Sectoral indices movement: a study of financial crisis era.

Taneja, Yash Pal ; Bansal, Shipra

INTRODUCTION

The global financial crisis happened in the mid of 2007 and caused a huge impact on financial markets and institutions around the world. The bursting of the housing bubble in a number of countries, the subprime financial crisis in the United States, rising commodity prices, and, restrictive monetary policies led the global economy to the "brink of recession" in the first half of 2008 particularly in several countries (TDR 2008: 1) (1) The IMF's Global Financial Stability Report 2006 warned that the rapid expansion of household credit "can compound the problems of excessive consumption, current account imbalances, and property boom-bust cycles. If credit is predominantly financed by external capital flows, it can heighten the vulnerability to sudden stops and financial crises" (IMF, 2006: 69) (2). What makes this crisis exceptionally widespread and deep is the fact that financial deregulation, "innovation" of many opaque products and a total ineptitude of credit rating agencies raised credit leverage to unprecedented levels. Blind faith in the "efficiency" of deregulated financial markets led authorities to allow the emergence of a shadow financial system and several global "casinos" with little or no supervision and inadequate capital requirements. (3)

In the 17th meeting of IMF 2008, P. Chidambaram, the then minister of finance, Indi stated that the immediate fallout of the financial crisis was reflected in a reversal of the robust trend of global growth during 2008. The year 2008 had been highly turbulent for the world's economy which had been hit hard by a profound financial crisis. The problems in financial markets turned into a full blown crisis in September 2008, the growth of Gross Domestic Product (GDP) had ground to a halt in most developed countries. Table 1 shows the annual growth rate of numerous countries of the world including the world annual growth rate.

It can be seen from table 1 that annual growth rate of the world fell from 3.98 in 2007 to 1.44 in 2008 and 2.31 in 2009. In the period 2008-09, many countries were found in the grip of recession. For example, US GDP growth rate fell from 1.94 in 2007 to -0.02 in 2008. Similarly India's GDP growth rate fell from 9.82 to 4.93, China's GDP growth rate fell from 6.39 to 2.31, Japan's GDP growth rate fell from 2.36 to -1.17 and UK's GDP growth fell from 3.47 to -1.10. This reflects that almost all countries had experienced a sharp slowdown of economic growth in mid-2008. This crisis was unique, not only in terms of its depth but also in the extent of its global reach: virtually no economy has remained unaffected. Even economies that were expected to grow in 2008-09, such as those of China and India, were slowed down significantly from their previous years of rapid growth. (4)

The above analysis clearly shows that 2003-07 phase was not unique to India in terms of growth. It was basically common for all economies which registered higher growth in the 2003-07 periods. It is also true that India was relatively less affected from the crisis compared to other economies during the crisis. The global financial crisis affected every economy in the world, and India was no exception. But India recovered from the crisis much sooner than even other emerging economies. The reason behind India's growth acceleration in the pre-crisis period: the impact of economic reforms of the 1990s; India's rapid integration with the global economy; rise of entrepreneurism; and increase in productivity. Underlying all these major factors was the massive increase in capacity as investment jumped from 26.9 per cent of GDP in 2003/04 to 38.1 per cent in 2007/ 08. This increase in investment was financed by growing domestic savings, and was accompanied by an increase in productivity driven by improvements in technology, organisation, financial intermediation and external and domestic competitiveness. The Current Account Deficit (CAD) during this period averaged just 0.3 per cent of GDP suggesting that the contribution of foreign savings to domestic investments was relatively modest. But to the extent foreign saving came by way of foreign direct investment (FDI), it raised the productivity of overall investment and resulted in higher exports. (5)

The financial crisis effect on the Indian economy was not significant in the initial part of the recession. In fact India was having positive effect of the subprime crisis as the country received accelerated Foreign Institutional Investment (FII) flows during September 2007 to January 2008. It was a general belief prevailing at that time that the emerging economies could remain unaffected from ill effects of the crisis and provide an alternative engine of growth to the world economy. But the belief soon proved wrong as the global crisis intensified and spread its arms even to the emerging economies through capital and current account balances of payments. And as a result the net foreign portfolio flows to India soon turned negative as Foreign Institutional Investors rushed to sell equity stakes in a bid to replenish overseas cash balances. This leads knock-on effect on the stock market and the exchange rates through creating the supply demand imbalance in the foreign exchange market. After September 2008, the current account was affected mainly because of decrease in exports. Despite setbacks, however, the Balance of Payments situation of the country continues to remain elastic. Growth got decelerated, inflation was high and stubborn, the investment rate had declined sharply and the external sector was beset with a record high current account deficit. This downturn caused widespread anxiety that we might have got derailed from the high growth trajectory.

