The issue of return and volatility spillover across the stock markets of different countries has ... more The issue of return and volatility spillover across the stock markets of different countries has become important as return and volatility shock of one market is transmitted from one market to another in terms of information transmission. Present study using the AR(p)-GARCH(1,1) model has investigated the contemporaneous as well as the dynamic return and volatility spillovers from the US stock markets (represented by NYSE Composite Index) to its Indian counterpart (represented by Sensex) and vice versa. A bi-directional contemporaneous return spillover has been reported while a unidirectional dynamic return spillover from US to India is revealed. However, a bi-directional contemporaneous as well as dynamic volatility spillover effect between the two markets is observed barring in the post-crisis period when no dynamic volatility has been reported from the Indian stock market to US stock market.
The present study investigates whether the Indian Stock Market represented by BSE SENSEX is effic... more The present study investigates whether the Indian Stock Market represented by BSE SENSEX is efficient or not. An attempt has also been made to test the assumption of independent and identically distributed (i.i.d) in respect to market returns in terms of daily SENSEX return data, which is the most restrictive version of the random walk hypothesis. The result of unit root test shows that the daily SENSEX returns are random. Moreover, to capture the possible non-linearity in the time series data TARCH(1,1) model has been fitted. Furthermore, BDS test has been applied to Standardized residuals of the above estimated model to check whether they are i.i.d. or not. The estimated result of the said test clearly indicates that null hypothesis of i.i.d. could not be rejected. Hence, it could be concluded that daily SENSEX returns follow Random Walk Model-I as described by Campbell et al (1997) and in general Indian Stock Market is efficient in its weak form during the study period.
The present study has sought to investigate the issue of day-of-the-week effect in Indian stock m... more The present study has sought to investigate the issue of day-of-the-week effect in Indian stock market. Applying GARCH-M model on the daily NIFTY returns data, a comparative study has been conducted to observe whether there is any difference between two sub-periods that is the period representing before the introduction of the T+2 rolling settlement and that of representing after the introduction of such system respectively regarding day-of-the-week effect in Indian stock market. The findings of the study clearly indicate that there was day-of-the-week effect in the daily NIFTY return during the pre T+2 rolling settlement period. But, such effect vanishes after the introduction of T+2 rolling settlement. However, a significant day-of-the-week effect remains in conditional volatility in the second sub-periods particularly in case of Tuesday. Application of TGARCH model has confirmed the above results.
Efficient Market Hypothesis proposes that it is not possible to outperform the market through mar... more Efficient Market Hypothesis proposes that it is not possible to outperform the market through market timing. However, research studies over the years have reported several anomalies in stock market returns. Anomalies that are linked to a particular time are called calendar effects.The month-of-the-year effect or particularly the January effect is one of such anomalies. The present study in this context has sought to address the issue of the month-of-the-year effect in Indian Stock Market represented by BSE SENSEX during the period ranging from January 2, 2004 to December 28, 2012. The GARCH(1,1)-M model has been used to model the conditional volatility. The results indicate the presence of September and November effects in the SENSEX returns during the study period. Moreover, in the volatility equation the coefficients of March, June, August, October, November and December dummy variables are negative and significant. Hence, it is confirmed that the month-of-the year effect is also present in the variance (volatility or risk) equation.
The present study has tried to explore a few stylized facts regarding the volatility of daily ret... more The present study has tried to explore a few stylized facts regarding the volatility of daily returns of S&P CNX NSE NIFTY. Highly significant JB statistic confirms that the return series is not normally distributed. Moreover, clear evidence of volatility clustering could be observed during the study period. Furthermore EGARCH (1, 1) model has been used to compute conditional variance of the NIFTY daily returnsof the sample period. The empirical results confirm that above model is a good fit and it clearly indicates that volatility in NSE persists over a long period. The empirical results establish that news asymmetry and Leverage Effect are present in this market. Finally, it has been clearly established that the recent sub-prime crisis has significant effect on the daily returns and volatility of S&P CNX NSE NIFTY.
