Nikunjkumar Patel - Institute of Management, Nirma Unoversity

Nikunjkumar Patel - Institute of Management, Nirma Unoversity
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Nikunjkumar Patel
Institute of Management, Nirma Unoversity
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Prof. Nikunj Patel holds MBA in Finance from the HNGU, Patan. He has almost thirteen years of standing in his academic career. Currently, he is working with Institute of Management, Nirma University, Ahmedabad, His areas of teaching and research include Accounting, Financial Management, Security Analysis and Portfolio Management, Behavioural Finance and International Finance. He has also acted as a resource person in several faculty development and Management development programmes.
Phone:
+91-9825674507
A/6, Akshardham Township,
Near Sahajanand School,
Visnagar - 384315,
Dist. Mehsana,
Gujarat, India
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Papers by Nikunjkumar Patel
VOLATILITY ANALYSIS AND VOLATILITY SPILLOVER ACROSS EQUITY MARKETS BETWEEN INDIA AND EUROPE
by
Nikunjkumar Patel
Nisarg Joshi
, and
Bhavesh Patel
D:\Probable Research Files\SMART Journal of Business Management Studies
, 2021
This paper is a comparative study of volatility spillover effects in India and European indices.T...
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This paper is a comparative study of volatility spillover effects in India and European indices.The analysis used various GARCH models, in order to measure conditional volatility (GARCH), asymmetric effect in the conditional volatility (T-GARCH), volatility persistence in conditional volatility (E-GARCH), impact of conditional volatility on conditional returns (M-GARCH) and volatility spillover (GARCH (1, 1), with exogenous variable, for the period 2005 to 2018. The major results, regarding volatility spillover, revealed that Indian stock market had exercised strong impact on selected European indices. Volatility spillover was found to be from Indian stock market to European indices and vice-versa. According to the T-GARCH model, there was significant asymmetric effect on the conditional volatility. The results of E-GARCH model established volatility persistence in conditional volatility.
CAUSALITY AND COINTEGRATION AMONG STOCK MARKET INDICES: A STUDY OF DEVELOPED MARKETS WITH SENSEX
by
Nikunjkumar Patel
and
Bhavesh Patel
International Journal of Accounting & Finance Review
, 2021
The aim of this paper is to examine the existence of degree of interdependence between Sensex and...
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The aim of this paper is to examine the existence of degree of interdependence between Sensex and various stock markets of the American and European regions. The study attempts to analyse the dynamic interactions among 22 global indices. The daily closing prices of indices were obtained from the respective stock exchange websites from January 2005 to May 2018. The normality, stationarity, and causality of the time series were evaluated in the first section using statistical techniques such as the Jarque-Bera statistic, ADF test, and Granger Causality test. The second part of the approach focused on analysing the interdependencies of various stock markets, determining the degree of association, and measuring market efficiency using techniques such as Johansen's Cointegration test, Cross-Correlation test, and Hurst Exponent. The results indicate that there is a significant amount of interdependence between stock markets. It was also observed that there is an association between markets. This study also found bi-directional as well as uni-directional causality among the stock market indices. The study found that interdependence of markets leads to improvements in short-term as well as long-term returns/gains for investors possibly due to international portfolio diversification if there are stronger co-movements of prices across the markets.
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SENSEX had the highest mean daily return (0.06) among global indices studied, indicating strong performance.
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The impact of economic growth, trade openness and manufacturing on CO2 emissions in India: an autoregressive distributive lag (ARDL) bounds test approach
Journal of Economics, Finance and Administrative Science
, 2021
Purpose-The purpose of this study is to examine the impact of economic growth, trade openness and...