To overcome from the crisis situation, both monetary and fiscal policy played an important role in attaining and sustaining high rates of economic growth. The former covered issues such as the trade-off between inflation and growth and the latter covered institutional reforms necessary for restoring high growth. Analysis of the sectoral composition of growth revealed that the growth moderation during 2008-12 has been driven largely by manufacturing and agriculture sectors. On the expenditure side, growth was led by both private and government consumption expenditure as investment growth moderated. To control inflation, the Reserve Bank reversed the crisis period's accommodative monetary stance in quick order. RBI raised the policy interest rate (repo rate) 13 times, cumulatively by 375 basis points (bps)--from 4.75 per cent to 8.5 per cent. RBI also raised the reserve requirement on banks--the cash reserve ratio (CRR)--by 100 bps from 5 per cent to 6 per cent. All these efforts supported the Indian economy to recover from the crisis state of affairs more promptly as compared to other economies of the world.

Various studies had been conducted to check the impact of this global meltdown on different economies by various stakeholders, researchers and academicians under different times. Angabini and Wasiuzzaman (2011) investigated the volatility of Kuala Lumpur Composite Index (KLCI) with regards to the financial crisis of 2007-08. For this, two different periods were selected-without crisis period and with crisis period. It was found that volatility was relatively consistent from 2001 to the year 2007 and increased in the middle of 2007 till 2009. Cocozza, Colabella and Spadafora (2011) found the adverse impact of global crisis on six south eastern European countries as their exports declined, external debt and Trade deficit increased. Adamu (2009) revealed that financial crisis lead to fall in commodity prices, decline in export, lower portfolio, and fall in FDI inflows and equity markets in the Nigerian economy.

While the developed World, including the US, the Euro zone and Japan had plunged into recession, the Indian Economy was being affected by the spill-over effects of the global financial crisis (Chidambaram, 2008). India started its globalization in 1992 and since then Indian economy integrated with the World economy. As a result, Indian economy was not isolated by freezing of stocks and downsizing in the World economy. As honorable Prime Minister, Dr. Manmohan Sing pointed out that "A global Financial Crisis of this magnitude was bound to affect our economy and it has." Post the beginning of 2008, the global stock markets, after a continuous bull run of virtually four years, has behaved intermittently since the beginning start of 2008. Indian indices fell severely accompanied with a high degree of volatility when the sub-prime crisis hit the global markets. Sensex, an economic barometer of Indian economy dropped from 21,000 to less than 10,000 points which was by or large due to the global slowdown wave. As per the data collected from file of preview grid of World Bank, the year 2008 reported the lowermost growth rate of 4.93 in India. It reflects that the financial crisis had an adverse consequence on the Indian Economy. A number of studies had been conducted to realise the influence of financial crisis on India. Aziz (2010) studied the effect of global recession on numerous macroeconomic variables and determined that the most immediate effect of that crisis on India has been an outflow of foreign institutional investment from the equity market. It was also found that both exports and imports of India slowed down in 2008-09 but decline in growth of exports during that period was sharper than the decline in growth rate of imports. Bera (2010) empirically scrutinized the impact of the current world-wide recession on India's growth by applying regression technique, by taking GDP as dependent variable, and exports, imports, FDI and FII as independent variables. All the variables were tested for stationarity first by using Augmented Dickey-Fuller (ADF) test. The results pointed out that financial crisis had adversely affected India's GDP although imports, exports and FDI were found to have exercised stimulating influence through technological spillovers and other externalities. Khan and Mehtab (2010) studied the same by studying the effect of crisis on exports, import and foreign reserves. For this, a T-test had been conducted. It was found that the global recession had an impact on Pre and Post Export Earnings as well as Import Earnings of the country. The Student T-Test also presumed the hostile impact of the recession on foreign reserves. Kundu (2008) focused on the impact and analysis of the global financial crisis on India's financial market and the real economy. The impact of crisis was seen through slower GDP growth, the depreciation of rupee, a high inflation and lower FII investment and foreign exchange reserves. The same conclusions had been supported by Kumar and Vashisht (2009) and Vidyakala, Poornima and Madhuvanthi (2009).

Many studies had been conducted to know such adverse impact by having sectoral analysis in order to know its magnitude and direction. Kaur (2010) analysed the impact of recession on various sectors of Indian economy during 2000-01 to 2009-10. The results found that major impact was seen on fall in growth rate of IT sector, decreased in FDI, exports and imports of the Indian economy. Beside this, the factor causing recession had also been studied using multiple regression technique by taking GDP as dependent variable and production of IT sector, FII and FDI as independent variable. It was found that these factors had influence on GDP as the model explained 99.10 percent of variation. Rao and Naikwadi (2010) examined the impact of global financial meltdown on beta of selected companies by using average, percentage and Karl Pearson correlation method. He concluded that Banking, cement, automobile, steel and Infrastructure sectors were badly affected by global financial meltdown. However, a small impact was found in FMCG and retail sector. Similarly, Prasad and Reddy (2009) found adverse affect on sectors like IT, FII, Banking, Infrastructure and exports. Vidyakala, Madhuvanthi and Poornima (2009) found the adverse effect on banking sector.