Efficient Market Hypothesis proposes that it is not possible to outperform the market through mar... more Efficient Market Hypothesis proposes that it is not possible to outperform the market through market timing. However, research studies over the years have reported several anomalies in stock market returns. Anomalies that are linked to a particular time are called calendar effects.The month-of-the-year effect or particularly the January effect is one of such anomalies. The present study in this context has sought to address the issue of the month-of-the-year effect in Indian Stock Market represented by BSE SENSEX during the period ranging from January 2, 2004 to December 28, 2012. The GARCH(1,1)-M model has been used to model the conditional volatility. The results indicate the presence of September and November effects in the SENSEX returns during the study period. Moreover, in the volatility equation the coefficients of March, June, August, October, November and December dummy variables are negative and significant. Hence, it is confirmed that the month-of-the year effect is also present in the variance (volatility or risk) equation.
This study investigated the relationship between daily returns and illiquidity of the NIFTY Index... more This study investigated the relationship between daily returns and illiquidity of the NIFTY Index (one of the broad based market indices of the National Stock Exchange of India). In this paper, illiquidity was used as an exogenous variable in the EGARCH (1, 1) framework. The empirical results clearly indicate the presence of a liquidity premium in the National Stock Exchange of India, as evidenced by the positive relationship between illiquidity and returns of the NIFTY Index. They also imply a relationship between liquidity and volatility since illiquidity was used as an exogenous variable in estimating the mean equation and hence it influenced the values of the residuals. The lags of residuals, lags of conditional standard deviation, and lags of conditional variance in turn were inputs in the determination of (the natural logarithm of) conditional variance in the EGARCH framework.
The present study investigates whether the Indian Stock Market represented by BSE SENSEX is effic... more The present study investigates whether the Indian Stock Market represented by BSE SENSEX is efficient or not. An attempt has also been made to test the assumption of independent and identically distributed (i.i.d) in respect to market returns in terms of daily SENSEX return data, which is the most restrictive version of the random walk hypothesis. The result of unit root test shows that the daily SENSEX returns are random. Moreover, to capture the possible non-linearity in the time series data TARCH(1,1) model has been fitted. Furthermore, BDS test has been applied to Standardized residuals of the above estimated model to check whether they are i.i.d. or not. The estimated result of the said test clearly indicates that null hypothesis of i.i.d. could not be rejected. Hence, it could be concluded that daily SENSEX returns follow Random Walk Model-I as described by Campbell et al (1997) and in general Indian Stock Market is efficient in its weak form during the study period.
The present study has sought to investigate the issue of day-of-the-week effect in Indian stock m... more The present study has sought to investigate the issue of day-of-the-week effect in Indian stock market. Applying GARCH-M model on the daily NIFTY returns data, a comparative study has been conducted to observe whether there is any difference between two sub-periods that is the period representing before the introduction of the T+2 rolling settlement and that of representing after the introduction of such system respectively regarding day-of-the-week effect in Indian stock market. The findings of the study clearly indicate that there was day-of-the-week effect in the daily NIFTY return during the pre T+2 rolling settlement period. But, such effect vanishes after the introduction of T+2 rolling settlement. However, a significant day-of-the-week effect remains in conditional volatility in the second sub-periods particularly in case of Tuesday. Application of TGARCH model has confirmed the above results.
The issue of return and volatility spillover across the stock markets of different countries has ... more The issue of return and volatility spillover across the stock markets of different countries has become important as return and volatility shock of one market is transmitted from one market to another in terms of information transmission. Present study using the AR(p)-GARCH(1,1) model has investigated the contemporaneous as well as the dynamic return and volatility spillovers from the US stock markets (represented by NYSE Composite Index) to its Indian counterpart (represented by Sensex) and vice versa. A bi-directional contemporaneous return spillover has been reported while a unidirectional dynamic return spillover from US to India is revealed. However, a bi-directional contemporaneous as well as dynamic volatility spillover effect between the two markets is observed barring in the post-crisis period when no dynamic volatility has been reported from the Indian stock market to US stock market.
The turmoil in the international financial markets of advanced economies that started around mid-... more The turmoil in the international financial markets of advanced economies that started around mid-2007 and intensified substantially since August 2008 had engulfed many developed and emerging countries within its blaze. India, a great example of an emerging economy was not far away from the heat. The present study in this context attempted to examine whether there was any significant change in the behaviour of share price synchronicity of the Indian Public Sector Banks during the crisis period in compare to pre and post crisis period or not. It was found that Indian Public Sector Banks " stock prices were more aligned to the market during the crisis period compared to the pre crisis and the post crisis period. _______________________________________________________________________________
The present study has tried to explore a few stylized facts regarding the volatility of daily ret... more The present study has tried to explore a few stylized facts regarding the volatility of daily returns of S&P CNX NSE NIFTY. Highly significant JB statistic confirms that the return series is not normally distributed. Moreover, clear evidence of volatility clustering could be observed during the study period. Furthermore EGARCH (1, 1) model has been used to compute conditional variance of the NIFTY daily returnsof the sample period. The empirical results confirm that above model is a good fit and it clearly indicates that volatility in NSE persists over a long period. The empirical results establish that news asymmetry and Leverage Effect are present in this market. Finally, it has been clearly established that the recent sub-prime crisis has significant effect on the daily returns and volatility of S&P CNX NSE NIFTY.
