Sanjay Sehgal

Contrarian and Momentum Strategies in the Indian Capital Market

The study attempts to evaluate if there are any systematic patterns in stock returns for the Indian market. The empirical findings reveal that there is a reversal in long-term returns, once the short-term momentum effect has been controlled by maintaining a one year gap between portfolio formation period and the portfolio holding period. A contrarian strategy based on long-term past returns provides moderately positive returns. Further, there is a continuation in short-term returns and a momentum strategy based on it provides significantly positive payoffs. The results in general are in conformity with those for developed capital markets such as the US.

Impact of infrastructure on output, productivity and efficiency: Evidence from the Indian manufacturing industry

Purpose - The purpose of this paper is to provide an empirical evaluation of the impact of infrastructure development on industry-level productivity, output and efficiency in India over the period 1994-2006. Design/methodology/approach - The first stage, estimated total factor productivity (TFP) and technical efficiency of eight important industries. In the next stage, the effects of infrastructure were estimated on TFP, output, labor productivity and technical efficiency. Fully modified ordinary least squares procedure was utilized to generate consistent estimates of the relevant panel variables in the cointegrated frameworks. Findings - The results of this study are mixed. On the one hand, TFP, output and technical efficiency appear to be positively and largely affected by infrastructure. On the other hand, the effect of infrastructure on the labor productivity is somewhat negligible. In addition, the effects of information and communication technology on the industrial performance are found to be very weak. Originality/value - This is the first study of its kind in the related literature which attempts to investigate the role of infrastructure in industrial performance, using alternative frameworks, namely, growth accounting and production function approach. The paper uses appropriate techniques to account for the potential endogeneity of regressors as well as for multicollinearity among infrastructure variables.

Size Effect in Indian Stock Market: Some Empirical Evidence

In this study we attempt to test if there is a size effect in Indian stock market. The data relates to the top 482 Indian companies for the period 1990–2003. We find a strong size premium using six alternative measures of company size, viz., Market Capitalization, Enterprise Value, Net Fixed Assets, Net Annual Sales, Total Assets and Net Working Capital. Further the size based investment strategy seems to be economically feasible as it provides extra normal returns on risk adjusted basis. Frequent rebalancing of size based portfoilo is however found to be undesirable. The size effect does not seem to be owing to any seasonality or business cycle factors. The study has strong implications for mutual funds managers, investment analysts as well as small investors who are continuously on the lookout for trading strategies that beat the market. The presence of a strong size premium also raises doubts about the informational efficiency of Indian equity market.

Company Characteristics and Common Stock Returns: The Indian Experience

The paper examines the relationship between selected company characteristics and common stock returns. The empirical results suggest that there is a strong size effect in the Indian stock market using both market-based as well as non-market based measures of company size. We also detect a weak value effect on stock returns, especially when E/P ratio is employed as a relative distress proxy. The study further finds that the present stock classification system in India fails to differentiate in returns on different categories of stocks. We recommend an alternative stock classification system based on company size and relative distress. The proposed classification procedure will provide better insights to investors about the risk-return characteristics of common stocks.

The Eurozone crisis and its contagion effects on the European stock markets

Purpose - – This paper aims to examine the contagion effects of Greece, Ireland, Portugal, Spain and Italy (GIPSI) and US stock markets on seven Eurozone and six non-Eurozone stock markets. Design/methodology/approach - – In this paper, a dynamic conditional correlation (DCC) model popularly known as DCC-GARCH (Generalized Autoregressive Conditional Heteroscedasticity) model given by Engle (2002) is applied to estimate the DCCs across sample markets. Findings - – Analyzing the Eurozone crisis period, the empirical results suggest that among GIPSI stock markets, Spain, Italy, Portugal and Ireland appear to be most contagious for Eurozone and non-Eurozone markets. The study finds that France, Belgium, Austria and Germany in Eurozone and UK, Sweden and Denmark in non-Eurozone are strongly hit by the contagion shock. Practical implications - – The findings of the study have significant implications for the concerned regulatory authorities, as it may provide an important direction for further policy research with regard to financial integration in the European Union (EU). From global investors’ perspective, the EU-based diversification strategies seem to be inefficient especially during Eurozone crisis. Originality/value - – To the best of the authors’ knowledge, this is the first study that examines the issue of financial contagion of Eurozone crisis for a large basket of stock markets of European countries comprising seven Eurozone and six non-Eurozone markets for the period 2009-2012. The study uses the Markov regime switching model to identify crisis period and utilizes the DCC estimates of DCC-GARCH to examine the patterns of financial contagion. The finding of this study is quite interesting and is different in several ways than existing studies in the literature.