Whereas Jeeyanthi, William and Kalavathy (2012) empirically examined the impact of global financial crisis on Indian stock market return and volatility during April 2005 to March 2010. They applied T-test, Binary regression test, wilcoxon rank sum test and Kruskal-wallis H-test to examine the short term and long term impact on the return of Indian stock market. Parkinson model, Garman and Klass model and GARCH model were used to know the impact of crisis on volatility of Indian stock market. The results concluded that financial crisis had no significant impact on Indian stock market return and volatility. The overall findings of different researches related to impact of global crisis on different economies are summarised in table 2.

The discussion above concludes that the financial crisis had brought about an adverse effect on the Indian economy as examined by Bera (2010), Khan and Mehtab (2010), Aziz (2010), Rao and Naikwadi (2010), Kaur (2010), Vidyakala, Poornima and Madhuvanthi (2009), Prasad and Reddy (2009), Kumar and Vashisht (2009) and Kundu (2008). The impact had been found out by studying adverse effect on various macroeconomic variables like GDP growth rate, exports, imports, FIIs and FIIs and sectors like Banking, IT, Infrastructure. It seems that few researchers had attempted to know the impact of financial crisis through sectoral indices risk-return paradigm that could not be traced especially with regard to Indian context.

The present study attempts to focus on sectoral indices returns with regard to global meltdown in comparison to post and pre financial era especially for India. Hence it becomes imperative to have a discussion on Index.

An index is a tool which enables investors to measure the performance of a group of stocks from a defined market. As there are numerous indices, investors can use them to compare their movement and have directional analysis. Sectoral indices are considered as lead indicator of the performance of a sector of an economy. It could also help investors to minimize their risk by using portfolio diversification strategies in order to balance down those with high risk (high returns) are balanced with those that are less risky (low returns). Ali, Abdullah and Azman (2011) states that sectoral indices serve as an indirect measure of the performance of the economy when studied as a whole. Therefore, the present study attempts to examine the effect of crisis on Indian economy by studying the various sectors of Indian economy by taking a sample of ten sectoral indices of Indian economy with S&P CNX Nifty.

OBJECTIVES OF THE STUDY

The study focuses on the following objectives:

* To examine the impact of global financial crisis on returns of sectoral indices in comparison to post and pre financial crisis era.

* To investigate which sectors are most affected by global financial meltdown.

* To know the effect of such changing sectoral dynamics on S&P CNX Nifty in comparison to post and pre financial crisis era.

RESEARCH METHODOLOGY

Data

The data consists of the daily closing prices of ten sectoral indices and S&P CNX Nifty for the period between 2005 to 2011 which is further sub-divided into three periods: before crisis (April 2005 to November 2007), during crisis (December 2007 to June 2009) and after crisis (July 2009 to March 2011 The daily closing prices have been transformed into a return series via the natural logarithm tool. The data for the indices has been collected from the NSE website www.nseindia.com for the whole period.

Sample

Table 3 shows the sectoral indices of the Indian Economy included in the sample selected for the study.

Tools of analysis

In order to accomplish the objectives, apart from Pictorial presentation and Descriptive Statistics, Multiple Regression-Stepwise Regression and Paired T-test have been used. Their discussion has been elucidated below:

(a) Multiple Regression-Stepwise Regression

It includes the relationship between a dependent or criterion variable (call it Y) and a set of k independent variables or potential predictor variables (call them X1, [X.sub.2], [X.sub.3], ..., [X.sub.k]), where the scores on all variables are measured for N cases.

The regression model fitted to the data is

[MATHEMATICAL EXPRESSION NOT REPRODUCIBLE IN ASCII]

where,

[Y.sub.i] is the dependent variable (S&P CNX Nifty), u is the error with mean zero.

A Step wise regression is designed to discover the maximum parsimonious set of predictors that are most effective in predicting the dependent variable. It is a method of computing OLS regression in stages. In stage one, independent variable which is best correlated with dependent variable is included in the equation. In the second stage, the remaining independent with the highest partial correlation with the dependent, controlling for the first independent is entered. The process is repeated at each stage partially for previously-entered independents, until the addition of a remaining independent does not increase R-square by a significant amount (or until all variables are entered). Kaur (2010) had applied the same test for analysing the factors causing recession.

(b) Paired t-test

Paired t-test is used to investigate which sectors are most affected by global recession. This test uses the difference between each of the paired variables and determines whether the result is statistically significant from 0. Thus, it is the difference within pairs, not between pairs, that is being tested. The form of the t-test for paired measurements is:

t = [[absolute value of [absolute value of [[bar.X].sub.d]] - [absolute value of [X.sub.O]]]/[[S.sub.d]/[square root of n]]]

where [X.sub.d] = Average of the differences between the individual split sample test results

[X.sub.0] = The value of the expected difference between split sample tests.

[S.sub.d] = Standard deviation of the differences between the split sample test results

n = Number of split samples (matched pairs)

EMPIRICAL RESULTS

(A) Effect of global financial meltdown on World Indices

Having started from the United States sub-prime mortgage market, the financial crisis spread quickly, infecting the entire United States financial system and almost simultaneously, spreading to the whole world due to globalisation. No market was spared from the hit of global recession which had been depicted in figure 1.

