13th Global Conference on Business & Economics ISBN : 9780974211428
Investigating Stock Market Indices of India - Empirical Analysis
Dr.Jaspal Singh* and Sidharath Seth**
I. Introduction
Charles Dow is credited to have conceived the idea of the first stock index i.e. Dow Jones Industrial Average in 1896. Since then, all stock exchanges across the globe have built their own indexes. While they are widely used by the investors to know overall daily market performance, fund managers use them as a benchmark in evaluating their periodical performance. Studies have found that mutual fund managers fail to beat their respective benchmark index (Jensen, 1968; Malkiel, 1995; Gruber, 1996; Carhart, 1997; Daniel et al., 1997 and Chevalier and Ellison, 1999). These findings encourage the passive mode of investment through index funds, where money is invested in the same proportion among the securities representing the underlying index. Bogle is credited to have founded the Vanguard 500 Index Fund as the first index fund in 1975. He popularized the index funds as a better instrument for the long term investment over traditional mutual funds owing to lower management costs and their perpetual growth with economy (Bogle, 2000). Due to its attractiveness towards investment, the total worldwide assets under internal indexed management has escalated to US$5.994 trillion as of June 30, 2011 (Olsen, 2011) while global ETF market stood at about US$1.4 trillion at the end of 2011 (BlackRock, 2011).
At the end of September 2014, there were 43 index funds and 38 exchange-traded funds (ETFs) in India (listed on the National Stock Exchange and the Bombay Stock Exchange), of which 24 were index-based ETFs and 14 were gold-based ETFs (ISMR, 2014). Given the variety of indexes and index funds in India, there are numerous queries in the mind of a passive investor like how the indexes have performed in the past and which index is the most profitable to invest with.
The present study aims at examining the long run performance of all the broad market stock indexes operational at NSE (National Stock Exchange, India) and evaluating the best performing index amongst them which could be recommended to the passive investor to invest with over a long term.
The paper is organized in the following manner: Section II briefly explains about various broad market indexes at national stock exchange, India followed by the discussion on the previous literature in Section III, then, Section IV explains the data analyzed and the methodology adopted. Section V deals with the discussion of the observed results and finally, Section VI concludes this paper.
II. About the indexes at NSE, India.
Among the recognized stock exchanges in India, NSE (National Stock Exchange) is the largest stock exchange with maximum daily turnover in cash and derivatives segment followed by BSE (Bombay Stock Exchange) (ISMR, 2014). As on 30 June 2014, there are 36 indexes at NSE, maintained and managed by IISL (India Index Service Ltd, a subsidiary of NSE). They are broadly classified by NSE into four categories, namely Broad market, Sectoral, Thematic and Strategy indexes. This paper focuses solely on the Broad market indexes consisting of the large, liquid stocks listed on the exchange. They serve as a benchmark for measuring the performance of the stocks or portfolios such as mutual fund investments. Stocks are broadly classified into large cap, mid cap and small cap categories based on their market capitalization. Based on this classification, there are five large cap indexes (CNX Nifty, CNX Nifty Junior, CNX 100, CNX 200 and CNX 500), two mid cap indexes (CNX Midcap 50 and CNX Midcap) and one small cap index (CNX Small cap) as listed in appendix I.
III. Review of Literature
A limited amount of research has been done comparing various indexes across the globe. In the context with American markets, Statman (2000) primarily compared the Domini social index (DSI) with S&P 500 from May 1990 to September 1998 but failed to find any risk adjusted superior returns by the former. Later, Hakim and Rashidian (2002) examined risk-return characteristics of Dow Jones Islamic Stock Market Indexes (DJIM) with Wilshire 5000 stock market index from 1999 to 2002 and found that they failed to generate any excess returns over three month T-bill. Also, return and risk of Islamic index was found to be less than Wilshire 5000. Thereafter, Hussein (2005) found that Financial Time Stock Exchange (FTSE) Global Islamic index and Dow Jones Islamic Market Index performed in similar manner but behaved significantly different from their common index for the period January 1996 to December 2004. Later in the same year, using Dow Jones index and its Islamic version, Hussein and Omran (2005) concluded that the Islamic index outperformed the non-Islamic index both over the entire period from 1995 to 2003 and the bull period, while the vice-versa was true for the bear period. Further, Chan et. al. (2009) found negative and statistically significant alpha for Russell 2000 growth index while assessing merits of popular performance evaluation procedures adopted by academicians to a sample of active money managers and passive indexes. Finally, in an extensive work on indexes and pricing models, Cremers et. al. (2013) concluded that standard fama-french and cahart models produce economically and statistically significant non-zero alpha for passive benchmark indexes like S&P 500 and Russell 2000.
In context to Malaysian stock market, we came across only two studies namely Ahmad and Ibrahim (2002) and Albaity and Ahmad (2008) who compared performance of KLSI with KLCI over different time periods and found no statistically significant difference in their mean returns.
In the global context, using the data from July 1996 till August 2003, Hussein (2004) tested the performance of FTSE Global Islamic Index with their index counterpart (FTSE All- World Index) and found that while Islamic index yielded statistically significant positive abnormal returns in bull market period (July 1996 –March 2000), it underperformed in bear market period (April 2000 - August 2003). On analyzing social responsible investing across the globe, Schroeder (2007) compared performance characteristics of SRI equity indices with benchmark indices and found no statistical difference between them.
In Indian context, the authors came across only two studies on indices, one by Narasimhan and Balasubramanian (1999) and the other by Dharani and Natarajan (2011). While Narasimhan and Balasubramanian (1999) compared risk-return characteristics of only three indexes namely Sensex, Natex and BSE 200 using mean difference test and variance difference test and found statistically insignificant difference in the risk-return characteristics of these indices, Dharani and Natarajan (2011) compared risk and return of only two indexes i.e. Nifty Shariah index and Nifty index for four years from 2nd January 2007 to 31st December 2010. They tested the difference in the mean returns of both the indices using t- test and found that there was no statistical difference between average daily returns of both the indexes. However, there existed significant difference between average return of both the indexes in the month of July and September.