Robustness of Fama-French Three Factor Model: Further Evidence for Indian Stock Market

In this article, we re-examine the efficacy of one factor capital asset pricing model (CAPM) and Fama-French three factor asset pricing model (FF model) in explaining the returns on various portfolios constructed based upon company characteristics such as size and value. Data is employed from 1996 to 2010 for 465 companies which form part of BSE-500 index. We use the same methodological procedures of Fama-French (1993 and 1996) for constructing the portfolios. This article evaluates the robustness of FF model with its standard version (Market Capitalization–Price to Book ratio) as well as alternative versions. We find that FF model does a better job than CAPM by explaining the returns on most of the portfolios constructed based on company characteristics. We also find that the alternative versions of FF model are robust in explaining the returns on various characteristics sorted portfolios.

Investment Strategies of Fiis in the Indian Equity Market

In this paper, we empirically evaluate if Foreign Institutional Investors (FIIs) adopt positive feedback and herding strategies in the Indian environment. We find that FIIs exhibit return chasing behaviour when we use monthly data. However, they do not seem to be working on the positive feedback strategy when we use daily files. This may be owing to the fact that they wait for the market information to crystallize and do not react to it in an instantaneous manner. We also observe that the FIIs display strong herding behaviour based on quarterly shareholding pattern. The herding behaviour seems to be stronger at the aggregate level than at the individual stock level. This may be explained by the fact that FIIs are more cognizant of corporate fundamentals at the individual stock level. Further, the market cycle behaviour may vary from such cycles for individual stocks. Our findings have strong implications for domestic financial institutions, portfolio managers, wealth managers and other investors as well as market regulators who wish to have better understanding of FIIs behaviour as the later are the dominant investors in the Indian equity market.

Investor Sentiment in India: A Survey

In this paper we examine definitional aspect of Investor Sentiment, the key economic, market and regulatory factors that influence investor sentiment and the relationship between investor sentiment and market performance. There seems to be no clear consensus on the concept of investor sentiment and hence any meaningful definition ought to be inclusive and fluid. The important economic factors highlighted in the work are: Real GDP, Corporate Profits, Rate of Inflation, Level of Interest Rate, and Liquidity in the Economy. The market based factors that can be linked to Investor Sentiment are: Put Call Ratio, Advance Decline Ratio, Earning Surprises, P/E Ratio, and Price to Book Value. The regulatory framework of a financial market does seem to have a strong bearing on investor sentiment especially the legal provisions relating to corporate governance and Grievance Redressal Mechanism. Most respondents believe that investors sentiment and market returns are bilaterally co-related. Our findings are largely in conformity with recent studies for other capital markets. These findings can be used to develop a comprehensive Investor Sentiment Index for India and hence have significant implications for investors, market intermediaries and financial regulators.

Assessing time-varying stock market integration in Economic and Monetary Union for normal and crisis periods

In this paper, we examine the stock market integration process amongst 17 Economic and Monetary Union (EMU) countries from January 2002 to June 2013 over a normal period as well as for the Global Financial Crisis (GFC) and Eurozone Debt Crisis (EDC) periods. We classify the economies in three groups (A, B and C) based on their GDP to examine whether the economic size influences financial integration. Seven indicators are used for the purpose, namely, beta convergence, sigma convergence, variance ratio, asymmetric DCC, dynamic cointegration, market synchronisation measure and common components approach. The results suggest that large-sized EMU economies (termed as Group A) exhibit strong stock market integration. Moderate integration is observed for middle-sized EMU economies with old membership (termed as Group B). Small-sized economies (termed as Group C) economies seemed to be least integrated within the EMU stock market system. The findings further suggest presence of contagion effects as one moves from normal to crisis periods, which are specifically stronger for more integrated economies of Group A. We recommend institutional, regulatory and other policy reforms for Group B and especially Group C to achieve higher level of integration.

Regime Shifts and Volatility in BRIICKS Stock Markets: An Asset Allocation Perspective

This paper examines the regime shifts and stock market volatility in the stock market returns of seven emerging economies popularly called as ‘BRIICKS’ which stands for Brazil, Russia, India, Indonesia, China, South Korea and South Africa, over the period from February, 1996 to January, 2012 by applying Markov regime switching in mean-variance model. The employed model finds two regimes in each of these markets. The identified regimes are further utilized in formulating the asset allocation strategies based on market synchronization and Sharpe ratio. The results suggest that BRIICKS is not a homogeneous asset class and each market should be independently evaluated in terms of its regime switching behavior, volatility persistence and level of synchronization with other emerging markets. The study finally concludes that Russia, India and China as the best assets to invest within this emerging market basket which can be pooled with a mature market portfolio to achieve further benefits of risk diversification.