Figure 1 displays the effect of crisis on various stock markets of the World. It is found that the most affected Index is Dow Jones Industrial Average Index. The reason behind this that Dow Jones is a barometer of US economy, the birthplace of the Global Meltdown. Besides this, every economy is affected by the crisis as average return through the crisis period comes to negative except JKSE. But its return fall down as compared to pre and post financial crisis era. It implies that crisis had affected all economies of the world. S&P CNX Nifty which is the indicator of Indian economy is also affected by financial crisis as its average returns falls to negative during the era of global financial meltdown. In the next section, the most affected sectors of Indian economy will be studied.

[FIGURE 1 OMITTED]

(B) Effect of global financial meltdown on returns of Sectoral Indices of India

Almost all developing countries had experienced a severe slowdown of economic growth in mid-2008 due to financial crisis as obvious from figure 1. It is found in section-I that S&P CNX Nifty brought negative returns during the same period. Table 4 displays the effect of such meltdown on risk and return dynamics of sectors contributing Indian economy under study.

[TABLE 5 OMITTED]

Table 4 shows the descriptive statistical returns of sectoral indices of Indian economy under study. It can be seen that mean returns of all indices are negative during crisis period. The highest mean returns are generated by Infrastructure sector in before crisis period where as IT sector recorded lowest mean returns in before crisis period and highest mean returns in after crisis period. This indicates that IT sector rehabilitates itself from the crisis situation in a better way.

In during crisis period, pharma sector generated the highest mean returns among all sectoral indices This may be well-understood from the statement made Mr. Ajit Kamath Managing Director, Arch Pharma labs, "We don't see a slowdown in exports in the pharma sector. Demand has been robust, thanks to the very nature of the industry which is perceived to be the most defensive and inelastic sector as far as demand is concerned."

In the after crisis period all sectors display the positive return except Infrastructure which may imply that it takes time for the Infrastructure sector to recover from the crisis situation. Standard deviation, a measure of total risk is also revealed in table 4 which affirms that during the period of crisis, the risk of all sectors increased however it started diminishing when economy started reviving from the crisis situation. Since standard deviation is a measure of total risk, a detailed study, taking systematic risk (beta), has been conducted in the next section.

(C) Effect of the Global Financial Meltdown on Beta and Return simultaneously

Systematic risk is non-diversifiable risk that is influenced by the external considerations. It is not peculiar to a particular firm only however iparticular to the whole economy. Since financial meltdown had affected all economies of the world, thus, in this section effect of global financial meltdown on syatematic risk and return of sectoral indices had been studied simultaneously.

Table 5 displays that the systematic risk during the era of global financial meltdown had been amplified in every sector under the sample of Indian Economy and the same sectors recorded downward trend in their returns. As it can be seen from table 4 that return of all sectoral indices became negative in financial crisis period. Thus, every sector under sample of Indian economy faced a situation of increased systematic risk and simultaneously decline in their retuns, which reflects adverse effect of global financial metdown on Indian economy.

(D) Study of most affected sectors by global financial meltdown

Paired T-test is used to discover out which sectors are most affected by the Global Financial Meltdown. Through the Paired T-test, one must able to discover the statistically variance between the two paired samples. Here each sector of one period is paired with the S&P CNX Nifty of the same period.

Table 6 exhibits that significant results of t-statistic are found only in three sectors, i.e. Infrastructure, IT and pharma in before crises period. This implies that only these three sectors are significant in period before global financial meltdown. Results of during crisis period show that none of the sector shows significant results of t-statistic. This reflects that none of the sector is having the significant difference with S&P CNX Nifty as all sectors moved in same downward direction. The mean returns of all sectors during this period is found to be negative, thus, all sectors are affected by global financial meltdown. In after crisis period, two sectors show the significant t-statistic results, i.e. Infrastructure and IT. Thus Infrastructure and IT sectors are most affected by Global Financial Meltdown. However the Infrastructure industry is the most affected sector as its mean returns is found to be negative even after the period of Global Financial Crisis.

E) Effect of changing sectoral dynamics on S&P CNX Nifty

In complex regression situations, when there is a large number of an explanatory variable which may or may not be relevant for making predictions about the response variable, it is useful to be able to reduce the model to contain only the variables which provide important information about the response variable. But deciding which explanatory variables to include in the simpler model is not always trivial. Thus, we need a general methodology to select the 'best' model for the response variable. Here we have S&P CNX Nifty as response variable and sectoral indices as explanatory variables.

Table 7 shows that Infra sector is the finest predictor in determining the value of S&P CNX Nifty in both before and during the financial crisis period. Infra sector explained 93.5 % of total value of S&P CNX Nifty throughout the financial crisis period. In the period of after financial crisis, the finance sector has played the chief role and explained 84.2 % value of S&P CNX Nifty. Thus the Infra sector levied the highest influence on S&P CNX Nifty during the era of Global Financial Meltdown and the Finance sector after the global financial meltdown period.

The significance of beta is also found out by calculating T-value. Table 7 shows that T-values are important at 5 percent level of significance (shown in brackets) and thus beta is significant in all sectors during all periods.