Stock market volatility has attracted growing attentions from scholars, policy makers and practit... more Stock market volatility has attracted growing attentions from scholars, policy makers and practitioners due to its impact on decision making. Present study in this context tries to explore the features of daily returns of BSE SENSEX and the conditional volatility of the same. Highly significant large JB-statistic confirms that the return series is not normally distributed. The return series is leptokurtic and returns are serially correlated. It appears that volatility clustering is present during the study period. Furthermore, GARCH (1, 1) model has been applied to compute conditional variance of the sample data. The empirical results show that above model is a good fit and it has also been established that volatility in this market persists over a long period of time. A large sum of coefficients implies that a large positive or a large negative return leads future forecasts of the variance to be high for a prolonged period. To capture the leverage effect present study has applied TARCH(1,1) model. From the empirical result it appears that news asymmetry and leverage effect are present in the market.
Efficient Market Hypothesis proposes that it is not possible to outperform the market through mar... more Efficient Market Hypothesis proposes that it is not possible to outperform the market through market timing. However, research studies over the years have reported several anomalies in stock market returns. Anomalies that are linked to a particular time are called calendar effects.The month-of-the-year effect or particularly the January effect is one of such anomalies. The present study in this context has sought to address the issue of the month-of-the-year effect in Indian Stock Market represented by BSE SENSEX during the period ranging from January 2, 2004 to December 28, 2012. The GARCH(1,1)-M model has been used to model the conditional volatility. The results indicate the presence of September and November effects in the SENSEX returns during the study period. Moreover, in the volatility equation the coefficients of March, June, August, October, November and December dummy variables are negative and significant. Hence, it is confirmed that the month-of-the year effect is also present in the variance (volatility or risk) equation.
The turmoil in the international financial markets of advanced economies that started around mid-... more The turmoil in the international financial markets of advanced economies that started around mid-2007 and intensified substantially since August 2008 had engulfed many developed and emerging countries within its blaze. India, a great example of an emerging economy was not far away from the heat. The present study in this context attempted to examine whether there was any significant change in the behaviour of share price synchronicity of the Indian Public Sector Banks during the crisis period in compare to pre and post crisis period or not. It was found that Indian Public Sector Banks " stock prices were more aligned to the market during the crisis period compared to the pre crisis and the post crisis period. _______________________________________________________________________________
This study investigated the relationship between daily returns and illiquidity of the NIFTY Index... more This study investigated the relationship between daily returns and illiquidity of the NIFTY Index (one of the broad based market indices of the National Stock Exchange of India). In this paper, illiquidity was used as an exogenous variable in the EGARCH (1, 1) framework. The empirical results clearly indicate the presence of a liquidity premium in the National Stock Exchange of India, as evidenced by the positive relationship between illiquidity and returns of the NIFTY Index. They also imply a relationship between liquidity and volatility since illiquidity was used as an exogenous variable in estimating the mean equation and hence it influenced the values of the residuals. The lags of residuals, lags of conditional standard deviation, and lags of conditional variance in turn were inputs in the determination of (the natural logarithm of) conditional variance in the EGARCH framework.
The issue of return and volatility spillover across the stock markets of different countries has ... more The issue of return and volatility spillover across the stock markets of different countries has become important as return and volatility shock of one market is transmitted from one market to another in terms of information transmission. Present study using the AR(p)-GARCH(1,1) model has investigated the contemporaneous as well as the dynamic return and volatility spillovers from the US stock markets (represented by NYSE Composite Index) to its Indian counterpart (represented by Sensex) and vice versa. A bi-directional contemporaneous return spillover has been reported while a unidirectional dynamic return spillover from US to India is revealed. However, a bi-directional contemporaneous as well as dynamic volatility spillover effect between the two markets is observed barring in the post-crisis period when no dynamic volatility has been reported from the Indian stock market to US stock market.