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Purpose-The purpose of this study is to examine the impact of economic growth, trade openness and manufacturing on CO2 emissions in India. Design/methodology/approach-The study employed autoregressive distributive lag (ARDL) bounds test approach and uses CO2 emissions, trade, manufacturing and GDP per capita to examine the relationship using an annual time series data from World Development Indicators during 1971 to 2016. Findings-Results depict that there exists a long-run relationship between CO2 emissions and other variables. Trade openness significantly reduces CO2 emissions, whereas manufacturing and GDP have a significant and positive impact on CO2 in the long run. Research limitations/implications-The findings of the study contribute to the body of knowledge by providing new evidence on the relationship between developmental metrics and the environment. These findings are critical for policymakers and regulatory bodies to focus on economic development without jeopardizing environmental degradation. Practical implications-In order to keep its commitment to sustainability, India needs to develop policies that encourage cleaner production methods and establishment of non-polluting industries. Simultaneously, it must disincentivize industries that emit CO2 by policy frameworks such as carbon taxes, pollution taxes or green taxes. Originality/value-None of studies examine at how these environmental factors interact in India. Kilavuz and Dogan (2020) used the same variables, but their scope was limited to Turkey. As a result, the study is the first to examine this relationship for India, contributing to the body of knowledge on economic growth, manufacturing, trade openness and environmental concerns.
Integration of stock markets using autoregressive distributed lag bounds test approach
by
Nikunjkumar Patel
and
Bhavesh Patel
Global Business and Economics Review
, 2022
Financial integration plays a decisive role to the institutional investors for diversification of...
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Financial integration plays a decisive role to the institutional investors for diversification of their investment portfolio(s). This research investigates the integration of selected stock markets (India, Australia, China, Spain, UK, and the USA) from different continents that are highly affected by COVID-19, employing the autoregressive distributed lag approach using daily data from 2 January 2011 to 7 May 2020. The outcomes show evidence of long and short-run integration among the markets. The rest of the markets are co-integrated with the markets of India, China, and UK. India has long-run equilibrium with the USA and Spain, whereas China has long-run association with Spain, and the UK has a long-run association with the USA. In short-run, India is positively influenced by the returns of rest of the markets, whereas all the markets under the study except USA influence China. Further, the UK's market is significantly inclined negatively by its own past innovations.
Study of Efficiency of Index Futures, Lead-Lag Relationship and Speed of Adjustments in India using High-Frequency Data
Indian Journal of Finance
, 2020
We conduct a rigorous analysis to find out the speed of adjustments in futures and spot indices o...
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We conduct a rigorous analysis to find out the speed of adjustments in futures and spot indices on NSE NIFTY 50 in short run as a part of examining the efficiency of financial futures market in India. Towards that, we undertake the analysis of long run and short run efficiencies separately, and use Engle-Granger's Error Correction Mechanism (ECM) so that a clear picture of short run efficiency in terms of speed of adjustments can emerge. The rigour manifests in the analysis of 412538 data points that breed from (i) the choice of five different time intervals spanning from 1-minute to 120-minutes using high frequency data, and (ii) examining 100 lags of 1-minute interval. Long run efficiency is a precondition for examining short run efficiency. We document an excellent state of affairs for long run efficiency across all five intervals of time. Most of the price discovery takes place in futures market, and the spot market follows it with a lag of 9 minutes, effectively. However, it takes 35 minutes to completely return to the desired relationship once a drift has taken place. The increase in the speed of adjustments, as compared to the speed documented in previous studies can be attributed to the large-scale adoption of the high frequency (i.e. algorithmic) trading, in recent times. Our findings suggest that traders can effectively use the near month contract of NIFTY 50 Futures to hedge their open positions in the index or any other stock. JEL Classification: G10, G14, G19
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Increased adjustment speed attributed to algorithmic trading enables effective hedging with NIFTY 50 Futures.
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Calendar anomalies: a survey of the literature
The specific purpose of this paper is to investigate the empirical evidence of stock price anomal...