With the adding up of one by one sector in each step, R-square is also growing. This shows that these sectors are significant in determining the value of S&P CNX Nifty. In the before financial crisis period, seven sectors are added to the regression equation which explained 97.5 percent of variation. Except media, Beta of all the other six sectors showed noteworthy results as t-value is positive for these sectors. The highest beta is shown by Infra sector, followed by IT and energy sector.

Similarly, in the during financial crisis period, 99.3 percent of variation in S&P CNX Nifty is explained by seven sectors. The highest influence on S&P CNX Nifty is denoted by energy sector, followed by Infra, finance and IT sector.

In the after crisis period, six sectors are added to the regression equation and they together explained the 98.4% of variation. Thus, it can be inferred that during the crisis period, sectors put maximum effect on S&P CNX nifty.

CONCLUSION

The study inspected the impact of the Global Financial Crisis on the returns of sectoral indices in contrast to the post and pre financial crisis era. It was found out that the Infrastructure sector was the most affected sector and Pharma sector was the least affected throughout the financial crisis as it produced the highest mean returns among all sectoral indices. The study further explored the most affected sectors by global financial meltdown but conducting the paired t-test it was found that only three sectors, i.e. Infrastructure, IT and Pharma had been significant in before crisis period. In after crisis period, two sectors, i.e. infrastructure and IT sector showed the significant results. Thus Infrastructure and IT sector were the two affected sector where infrastructure sector was the most affected one whose returns was negative even after the crisis period. Another effort was made to study the effect of changing sectoral dynamics on S&P CNX Nifty. This had been studied through step-wise regression. The results exposed that infrastructure sector explained 93.5 % of total value of S&P CNX Nifty, i.e. best predictor of S&P CNX Nifty during both before and after crisis period.

In the end, it is determined that recession entered in the Indian economy due to Globalization. All its sectors are affected by the crisis however the major impact is seen on mainly two sectors i.e. IT and Infra. The same impact on IT and Infra sector was found by Garg and Pandey (2008), Khan (2009), Vidyakala, Madhuvanthi and Poornima (2009), Kaur (2010), and Rao and Naikwadi (2010), thus, financial crisis had an adverse effect on the Indian economy. The results might help investors in choosing viable investment decision by guiding them against the most affected sectors due to the crisis and their improving trend towards the growth.

Notes for details

* [pounds sterling]--It denotes the Statement made by P. Chidambaram on April 12, 2008 to the International Monetary and Financial Committee, downloaded from www.imf.org/external/spring/ 2008/imfc/statement/eng/ind.pd

* [yen]--It indicates File "preview grid" downloaded from http://search.worldbank.org/data? qterm =gdp% 20growth%20rate&language=EN-on 13 may 2012

* [paragraph]--It denotes the statement made by Dr. Man Mohan Singh Quoted from newspaper, "The Times of India: Nov., 05,2008" downloaded from http:// articles.timesofindia.indiatimes.com/2008-11-03/ india-business/27920379_1_global-crisis-bank-deposits-banking-system

*--It indicates the Source of recession date taken from National bureau of economic research, downloaded from http://blogs.wsj.com/economics/ 2010/09/20/nber-recession-ended-in-june-2009/

* [epsilon]--It denotes the statement made by Mr. Ajit Kamath downloaded from http://www. expresspharmaonline.com/20081231/market 01. Shtml

List of Abbreviations

IMF--International Monetary Fund

JKSE--Jakarta Composite Index

KOSPI--The Korea Composite Stock Price Index

KLSE--Kaula Lampur Stock Exchange

OLS--Ordinary Least Square

Caption: Figure 1: Effect of crisis on returns of World Indices

Caption: Table 5: Effect of crisis on beta and return of sectoral indices

REFERENCES

[1.] Adamu, A., the Effects of Global Financial Crisis on Nigerian Economy (April 30, 2009). Retreived from http://ssrn.com/abstract=1397232 or http:// dx.doi.org/10.2139/ssrn.1397232

[2.] Angabini, A., & Wasiuzzaman, S. (2011). GARCH models and Financial Crisis--A study of Malayasian Stock market. International Journal of Applied Economics and Finance, 5(3), 226-236.

[3.] Aziz, G., Global Financial Crises and Its Effect on India (January 13, 2010). Available at http:// ssrn.com/abstract=1535854 or http://dx.doi.org/ 10.2139/ssrn.1535854.

[4.] Bera, S. K. (2010). Financial Crisis: The Incredible Hulk in Indian Economic Growth and External Sector. (MPRA Working Paper 27750). Retrieved from http://bit.ly/gxYFPS.

[5.] Cocozza, E., Colabella, A., & Spadafora, F. (2011). The Impact of Global crisis on South-Eastern Europe. IMF working paper WP/11/300. Available at http://www.imf.org/external/pubs/ft/wp/2011/ wp11300.pdf.

[6.] Jeeyanthi, B. J. Q., William, A., & Kalvathy, S. T. (2012). The impact of Global financial crisis on Indian Stock markets. International Journal of research in commerce & management, 3(2), 71-75.