The present study investigates whether the Indian Stock Market represented by BSE SENSEX is effic... more The present study investigates whether the Indian Stock Market represented by BSE SENSEX is efficient or not. An attempt has also been made to test the assumption of independent and identically distributed (i.i.d) in respect to market returns in terms of daily SENSEX return data, which is the most restrictive version of the random walk hypothesis. The result of unit root test shows that the daily SENSEX returns are random. Moreover, to capture the possible non-linearity in the time series data TARCH(1,1) model has been fitted. Furthermore, BDS test has been applied to Standardized residuals of the above estimated model to check whether they are i.i.d. or not. The estimated result of the said test clearly indicates that null hypothesis of i.i.d. could not be rejected. Hence, it could be concluded that daily SENSEX returns follow Random Walk Model-I as described by Campbell et al (1997) and in general Indian Stock Market is efficient in its weak form during the study period.
The present study has sought to investigate the issue of day-of-the-week effect in Indian stock m... more The present study has sought to investigate the issue of day-of-the-week effect in Indian stock market. Applying GARCH-M model on the daily NIFTY returns data, a comparative study has been conducted to observe whether there is any difference between two sub-periods that is the period representing before the introduction of the T+2 rolling settlement and that of representing after the introduction of such system respectively regarding day-of-the-week effect in Indian stock market. The findings of the study clearly indicate that there was day-of-the-week effect in the daily NIFTY return during the pre T+2 rolling settlement period. But, such effect vanishes after the introduction of T+2 rolling settlement. However, a significant day-of-the-week effect remains in conditional volatility in the second sub-periods particularly in case of Tuesday. Application of TGARCH model has confirmed the above results.
Efficient Market Hypothesis proposes that it is not possible to outperform the market through mar... more Efficient Market Hypothesis proposes that it is not possible to outperform the market through market timing. However, research studies over the years have reported several anomalies in stock market returns. Anomalies that are linked to a particular time are called calendar effects.The month-of-the-year effect or particularly the January effect is one of such anomalies. The present study in this context has sought to address the issue of the month-of-the-year effect in Indian Stock Market represented by BSE SENSEX during the period ranging from January 2, 2004 to December 28, 2012. The GARCH(1,1)-M model has been used to model the conditional volatility. The results indicate the presence of September and November effects in the SENSEX returns during the study period. Moreover, in the volatility equation the coefficients of March, June, August, October, November and December dummy variables are negative and significant. Hence, it is confirmed that the month-of-the year effect is also present in the variance (volatility or risk) equation.
The present study has tried to explore a few stylized facts regarding the volatility of daily ret... more The present study has tried to explore a few stylized facts regarding the volatility of daily returns of S&P CNX NSE NIFTY. Highly significant JB statistic confirms that the return series is not normally distributed. Moreover, clear evidence of volatility clustering could be observed during the study period. Furthermore EGARCH (1, 1) model has been used to compute conditional variance of the NIFTY daily returnsof the sample period. The empirical results confirm that above model is a good fit and it clearly indicates that volatility in NSE persists over a long period. The empirical results establish that news asymmetry and Leverage Effect are present in this market. Finally, it has been clearly established that the recent sub-prime crisis has significant effect on the daily returns and volatility of S&P CNX NSE NIFTY.
Efficient Market Hypothesis proposes that it is not possible to outperform the market through mar... more Efficient Market Hypothesis proposes that it is not possible to outperform the market through market timing. However, research studies over the years have reported several anomalies in stock market returns. Anomalies that are linked to a particular time are called calendar effects.The month-of-the-year effect or particularly the January effect is one of such anomalies. The present study in this context has sought to address the issue of the month-of-the-year effect in Indian Stock Market represented by BSE SENSEX during the period ranging from January 2, 2004 to December 28, 2012. The GARCH(1,1)-M model has been used to model the conditional volatility. The results indicate the presence of September and November effects in the SENSEX returns during the study period. Moreover, in the volatility equation the coefficients of March, June, August, October, November and December dummy variables are negative and significant. Hence, it is confirmed that the month-of-the year effect is also present in the variance (volatility or risk) equation.
