Multivariate Analysis to get an Estimate of the Indian Stock Market Nifty Index

Research Paper (postgraduate), 2011

20 Pages, Grade: 1



The Indian stock market S and P CNX Nifty Index (Nifty) is a well diversified index of 50 companies. Foreign Institutional Investors (FII’s), wield significant influence over daily trading volumes in both the spot and derivative segments in the Indian markets. This tends to impact market volatility and returns. This study attempted to study the effect of FII transaction amounts, derivative turn over amounts and volatility on the performance of the Nifty index. A strong correlation was observed between derivative turnover and the Nifty but the correlation was relatively weaker between the Nifty and FII transaction amounts and Volatility. FII and F&O activity established important tops ahead of major tops in the Nifty. Volatility remained low during periods of significant upside in the stock market but spiked up during market declines. Linear and Non-linear models using multivariate analysis were fit to estimate the Nifty from the respective independent variables. A non linear model involving all three variables provided the best fit and the least deviation from actual values suggesting that interplay of these and other factors drive the performance of the index.

Keywords: Nifty, FII transaction amounts, F&O turnover, Volatility, Nifty forecasting, Linear and Non Linear Models.

1. Introduction

The Indian Stock market Index the S&P CNX NIFTY (NIFTY) has always been used as a barometer for a country’s economic progress. Covering fifty companies and well over fifteen sectors of the economy the index has assumed pivotal significance (S&P CNX Nifty, n.d.). The Nifty index is computed on a free float methodology from its underlying constituents. In the last six months, the total traded value of all Nifty constituents contributed more than 50% of the traded value of all stocks on the National Stock Exchange of India (NSE). Nifty stocks represented greater than 60% of the Total Market Capitalization as of April 30, 2010 (S&P CNX Nifty, n.d). The index figures prominently in a variety of purposes such as benchmarking fund portfolios, index based derivatives and index funds. Additionally with the growing popularity of India as a BRIC (Brazil Russia India China) economy the index and exchange traded funds and derivatives based on the Index have been listed and traded globally on several major stock exchanges such as the New York Stock Exchange (NYSE).

Movements in market indices are governed by technical factors such as chart patterns and fundamental factors that comprise events that influence the economy and corporate performance (Cofnas, 2003; Cofnas, 2004). Additionally fund flows and interest rate differentials are known to influence the long term direction of the Index (Gabaix et al., 2006; Lien, 2006). In India foreign institutional investor (FII) activity accounts for a significant portion of the trading volume of the index and its derivatives (Foreign Institution Investment trends, n.d). However it is not clearly known how this activity impacts the performance of the Nifty Index. The introduction of index derivatives has helped to smooth out market volatility (Girard and Biswas, 2007). However it is not clear as to what role derivative turnover and index volatility play in influencing the performance of the index. Quantitative models to estimate the index as a function of the above parameters are yet to be developed. Thus the goal of this study was to model and analyze the effect of the three parameters namely FII transaction amounts, derivative turnover or futures and options (F&O) turnover and volatility on the performance of the NIFTY index and develop models to get estimates of the index.

2. Literature Review

The Nifty is the most highly benchmarked Indian stock market index. Short term fluctuations in the Index are attributable to both Technical and fundamental factors. Fundamental factors that impact markets include economic news releases, corporate earnings releases, and changes in interest rates (Cofnas, 2004). Additionally Technical Analysis based on charting patterns and Fibonacci analysis offer short term trend trading opportunities (Cofnas, 2003). Emerging markets like India tend to benefit from favorable interest rate differentials and a shift in fund flows arising from potential changes in interest rates across the globe (Lien, 2006). These large and favourable interest rate differentials have led to the emergence of what is called the carry trade, which is simply an interest rate arbitrage strategy that borrows in low yielding economies like Japan and Invests in high yielding economies like those of the BRIC nations. The index is often also impacted by the performance of other global indices. A study has shown that the Indian market is strongly influenced by the performance of markets in the US, Japan and the UK (Lamba, 2005). Sabri, 2004 has showed in addition that trading volumes and exchange rates exerted the most influence on emerging market stock prices.

Fund flows into the Indian market occur through Foreign Institutional Investors (FII’s) and domestic players like banks and insurance companies, pension funds, hedge funds, and mutual funds, contributing significantly to trading volume on the major exchanges. Chakrabarti (2001) suggests that FII flows are the effect and not the cause of market returns. Mukherjee et al., (2002) on the other hand point out that FII fund flows tend to be a direct function of returns in the market. Thus there is no conclusive evidence as to whether these investors are the cause or effect of market returns. Griffin et al., 2004 suggest that FII flows are predictors of market returns in emerging markets like South Korea, Taiwan and India thereby indicating that FII’s are buyers before markets appreciate. Gabaix et al., 2006 suggest that FII’s can wield a significant influence in illiquid markets.

FII’s are active in both the cash and derivative segments and particularly in Nifty based derivatives which are among the most actively traded on the NSE. Analyzing derivative patterns such as open interest and put call ratios can possibly give an idea of the market trend as a whole. Studies have shown that the introduction of futures contracts in the Indian marked has resulted in reducing Nifty Volatility (Gupta and Kumar, 2002; Thenmozhi, 2002). Board et al., 2001 on the other hand observed that futures market trading does not significantly affect spot market volatility. The volatility of the Nifty index has been observed to vary significantly at market peaks and troughs. Global Volatility is observed to spike in situations governed by fear and panic as was observed during the Great Depression of 1929- 1939 (Officer, 1973) and in the most recent credit crisis. Indian market Volatility has been shown to be low during periods of growth and high during recessionary periods (Kumar, 2007). High volatility is often accompanied by low trading volumes as traders don’t like to expose themselves to rapidly fluctuating prices (Kiymaz and

Berument, 2003). We have recently shown that the above three parameters do synergistically impact the index (Rajveer et al., 2010). However the overall impact of FII flows, derivative turnover and Index volatility on the performance of the Nifty Index is not clearly established and models to estimate the index from these parameters are yet to be explored.

3. Methodology

This study used historical data to study the impact of the independent variables FII transaction amounts, derivative turnover and volatility on the performance of the dependent variable the NIFTY index. Weekly data on the above was obtained and studied in the time frame from January 2005 to December 2009. Historical data on derivative turnover i.e. F&O trading amounts was obtained from the National Stock exchange of India’s web site (Business Growth in Derivate Segment, n.d). Data for FII investment amounts was obtained from the Security and Exchange board of India (Foreign Institution Investment trends, n.d). Only FII investments in equity were considered. For FII and F&O amounts weekly data was obtained by summing up daily figures. The volatility of the Nifty index (VIX Nifty) was also retrieved from the National Stock exchange of India (India Vix, n.d). However data on Indian market volatility is not available prior to November 2007. Hence volatility for earlier periods was assessed by looking at the historic volatility of the US S&P 500 index (VIX S&P 500) which is available for much earlier periods. The VIX S&P 500 values were obtained from Yahoo finance (Volatility S&P 500, n.d). The relationship between the VIX Nifty and VIX S&P 500 was studied with the Statistics SPSS 18.0 package. The linear relationship fitted was used to calculate Indian market Volatility for earlier periods (Table I, Eqn (1)).


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Multivariate Analysis to get an Estimate of the Indian Stock Market Nifty Index
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Rajveer Rawlin (Author), 2011, Multivariate Analysis to get an Estimate of the Indian Stock Market Nifty Index, Munich, GRIN Verlag,


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