[7.] Kaur, P. (2010). Impact of recession on India: A Sector-wise Analysis. Submitted to Thapar University, Patiala. Retrieved from http:// dspace.thapar.edu:8080/dspace/bitstream/10266/ 1133/3/1133.pdf.

[8.] Khan, A. Q., & Mehtab, M. (2010). Strategies and Opportunities for Indian Economy to Come Out Of the Impact of Global Economic Meltdown Morass. International Review of Business and Finance, 2(1), 1-27.

[9.] Kumar, R., & Vashisht, P. (2009). The Global Economic Crisis: Impact on India and Policy Responses. (ADBI Working Paper 164). India, Delhi: Asian Development Bank. Retrieved from http://bit.ly/gIQuVl.

[10.] Kundu, S. (2008). Can the Indian economy emerge unscathed from the global financial crisis? Retrieved from www.scribd.com/doc/57687877/ Global-Financial-Crisis-in-India.

[11.] Prasad, A., & Reddy, C. P. (2009). Global financial crisis and its impact on India. Journal of Social Science, 21(1), 1-5. Retrieved from http:// www.krepublishers.com/02-Journals/JSS/JSS-210-000-09-Web/JSS-21-1-000-09-Abst-PDF/JSS-21-1-001-09-963-%20Prasad-A/JSS- 21-1-001-09963-%20Prasad-A-Tt.pdf.

[12.] Rao, N. M., & Naikwadi, I. A. M. (2010). Impact of Global Financial Meltdown on Beta of Selected Scrips. The IUP Journal of Applied Economics, 9(1), 40-63.

[13.] Trade and development report. (2008). UNCTAD/ TDR/2008. Retrieved from unctad.org/en/docs/ tdr2008ch4_en.pdf.

[14.] Trade and development report. (2009). UNCTAD/ TDR/2009. Retrieved from unctad.org/en/docs/ tdr2009_en.pdf.

[15.] Vidyakala, K., Madhuvanthi, S., Impact of Global Financial Crisis on Indian Economy (October 27, 2009). Available at SSRN: http://ssrn.com/ abstract=1494903 or http://dx.doi.org/10.2139/ ssrn.1494903.

[16.] Vidyakala, K., Madhuvanthi, S., & Poornima, S., Recession in Indian Banking Sector (October 27, 2009). Available at SSRN: http://ssrn.com/ abstract=1494873 or http://dx.doi.org/10.2139/ ssrn.1494873.

* Multicolinearity has been checked through collinearity diagnostics and none of the variable shows significant value. Thus no linearity is present in the above data

(1) Trade and Development report (2009), Chapter-1, "The Impact of the Global Crisis and the Short-term Policy Response", pg-1

(2) Trade and Development report (2008), Chapter-IV, "Domestic sources of finance and investment in productive capacity", pg-108

(3) Trade and Development report (2009), Page-Ill

(4) Trade and Development report (2009), Chapter-1, "The Impact of the Global Crisis and the Short-term Policy Response", pg-1

(5) "India's Macroeconomic Challenges Some Reserve Bank Perspectives"--Fifth I.G. Patel Memorial Lecture delivered by Dr. Duvvuri Subbarao, Governor, Reserve Bank of India at the London School of Economics on March 13, 2013, Pg. 5.

Dr. Yash Pal Taneja, Assistant Professor, GGDSD College, Sector-32c, Chandigarh; e-mail: dryash.pal@gmail.com

Prof. Shipra Bansal, Assistant Professor, GGDSD College, Sector-32c, Chandigarh; e-mail: shiprabansal88@gmail.com

Table 1: Showing annual growth rate of various countries
of the WORLD

Country Name 2002 2003 2004 2005 2006 2007 2008

World 1.98 2.69 4.09 3.55 4.05 3.98 1.44
Japan 0.26 1.41 2.74 1.93 2.04 2.36 -1.17
India 3.77 8.37 8.28 9.32 9.27 9.82 4.93
China 9.10 10.00 10.10 11.30 12.70 14.20 9.60
UK 2.66 3.52 2.96 2.09 2.61 3.47 -1.10
United States 1.83 2.50 3.59 3.06 2.67 1.94 -0.02
France 0.93 0.90 2.54 1.83 2.47 2.29 -0.08
Germany 0.01 -0.38 1.16 0.68 3.70 3.27 1.08
Hong Kong 1.84 3.01 8.47 7.08 7.02 6.39 2.31
Singapore 4.24 4.60 9.24 7.38 8.70 8.77 1.49

Country Name 2009 2010

World -2.31 4.22
Japan -6.29 4.00
India 9.10 8.81
China 9.20 10.40
UK -4.37 2.09
United States -3.50 3.00
France -2.73 1.48
Germany -5.13 3.69
Hong Kong -2.66 6.97
Singapore -0.77 14.47