This study investigated the relationship between daily returns and illiquidity of the NIFTY Index... more This study investigated the relationship between daily returns and illiquidity of the NIFTY Index (one of the broad based market indices of the National Stock Exchange of India). In this paper, illiquidity was used as an exogenous variable in the EGARCH (1, 1) framework. The empirical results clearly indicate the presence of a liquidity premium in the National Stock Exchange of India, as evidenced by the positive relationship between illiquidity and returns of the NIFTY Index. They also imply a relationship between liquidity and volatility since illiquidity was used as an exogenous variable in estimating the mean equation and hence it influenced the values of the residuals. The lags of residuals, lags of conditional standard deviation, and lags of conditional variance in turn were inputs in the determination of (the natural logarithm of) conditional variance in the EGARCH framework.
The present study investigates whether the Indian Stock Market represented by BSE SENSEX is effic... more The present study investigates whether the Indian Stock Market represented by BSE SENSEX is efficient or not. An attempt has also been made to test the assumption of independent and identically distributed (i.i.d) in respect to market returns in terms of daily SENSEX return data, which is the most restrictive version of the random walk hypothesis. The result of unit root test shows that the daily SENSEX returns are random. Moreover, to capture the possible non-linearity in the time series data TARCH(1,1) model has been fitted. Furthermore, BDS test has been applied to Standardized residuals of the above estimated model to check whether they are i.i.d. or not. The estimated result of the said test clearly indicates that null hypothesis of i.i.d. could not be rejected. Hence, it could be concluded that daily SENSEX returns follow Random Walk Model-I as described by Campbell et al (1997) and in general Indian Stock Market is efficient in its weak form during the study period.
The present study has sought to investigate the issue of day-of-the-week effect in Indian stock m... more The present study has sought to investigate the issue of day-of-the-week effect in Indian stock market. Applying GARCH-M model on the daily NIFTY returns data, a comparative study has been conducted to observe whether there is any difference between two sub-periods that is the period representing before the introduction of the T+2 rolling settlement and that of representing after the introduction of such system respectively regarding day-of-the-week effect in Indian stock market. The findings of the study clearly indicate that there was day-of-the-week effect in the daily NIFTY return during the pre T+2 rolling settlement period. But, such effect vanishes after the introduction of T+2 rolling settlement. However, a significant day-of-the-week effect remains in conditional volatility in the second sub-periods particularly in case of Tuesday. Application of TGARCH model has confirmed the above results.
The issue of return and volatility spillover across the stock markets of different countries has ... more The issue of return and volatility spillover across the stock markets of different countries has become important as return and volatility shock of one market is transmitted from one market to another in terms of information transmission. Present study using the AR(p)-GARCH(1,1) model has investigated the contemporaneous as well as the dynamic return and volatility spillovers from the US stock markets (represented by NYSE Composite Index) to its Indian counterpart (represented by Sensex) and vice versa. A bi-directional contemporaneous return spillover has been reported while a unidirectional dynamic return spillover from US to India is revealed. However, a bi-directional contemporaneous as well as dynamic volatility spillover effect between the two markets is observed barring in the post-crisis period when no dynamic volatility has been reported from the Indian stock market to US stock market.
The turmoil in the international financial markets of advanced economies that started around mid-... more The turmoil in the international financial markets of advanced economies that started around mid-2007 and intensified substantially since August 2008 had engulfed many developed and emerging countries within its blaze. India, a great example of an emerging economy was not far away from the heat. The present study in this context attempted to examine whether there was any significant change in the behaviour of share price synchronicity of the Indian Public Sector Banks during the crisis period in compare to pre and post crisis period or not. It was found that Indian Public Sector Banks " stock prices were more aligned to the market during the crisis period compared to the pre crisis and the post crisis period. _______________________________________________________________________________
The present study has tried to explore a few stylized facts regarding the volatility of daily ret... more The present study has tried to explore a few stylized facts regarding the volatility of daily returns of S&P CNX NSE NIFTY. Highly significant JB statistic confirms that the return series is not normally distributed. Moreover, clear evidence of volatility clustering could be observed during the study period. Furthermore EGARCH (1, 1) model has been used to compute conditional variance of the NIFTY daily returnsof the sample period. The empirical results confirm that above model is a good fit and it clearly indicates that volatility in NSE persists over a long period. The empirical results establish that news asymmetry and Leverage Effect are present in this market. Finally, it has been clearly established that the recent sub-prime crisis has significant effect on the daily returns and volatility of S&P CNX NSE NIFTY.