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The specific purpose of this paper is to investigate the empirical evidence of stock price anomalies, especially day-of-the-week, month-of-the-year and the holiday effect. The review covers the critical evaluation of calendar anomalies, and the major focus has been given to extensively cited papers. Most of the researchers have found evidence of a negative Monday effect, though a relatively small number of researchers have refuted these results. We found a clear indication of a January effect in developed stock markets; however, there was no consensus in developing and least developed countries. Most of the researchers found a strong pre-holiday effect in the majority of markets; however, a few researchers found that the pre-holiday effect has diminished. The research could be extended to include other calendar anomalies such as the turn-of-the-month effect and semi-month effect. This research is helpful to all stakeholders of the stock market, specifically to regulators for maintaining market efficiency.
Weak Form of Market Efficiency of Metal Commodities in India
International Journal of Applied Financial Management Perspectives
, Sep 1, 2014
The aim of this paper is to examine the impact of Information Efficiency on Metal commodities nam...
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The aim of this paper is to examine the impact of Information Efficiency on Metal commodities namely Aluminium, Copper and Nickel. This study also examines the volatility in the prices of Metal commodities. Closing prices of metal commodity were taken for the period February 2003 to January 2013. The sample includes total 120 Monthly observations of individual metals for 10 years. Daily log return data were examined for information efficiency using descriptive statistics, Unit root test, Runs test, Autocorrelation Test and GARCH (1, 1).
Copper is one of the high-risk return trade-off commodities with mean returns of 1.43 per cent and standard deviation of 7.60 per cent. The Runs test suggests Copper as weak form of inefficiency and Aluminium and Nickel hold weak form of efficiency during the period. Aluminium appears the significant positively autocorrected before lag 5 and significant negative auto correlated beyond lag 4. Copper also shows significant negative autocorrelation between lag 3 to 10 lag. However, the autocorrelations in Nickel disappeared after lag 7. The results also exemplify the existence of ARCH and GARCH effect claiming impact of volatility on Commodity returns. The volatility is persistent in returns and is less news sensitive. This study helps regulator for policy decisions. It also helps speculators to trade to earn abnormal returns, and later helps commodity market to become efficient in weak form.
KEYWORDS Commodity Market, Multi-Commodity Exchange (MCX), Augmented Dickey-Fuller, Runs test, ARCH, GARCH etc.
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Runs test indicates that Copper's returns are not independent, confirming weak-form inefficiency at 1% and 5% levels.
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Spillover Effects between BRIC Nations’ Stock Markets
by
Nikunjkumar Patel
and
Pankajray Patel
Asian Research Consortium
, Oct 1, 2014
This paper examines the Spillover Effects of the BRIC nations’ Stock markets for the period Janua...
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This paper examines the Spillover Effects of the BRIC nations’ Stock markets for the period January 2002 to March 2013. Daily returns are examined for Spillover Effects using descriptive statistics, correlation, 100 days rolling correlation, Unit Root Test and Granger Causality. It has been found that data is stationary. From the analysis, it is found that all markets showed positive returns, more specifically Russian market has given highest return and also it moves positive side of average return. Highest fluctuation was observed in Russian market and lowest fluctuation in Chinese market. Brazilian stock market showed upward trend in Russian and Indian stock markets, while the downward trend with the Chinese market. Russian stock market shows upward trend with the Indian stock market, while the downward trend with Chinese market. And, Indian stock market shows downward trend with Chinese stock market. Chinese stock market return depends on all the other three markets. While in other side Brazilian stock market return does not depend with other three market.
Testing Weak Form Market Efficiency of Indian Stock Markets
"This paper examines the weak-form market efficiency of Indian stock markets namely Bombay Stock ...
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"This paper examines the weak-form market efficiency of Indian stock markets namely Bombay Stock Exchange and National Stock Exchange for the period August 1998 to July 2010. The data is also divided into intervals of three years, to find out the weak form efficiency over periods. Daily returns are examined for random walks using Unit Root Test, Auto correlation and runs tests. From the Unit Root, It has been found that data is stationary. From the analysis of whole period, it is found that Autocorrelation prevails in the market. But in the Interval of three year data, significant Autocorrelation is found only in the period
August 2001 to July 2004. But thereafter, market became random walk because no significant autocorrelation found after 2004. Runs Test conclude that the whole period null hypothesis of random walk was not accepted. In all months, null hypothesis is accepted of random walk except January month. But in all days random walk is prevailing. The period of 2004 to 2010 support weak form Market Efficiency."