Source: World Bank file

Table 2: summarized review of literature

Research study Objective Tools

1. Angabini and To investigate the Descriptive
Wasiuzzaman volatility of Kuala statistics, ARCH and
(2011) Lumpur Composite GARCH (1, 1), EGARCH
 Index (KLCI) with (1, 1). GJR-
 regards to the GARCH(1,1) models
 financial crisis of
 2007-08

2. Cocozza, To found the impact Tabular presentation
Colabella and of global crisis on
Spadafora six south eastern
(2011) European countries

3. Adamu (2009) To examine the Theoretical
 influence of the explanation
 Global Financial
 Crisis on Nigerian
 economy

4. Bera (2010) To examine the Regression analysis,
 impact of current testing for
 world-wide recession stationary and ADF
 on India's growth test

5. Khanand To develop an T-test
Mehtab (2010) understanding of the
 global recession and
 To analyze its
 impact on the India
 economy by studying
 various economic
 indicators

6. Aziz (2010) To analyze the Tabular presentation
 effect of global
 recession on various
 macroeconomic
 variables

7. Kundu (2008) To study the impact Graphical
and Kumar and and analysis of the presentation
Vashisht (2009) global financial
 crisis on India's
 financial market and
 the real economy.

8. Kaur (2010) To analyze the Pictorial
 impact of recession presentation, OLS
 on various sectors and Stepwise
 of Indian economy regression method

9. Prasad and To investigate Theoretical
Reddy (2009) impact of crisis on explanation
 Indian economy

10. Vidyakala, To investigate the Pictorial
Madhuvanthi and effect of Global presentation
Poornima recession on various
(2009). sectors of Indian
 Economy

11.Raoand To examine the using average,
Naikwadi (2010) impact of global percentage and Karl
 financial meltdown Pearson correlation
 on beta of selected method
 companies

12. Jeeyanthi, To empirically T-test and Binary
William and examine the impact regression test,
Kalavathy (2012) of global financial wilcoxon rank sum
 crisis on Indian test and
 stock market return Kruskal-wallis
 and volatility H-test, Parkinson
 during the period model, Garman and
 April 2005 to March Klass modeland GARCH
 2010. model

Research study Results

 Impact on sectors No impact

1. Angabini and volatility was
Wasiuzzaman relatively
(2011) consistent from 2001
 to the year 2007 and
 increased in the
 middle of 2007 till
 2009

2. Cocozza, Exports declined,
Colabella and external debt and
Spadafora Trade deficit
(2011) increased

3. Adamu (2009) Fall in commodity
 prices, decline in
 export, lower
 portfolio and FDI
 inflow, fall in
 equity market,
 decline in
 remittance from
 abroad

4. Bera (2010) Slower growth of
 India's GDP ,
 imports, exports and
 FDI

5. Khanand Adverse effect on
Mehtab (2010) Export, import and
 Foreign reserves of
 India

6. Aziz (2010) Depletion in FII and
 foreign exchange
 reserves, slower
 growth of export and
 import of India

7. Kundu (2008) Slower GDP growth,
and Kumar and depreciation of
Vashisht (2009) rupee, high
 inflation and lower
 FII investment and
 foreign exchange
 reserves

8. Kaur (2010) Adverse effect on IT
 sector, FIIs, FDIs,
 Exports and imports
 of the Indian
 Economy

9. Prasad and Adverse effect on
Reddy (2009) India's IT, FII,
 Banking,
 Infrastructure and
 exports

10. Vidyakala, Decline in India's
Madhuvanthi and GDP, Exchange rate,
Poornima Trade deficit, ,
(2009). Banking and Retail
 sector

11.Raoand Adverse effect on Small effect on
Naikwadi (2010) Banking, cement, FMCG and
 automobile, steel retail sector
 and Infrastructure
 sectors

12. Jeeyanthi, No significant
William and impact on
Kalavathy (2012) Indian stock
 market return
 and volatility.

Table 3: Sectoral Indices included in the sample

Sr. No Sector Index Symbol

1 Banking Sector CNX Bank Bank
2 Energy sector CNX Energy Energy
3 Finance sector CNX Finance Finance
4 FMCG sector CNX FMCG FMCG
5 IT sector CNX IT IT
6 Media sector CNX Media Media
7 Metal sector CNX Metal Metal
8 MNC sector CNX MNC MNC
9 Pharmaceutical sector CNX Pharma Pharma
10 Infrastructure sector CNX Infrastructure Infrastructure

Table 4: Descriptive statistics of returns of sectoral indices

Sectors Before crisis During crisis

 Mean Standard Mean Standard
 Deviation Deviation

Bank 0.001427 .020195113 -0.00064 .034053214
Energy 0.001586 .016527524 -0.00057 .028695262
Finance 0.001748 .019085576 -0.0008 .03437850
FMCG 0.00109 .016015263 -3.83e-06 .019324166
IT 0.00061 * .017139783 -0.00062 .028732918
Media 0.001838 .019066629 -0.00197 * .028920771
Metal 0.002099 .028105069 -0.00132 .036742236
MNC 0.001325 .015089305 -0.00049 .021119839
Pharma 0.000602 .013816761 -0.00017 * .019077588
Infrastructure 0.002099 * .018184474 -0.0012 .030926535