Stock market volatility has attracted growing attentions from scholars, policy makers and practit... more Stock market volatility has attracted growing attentions from scholars, policy makers and practitioners due to its impact on decision making. Present study in this context tries to explore the features of daily returns of BSE SENSEX and the conditional volatility of the same. Highly significant large JB-statistic confirms that the return series is not normally distributed. The return series is leptokurtic and returns are serially correlated. It appears that volatility clustering is present during the study period. Furthermore, GARCH (1, 1) model has been applied to compute conditional variance of the sample data. The empirical results show that above model is a good fit and it has also been established that volatility in this market persists over a long period of time. A large sum of coefficients implies that a large positive or a large negative return leads future forecasts of the variance to be high for a prolonged period. To capture the leverage effect present study has applied TARCH(1,1) model. From the empirical result it appears that news asymmetry and leverage effect are present in the market.
Efficient Market Hypothesis proposes that it is not possible to outperform the market through mar... more Efficient Market Hypothesis proposes that it is not possible to outperform the market through market timing. However, research studies over the years have reported several anomalies in stock market returns. Anomalies that are linked to a particular time are called calendar effects.The month-of-the-year effect or particularly the January effect is one of such anomalies. The present study in this context has sought to address the issue of the month-of-the-year effect in Indian Stock Market represented by BSE SENSEX during the period ranging from January 2, 2004 to December 28, 2012. The GARCH(1,1)-M model has been used to model the conditional volatility. The results indicate the presence of September and November effects in the SENSEX returns during the study period. Moreover, in the volatility equation the coefficients of March, June, August, October, November and December dummy variables are negative and significant. Hence, it is confirmed that the month-of-the year effect is also present in the variance (volatility or risk) equation.
The turmoil in the international financial markets of advanced economies that started around mid-... more The turmoil in the international financial markets of advanced economies that started around mid-2007 and intensified substantially since August 2008 had engulfed many developed and emerging countries within its blaze. India, a great example of an emerging economy was not far away from the heat. The present study in this context attempted to examine whether there was any significant change in the behaviour of share price synchronicity of the Indian Public Sector Banks during the crisis period in compare to pre and post crisis period or not. It was found that Indian Public Sector Banks " stock prices were more aligned to the market during the crisis period compared to the pre crisis and the post crisis period. _______________________________________________________________________________
This study investigated the relationship between daily returns and illiquidity of the NIFTY Index... more This study investigated the relationship between daily returns and illiquidity of the NIFTY Index (one of the broad based market indices of the National Stock Exchange of India). In this paper, illiquidity was used as an exogenous variable in the EGARCH (1, 1) framework. The empirical results clearly indicate the presence of a liquidity premium in the National Stock Exchange of India, as evidenced by the positive relationship between illiquidity and returns of the NIFTY Index. They also imply a relationship between liquidity and volatility since illiquidity was used as an exogenous variable in estimating the mean equation and hence it influenced the values of the residuals. The lags of residuals, lags of conditional standard deviation, and lags of conditional variance in turn were inputs in the determination of (the natural logarithm of) conditional variance in the EGARCH framework.
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Papers by Dr. Som Sankar Sen
(one of the broad based market indices of the National Stock Exchange of India). In this paper,
illiquidity was used as an exogenous variable in the EGARCH (1, 1) framework. The empirical
results clearly indicate the presence of a liquidity premium in the National Stock Exchange of
India, as evidenced by the positive relationship between illiquidity and returns of the NIFTY
Index. They also imply a relationship between liquidity and volatility since illiquidity was used
as an exogenous variable in estimating the mean equation and hence it influenced the values of
the residuals. The lags of residuals, lags of conditional standard deviation, and lags of
conditional variance in turn were inputs in the determination of (the natural logarithm of)
conditional variance in the EGARCH framework.
(one of the broad based market indices of the National Stock Exchange of India). In this paper,
illiquidity was used as an exogenous variable in the EGARCH (1, 1) framework. The empirical
results clearly indicate the presence of a liquidity premium in the National Stock Exchange of
India, as evidenced by the positive relationship between illiquidity and returns of the NIFTY
Index. They also imply a relationship between liquidity and volatility since illiquidity was used
as an exogenous variable in estimating the mean equation and hence it influenced the values of
the residuals. The lags of residuals, lags of conditional standard deviation, and lags of
conditional variance in turn were inputs in the determination of (the natural logarithm of)
conditional variance in the EGARCH framework.