The traditional finance studies suggest that financial markets move rationally and they are based on economic fundamentals. But psychological factors also influence the investment decisions and the mood of people significantly affects the decisions they make (Saunders, 1993; Hirshleifer & Shumway, 2003). It is well-known that weather effect is closely related to investors' mood and sentiments. Weather conditions affect an individual's emotional state or mood, which obstructs the people from making optimal or rational decisions. If the existence of weather effect affects the investors' decision making, various weather conditions might influence the movement of stock returns. The weather was extensively understood to influence people's mood. Good or bad weather, in the regions in which investors' trade, could be affected by their moods. Howarth & Hoffman (1984); Lucey & Dowling (2005) viewed that the returns may increase or decrease, according to the weather conditions. Many psychological studies confirmed the fact that depending on the mood, the individuals were more predisposed to either pessimistic or optimistic expectations (Arkes & Isen, 1988; Etzioni, 1988; Romer, 2000). Some economists (Lucey & Dowling, 2005) argued that the investors may not always act rationally when they make decisions in the economic market. Investors' psychological movements may affect their decisions (Bell & Baron, 1976; Allen & Fischer, 1978). Over the recent years, many researchers in behavioral finance have put their efforts to investigate the psychological factors that influence the investors' evaluation of securities. These psychological factors are related to mood fluctuations, induced by weather. (Kamstra, Kramer & Levi, 2003) investigated the relations between stock market returns and current weather conditions and the study found the 'sunshine effect', which is a negative correlation between cloudiness and stock market return. Predictability of stock returns was important for practitioners and academicians in finance since it has important implications for market efficiency, which, in turn, helps to produce more realistic asset pricing models (Rapach & Zhou, 2013; Neely, Tu, Rapach & Zhou, 2014). The market openness and globalization increased the proportion of foreign investors in local stock markets, which could weaken the weather effects in markets. With the development of electronic-trading system, the communication technology, arbitrageurs could make international portfolio strategies, using program trading. This development could also weaken the weather effects and make stock market more efficient.
REVIEW OF LITERATURE
An attempt has been made, to review the earlier research works, undertaken in the area of stock markets and weather factors, to understand research gaps, tools used and findings of earlier studies.
The review of earlier studies clearly reveals the fact that there was no comprehensive study, exclusively covering the correlation between stock returns and the weather, at the Indian Stock Exchange (Table 1). This research, on this subject, could help the policy makers and the investors, to easily identify the riskless weather condition and their diversification strategy for investments. It is an attempt to fill the gap of research on the Stock Returns and the Weather Conditions.
NEED AND IMPORTANCE OF THE STUDY
This research study is important because Indian Subcontinent attracts more number of portfolio investments compared to other Asian markets. The present study examined the interlinkages of three weather factors (temperature, humidity and wind speed), on the returns of the Indian stock indices (namely BSE Sensex and S&P CNX Nifty). Research in this area of weather factor and stock market has been mainly undertaken in the US, Europe and UK, where data are more available. A limited number of researches have been conducted examining the weather effect on the Indian capital market; moreover, none of the studies address causation. Which motivated to take a deeper look into seasonality in Indian stock markets? This study would help the investors make their investment decision strategy in Indian stock indices. The present study would be useful to the investors could formulate profitable trading strategies if they were able to predict the share price behavior with full information on these weather factors.
OBJECTIVES OF THE STUDY
The main objective of this study was to examine, the linkages and relationship among the sample indices (BSE Sensex and CNX Nifty) and weather factors (Temperature, Humidity and Wind speed), over the sample period.
HYPOTHESES OF THE STUDY
[NH.sub.1]: There is no normal distribution among the sample indices and weather factors in five sample cities.
[NH.sub.2]: There is no co-relation between the sample indices and weather factors in five sample cities.
[NH.sub.3]: There is no causal relationship among the sample indices and weather factors in five sample cities.
METHODOLOGY OF THE STUDY
Period of Study
For the purpose of examining the linkages and relationship among the sample indices (BSE Sensex and CNX Nifty) and weather factors (Temperature, Humidity and Wind speed)), the study covered a period of 16 years, from January 1, 2001 through December 31, 2016 (Chinnadurai, Sankaran, Kasilingam & Sigo, 2017).
In order to examine the linkages and relationship among the sample indices and weather factors, the study identified two Stock Market Indices, namely, BSE Sensex and CNX Nifty and three weather variables, namely, Temperature, Humidity and Wind Speed.
Sources of Data
For the purpose of analysis, the study used daily data of two stock indices, namely, BSE SENSEX, collected from http: www.bseindia.com and for S&P CNX NIFTY, from http:www.nseindia.com. Similarly, the data, relating to weather factors, in five metro cities of India (Bangalore, Chennai, Delhi, Mumbai and Kolkata), were collected from Indian Metrological Department-www.imd.gov.in
TOOLS USED FOR ANALYSIS
The following tools were used for the analysis.
Descriptive Statistics (to find out the normal distribution of returns of sample indices and weather factors in five sample cities).
Correlation Matrix (to find the correlation between sample indices and weather factors in five sample cities)
Granger Causality Test (to examine the linkage among the sample indices and weather factors in five sample cities).
LIMITATIONS OF THE STUDY
This study suffered from following limitations:
Only two indices, namely, SENSEX from Bombay Stock Exchange and S&P CNX Nifty from National Stock Exchange, were selected as the sample.
The study was limited to three weather factors (temperature, humidity and wind speed) and only in five metro cities (Bangalore, Chennai, Delhi, Kolkata and Mumbai) of India.
The study was based only on secondary data.
The limitations, associated with various statistical tools, may also apply to this study.
ANALYSIS OF EFFECT OF WEATHER ON SAMPLE STOCK MARKET INDICES
For the purpose of the study, the analysis of Normality, Pearson Correlation and Granger Causality, for the returns of Sample Indices and returns of Weather factors, is presented as follows:
Analysis of Normality for the returns of Sample Indices and weather factors in Sample Cities in India,
Analysis of Pearson Correlation for the returns of Sample Indices and weather factors in Sample Cities in India
Analysis of Granger Causality for the returns of Sample Indices and weather factors in Sample Cities in India.
Analysis of Normality for the returns of Sample Indices and Weather Factor in Sample Cities in India
The results of descriptive statistics, for the returns of sample indices and weather factors (temperature, humidity and wind speed), in top cities of India (Bangalore, Chennai, Delhi, Kolkata and Mumbai), during the study period from 1st January 2001 to 31st December 2016, are presented in Table 2. For the purpose of the analysis, the daily data, relating to sample two indices (BSE Sensex and NSE S&P CNX NIFTY) and daily data of weather factors, in five major cities of India, were compared. The Table clearly shows that there were positive mean returns, earned by two sample indices, against three weather factors, in five metro cities of India. The mean value of temperature, at Delhi Metro City was found to be the highest (0.005925), among all five sample cities, considered for this study. Similarly, the mean value of humidity, at Delhi Metro City, was found to be the highest (0.019858), among all five sample cities. But the mean value of Wind Speed, at Kolkata City, was found to be the highest (0.184436), among all five sample cities, during the study period. It is to be noted that the mean value, in respect of two sample indices, showed positive sign and it indicated the fact that both the indices (BSE Sensex and NSE S&P CNX Nifty) and weather factors (temperature, humidity and wind speed), in five major cities of India (Bangalore, Chennai, Delhi, Kolkata and Mumbai), earned high return, during the study period. The analysis of standard deviation...