Sectors After crisis

 Mean Standard
 Deviation

Bank 0.001063 .016224607
Energy 0.000284 .011560448
Finance 0.001004 .015621847
FMCG 0.001033 .011299149
IT 0.001628 * .014003133
Media 0.000526 .014081982
Metal 0.000868 .018858250
MNC 0.000722 .010557829
Pharma 0.001251 .010115123
Infrastructure -0.00032 * .013346589

Source: Authors' own work

Table 6: showing results of paired t-test

 Before crisis During crisis
 t-stat (p-value) t-stat (p-value)

Bank -0.24613 (0.402831) 0.161132 (0.436037)
Energy 0.216893 (0.414179) 0.460487 (0.322714)
Finance 0.617625 (0.268517) -0.04095 (0.483679)
FMCG -1.14798 (0.125694) 0.83703 (0.201549)
IT -2.37822 * (0.008838) 0.164419 (0.434744)
Media 0.54591 (0.292691) -1.21494 (0.112569)
Metal 0.865295 (0.193594) -0.5924 (0.276968)
MNC -0.74066 (0.229579) 0.440909 (0.329764)
Pharma -2.48525 * (0.006595) 0.630353 (0.26442)
Infrastructure 2.11686 * (0.01732) -1.00965 (0.156651)

 After crisis
 t-stat (p-value)

Bank 1.009974 (0.156533)
Energy -1.23703 (0.108369)
Finance 0.975628 (0.164894)
FMCG 0.707481 (0.239822)
IT 1.90619 * (0.02864)
Media -0.3355 (0.368705)
Metal 0.339557 (0.367176)
MNC 0.069166 (0.472445)
Pharma 1.184857 (0.118358)
Infrastructure -3.54728 * (0.000216)

Source: IBM SPSS statistics 19

* values in brackets show the p-value

* values without brackets show the t-statistic results

* t-values are significant at 5% level of significance

Table 7: showing results of step wise regression

 Before Crisis R-
 period Beta square
 (T-value)

Step-1 Infra .826 (53.027) .855

Step-2 Infra .638 (38.637) .910
 IT .299 (17.067)

Step-3 Infra .329 (16.694) .951
 IT .272 (20.860)
 Energy .410 (19.899)

Step-4 Infra .226 (12.612) .966
 IT .246 (22.425)
 Energy .359 (20.526)
 Finance .187 (14.534)

Step-5 Infra .188 (11.342) .972
 IT .230 (22.879)
 Energy .336 (20.995)
 Finance .172 (14.688)
 Fmcg .122 (10.298)

Step-6 Infra .163 (9.886) .974
 IT .223 (22.929)
 Energy .326 (21.125)
 Finance .169 (14.984)
 Fmcg .110 (9.527)
 Metal .042 (6.373)

Step-6 Infra .170 (10.139) .975
 IT .227 (23.039)
 Energy .326 (21.165)
 Finance .171 (15.175)
 Fmcg .114 (9.768)
 Metal .043 (6.554)
 Media .020 (-2.094)

 During crisis R-
 Period Beta square
 (T-value)

Step-1 Infra .852 (74.013) .935

Step-2 Infra .498 (23.173) .965
 Energy .415 (17.909)

Step-3 Infra .442 (26.642) .980
 Energy .352 (19.694)
 IT .168 (16.950)

Step-4 Infra .300 (21.609) .990
 Energy .340 (26.696)
 IT .140 (19.470)
 Finance .174 (19.303)

Step-5 Infra .266 (21.689) .993
 Energy .309 (27.437)
 IT .134 (21.522)
 Finance .164 (21.094)
 Metal .075 (11.671)

Step-6 Infra .266 (21.689) .993
 Energy .302 (27.011)
 IT .130 (20.925)
 Finance .161 (20.958)
 Metal .075 (11.992)
 Fmcg .035 (3.788)

Step-6 Infra .273 (22.606) .993
 Energy .303 (27.872)
 IT .127 (20.911)
 Finance .162 (21.711)
 Metal .082 (13.078)
 Fmcg .044 (4.800)
 Media .032 (-4.761)

 After Crisis R-
 Period Beta square
 (T-value)

Step-1 Finance .724 (48.176) .842

Step-2 Finance .443 (25.851) .921
 Infra .419 (20.849)

Step-3 Finance .390 (27.918) .950
 Infra .357 (21.887)
 IT .188 (16.174)

Step-4 Finance .342 (30.920) .971
 Infra .260 (18.972)
 IT .172 (19.089)
 Energy .236 (17.442)

Step-5 Finance .318 (32.678) .978
 Infra .237 (19.816)
 IT .161 (20.598)
 Energy .231 (19.772)
 Fmcg .118 (12.303)

Step-6 Finance .297 (34.674) .984
 Infra .197 (15.860)
 IT .152 (22.595)
 Energy .207 (20.239)
 Fmcg .105 (12.619)
 Metal .091 (12.384)

Step-6

Source: IBM SPSS statistics 19