Using the Sharpe model on monthly average data relating to closing prices of 27 companies and monthly average of BSE FMCG sector index during 2000:1 to 2004:8, it is shown that the `betas' based on the Divisia stock index are significant in most of the cases, while it is the other way round in the case of bs based on the FMCG index. The results also revealed that the unsystematic risk component is higher than that of systematic risk in case of Divisia stock index.

© 2005 IUP. All Rights Reserved.

Horizon Effect on the Prediction Performance of Artificial Neural Network: A Study in Indian Stock Market

-- Chakradhara Panda and V Narasimhan

This paper tries to see the performance of artificial neural network in predicting daily and weekly stock returns in both short and long forecast horizons. This paper also compares performances of neural network with those of linear autoregressive and random walk models in four different forecast horizons. Root mean square and sign prediction are used as two performance measures. From the results, we find that neural network performs better in the long run than in short run in terms of root mean square in the out-of-sample forecasting of daily stock returns. However, it is found that neural network's performance becomes worse, in terms of correct sign prediction, as the forecast horizon increases. Neural network has superior out-of-sample performance in predicting daily stock returns than linear autoregressive and random walk model under all forecast horizons in terms of both root mean square and correct sign prediction. We do not find a very clear forecast horizon effect on neural network's out-of-sample performance in terms of root mean square and sign prediction in predicting weekly stock returns. Neural network gives better out-of-sample forecasting of weekly stock returns, in terms of root mean square error, than random walk in longer horizons than shorter horizons. Neural network is also found to give better out-of-sample forecasting of weekly stock returns than linear autoregressive model, in terms of sign prediction, in short forecast horizon than long forecast horizon.

© 2005 IUP. All Rights Reserved.

Shareholding Patterns and Dividend Policy: Evidence from Indian Corporate Sector

-- Jitendra Mahakud

This paper examines the influence of shareholding pattern on dividend pay-out ratio of the Indian companies which belong to manufacturing industries and listed in Bombay Stock Exchange (BSE) during the period 2001-04. A balanced panel data analysis has been carried out to find out the effect of shareholding pattern on dividend policy. It finds a positive association of dividend with lagged dividend, earnings, sales and size of the company. Debt to equity ratio is found to be negatively related with dividend. Institutional shareholders have greater impact or influence on the determination of dividend pay-out ratio and it affects dividend policy inversely.

© 2005 IUP. All Rights Reserved.

Managing Mutual Fund Investments in the Era of Change

-- Kulbhushan Chandel and O P Verma

The active involvement of mutual funds in economic development can be seen by their dominant presence in the money and capital market. The present study is confined to evaluate the performance of mutual funds on the basis of weekly returns compared with risk free security returns and BSE Index. The present study includes the five different sector specific schemes. Among these 25 schemes, only sector-specific schemes floated by different institutions have been studied. To evaluate the performance of funds only three performance measures are applied under this study i.e., Sharpe Index, Treynor Index and Jensen's measure. It is observed that the performance of sample schemes during the study period is best. However, there are some instances where poor performance has been reflected. It may lead to regain investors' confidence.

© 2005 IUP. All Rights Reserved.

Financial Distress Prediction Models: A Case of Potential Sick Companies in India

-- P R Ramakrishnan

In this paper the applicability of two well-known financial distress models namely multiple discriminant analysis and logistic regression analysis have been examined. By using a sample of 298 firms it is found that cash flow and working capital are important predictive variables irrespective of models selected and these models are capable of predicting with minimum error one year in advance, which is vital for the bankers, restructuring agencies and the management to initiate revival process before the company actually gets into financial distress.

© 2005 IUP. All Rights Reserved.