Study of Co Movement and Interdependence of Indian Stock Market with Selected Foreign Stock Markets
PURPOSE –The objective of this paper is to examine the short-run causal linkages among equity mar...
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PURPOSE –The objective of this paper is to examine the short-run causal linkages among equity markets to better understand how shocks in one market are transmitted to other markets and also try to study co-movement of Indian stock markets index with developed as well as developing countries’ stock market indices.
DATA/PERIOD AND METHODOLOGY– The data were collected from finance.yahoo.com. The data includes daily adjusted closing index prices of Indian Stock market (BSE Sensex) and 10 other major developed and emerging stock markets. We have taken sample period of daily data from July 1997 to Dec 2009. We have also divided the data in two sub-periods, Period-I is ranging From July 1997 to September 2003 and Period –II is ranging from October 2003 to December 2009. We have used logarithm transformed stock price indices to neutralize their returns.
STATISTICAL TOOLS USED – Daily log return data are examined for co-movement and interdependence using descriptive statistics, correlation among the major indices, Unit Root Test/ Stationary test, and Granger causality test.
FINDINGS–The SENSEX has given highest Risk adjusted return for the whole period followed by BVSP, whereas Nikkei has given negative Risk adjusted return for the same period. It has been observed that SENSEX has highest correlation with BVSP (98%) among all the pairs. With the help of bi-variate granger causality test, it is revealed that SENSEX is affected by HANGSENG, STI, DJIA, FTSE and DAX. So we can interpret that SENSEX is interdependent on Developed countries stock markets except NIKKEI. We can also see that SENSEX causes SCI, BVSP NIKKEI, KOSPI and AORD. It means that these markets are interdependent on stock price movement in SENSEX.
Impact of Dividend Announcement on the stock Prices of Indian Companies An Empirical Evidences
Dividend, announcement effect, Abnormal Returns, Cumulative Abnormal Returns, mean return, BSE
Are Stock Markets Interdependent? A Study On Selected Stock Markets
India has adopted LPG Policy in 1991 for rest of the world and leads to increase an integration o...
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India has adopted LPG Policy in 1991 for rest of the world and leads to increase an integration of the Indian capital market with international financial. Here, we have examined the co-movement of the Indian stock market(BSE) with developed markets like US, . Tools like descriptive statistics, correlation, rolling correlation and Granger-causality tests have been used in the paper to find out the same. We found that the US market is not playing a unique role in integration of Asian markets. It is observed from the analysis that majority of the Asian Stock market indices integrate with each other, like BSE, SHANGHAI, JAKARTA and KLSE is highly correlated with Strait Times whereas KSE is highly correlated with BSE. All these stock exchanges are the developing economies of the world. Whereas the developed countries stock indices showed the co-integration majorly with the Volume 2, Issue 11 (November, 2012) ISSN: 2249-7307 AJRBEM Journal of Asian Research Consortium 2
developed countries indices like, Dow Jones is highly correlated with DAX, CAC40 with DAXand NIKKEI with AOA. This shows that an investor can be able to earn a good return by diversifying investment in both kinds of economies (developed and developing). This study yields an interesting result that, excluding the Indian market from the set of Asian markets leads to no or fewer co-integrating relations; this indicates a unique role of India in the degree of linkages of these stock markets during the recent period of more open capital markets, where FII investments play a key role in synthesizing markets across a region. The degree of integration found is not significant that implies the nature of integration with emerging Asian markets
Day of the Week Effect of Asian Stock Markets
The objective of this paper is to observe the descriptive statistics and examine day of the week ...