Thus, it can be seen that very limited research is done on performance of indexes in the Indian context. At the international level, while, majority of the studies found that there is insignificant difference in the returns of indices, however, only two studies namely, Chan et. al. (2009) and Cremers et. al. (2013) exclusively concluded that few indices show statistically significant different performance from others. Compared to the above mentioned studies on Indices, our study extends the research in two aspects. Firstly, we analyze performance characteristics of all the broad market stock indexes operational at national stock exchange, India using total return index values, and secondly, the study is done for a longer period i.e. from 1st January 2004 till 31st march 2014.
IV. Database and Methodology
Out of 36 indexes operational at NSE, 10 are broad market stock indexes that have been considered for our analysis (the other two are India VIX, a volatility index, and Nifty Dividend, a running total of dividend points of the securities forming part of CNX Nifty Index). However, each index has a different base date (as shown in appendix I). As a result, distinct time period is available for calculating performance evaluation parameters, thereby rendering them to be exposed to dissimilar market conditions. To illustrate, CNX Nifty Junior will be evaluated for 17.5 years (4th November 1996 till 31st March 2014), witnessing two bull and two bear periods but CNX Smallcap will be evaluated for only 10.25 years (1st January 2004 till 31st March 2014), observing only one bull and one bear period . Considering this disparity in evaluation due to varied time periods, a common period representing one complete business cycle of stock market that includes a bear and a bull run, has been selected from 1st January 2004 till 31st March 2014 for making meaningful comparison of performance. Out of 10 broad based stock indexes, it was found that 9 stock indexes have base date prior to 2nd January 2004. Hence, these are 9 stock indexes are analyzed using total returns index values from a common date i.e. 1st January 2004 till 31st March 2014 (covering complete cycle comprising one bull and bear period), after being exposed to similar market conditions. The total return index values reflect the returns arising from dividend receipts and price movement of the constituent stocks. The total return index values of all indexes is taken from bloomberg database. The implicit yield of 91-day treasury bills of Government of India is taken as a proxy of risk free rate (Connors and Sehgal, 2001). The data of risk free rates is taken from the website of Reserve Bank of India (www.rbi.gov.in). CNX Nifty is taken as market proxy. The daily data on factor portfolio excess returns for Indian stock market was obtained from the website of IIM Ahmedabad (http://www.iimahd.ernet.in/~iffm/Indian-Fama-French-Momentum/ accessed on 30th January 2015) (Agarwalla et al., 2013). The performance of indexes is evaluated using annualized return, annualized standard deviation, Sharpe ratio, Jensen alpha and Cahart four factor alpha.
The annualized return is the annual compounded return earned by an investor over a period by investing in an asset. It is useful in a way that for comparing returns over different lengths of time, the returns are rescaled to one year. It is calculated as follows:
R = X (I)
Where: R= Annualized Return (expressed as percentage), Xt =Terminal Value, Xo =Initial Value, t= Number of years.
Annualized Standard Deviation is a measure of volatility. An index with high annualized standard deviation is considered more volatile and hence, more risky. It is calculated as follows:
X (II)
Where: σA = Annualized Standard Deviation, σd = Standard Deviation computed using daily returns, T= Number of trading days in a year
The Sharpe Ratio measures the risk premium return earned per unit of total risk. It is calculated by dividing the excess of average daily portfolio rate of return over average daily risk free rate with the standard deviation of excess average daily portfolio returns. It is stated as follows:
(III)
Where: Si=Sharpe ratio for a portfolio, = Mean return on the portfolio, = Mean return on 91-day RBI Treasury bills (proxy for risk-free rate of interest), = Standard deviation of the excess average daily portfolio returns.
The Sharpe ratio shows the excess return earned by an investor for per unit of variability, they are exposed to by holding a riskier asset. A portfolio with highest positive Sharpe ratio is considered best for investment while the one having negative Sharpe ratio indicates that it failed to generate any superior return over risk free rate.
Jensen alpha is a risk-adjusted measure of fund managers’ performance that measures the excess return on a portfolio over the expected returns as predicted by the capital asset pricing model (CAPM). Jensen alpha is stated as follows:
(V)
Where: = Jensen Alpha, = Mean return on the portfolio, = Mean Return of CNX Nifty (proxy for market), = Mean return on 91-day RBI Treasury bills (proxy for risk-free rate of interest), = Beta of the portfolio.
The null hypotheses tested are as follows:
H0 = An index does not generate significant excess return than CNX Nifty i.e.
α = 0
H0= There is no significant difference in the relative risk of the particular index and CNX NIFTY i.e.
β = 1
H0= The particular index can be replicated by CNX Nifty, using joint hypothesis i.e.
α = 0 and β = 1
If a stock/portfolio/fund generates a better return than its beta would predict, it has a positive Jensen Alpha, and if it returns less than the amount predicted by beta, it has a negative Jensen Alpha. An investment manager yields a statistically significant positive Jensen alpha, if he has a superior stock picking or market timing ability in excess of the benchmark. Similarly, a portfolio whose beta is more than 1 is considered more volatile and hence, more risky than the market. On the contrary, a portfolio with beta less than 1 is considered less risky than the market. Also, the joint hypothesis H0: (α = 0 and β = 1) is tested to check if a portfolio can be replicated by the benchmark index. If the null hypothesis is not rejected, then investing in the benchmark index, on average, is equivalent to investing in the portfolio, without any significant difference in return or risk.