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The objective of this paper is to observe the descriptive statistics and examine day of the week effect in four selected stock markets of Asian countries namely: India (Bombay Stock Exchange), Hong Kong (Hong Kong Stock Exchange), Japan (Tokyo Stock Exchange) and China (Shanghai Stock Exchange). The data includes daily adjusted closing index prices of Asian stock markets understudy. We have taken sample period of daily data from 1st Jan. 2000 to 31st March. 2011. We have also divided the data in three sub-periods, 1. Period 1: Sample from 05/01/2000 to 20/10/2003 2. Period 2: Sample from 21/10/2003 to 29/06/2007 3. Period 3: Sample from 03/07/2007 to 31/03/2011. We have used logarithm transformed stock price indices to neutralize their returns. BSE has given maximum average return on Wednesday; Hang Seng has given highest returns on Friday whereas, Nikkei and SSE Composite have given highest returns on Thursday and Wednesday respectively. The Monday was a day of high volatility in Asian markets understudy. The return distributions in all market were not normally distributed. The research suggests that there is no evidence of “day of the week effect” in the markets understudy during the period. This finding is also similar in all sub-periods.
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BSE recorded maximum average return on Wednesday while showing positive returns for all days, contrasting with other markets studied.
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An Empirical Study on Weak-Form of Market Efficiency of Selected Asian Stock Markets
by
Nikunjkumar Patel
and
Juhi Dhawan
The purpose of this research is to investigate the weak form of market efficiency of Asian four s...
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The purpose of this research is to investigate the weak form of market efficiency of Asian four selected stock markets. We have taken a daily closing price of stock markets under the study from the 1st January 2000 to 31st March 2011 and also divided full sample in three interval periods, and have applied various test like Runs Test, Unit Root Test, Variance Ratio, Auto Correlation and other test. BSE Sensex has given the highest mean returns to the investor followed by SSE Composite and HANGSENG. BSE Sensex could be considered as high risk markets as it has reported the highest Standard Deviation. During the period BSE Sensex, HANGSENG and SSE Composite markets showed positive average daily returns except NIKKEI. The Runs Test indicated BSE Sensex and NIKKEI markets are weak form inefficient whereas HANSENG and SSE Composite hold weak form of efficiency. The time series for the full as well as sample period did not have a presence of unit root in the markets understudy. According to Auto correlation test it is inferred that the equity markets of the Asian region under the study remained inefficient for some lag whereas they were efficient for the other lag.
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Investment in periods two and three shows better average returns to standard deviation ratio in BSE Sensex and HANGSENG.
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The Study on Co-Movement of Selected Stock Markets
by
Nikunjkumar Patel
Ashwin Modi
, and
Bhavesh Patel
The twenty-first century may well be the time when the balance of power shifts to Brazil, Russia,...
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The twenty-first century may well be the time when the balance of power shifts to Brazil, Russia, India and China, nations collectively referred to as BRICs economies. These nations constitute the shape of the future, giving rise to a new world economy. Leaders in BRICs are frenetically laying the groundwork for decades of new growth. Foreign Investors are investing considerably in the emerging economies with mainly two objectives; (1) To enhance the portfolio growth and; (2) To reduce portfolio risk through efficient international portfolio diversification. This paper studies various alternative techniques for recognizing co-movement resulting among the selected developed stock markets and the emerging stock markets of the world. The leading indices of the selected stock markets are considered as proxies of the markets. Using the daily Index data from July 1, 1997 to June 30, 2008, authors examine the stock market indices of India (SENSEX), Hong Kong (HANGSENG), Mexico (MXX), Russia (RTS), Brazil (BVSP), UK (FTSE-100) and US (DJIA and NASDAQ). Co-integration technique has been employed to study the short term and long-term relationships between the market pairs. The paper explores the issues like contributions of national market volatilities, external world market volatility, and some other factors influencing the correlation between stock market returns.
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RTS Russia had the highest average daily return (0.11%), while FTSE 100 and DJIA had the lowest (0.02%).
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Microfinance: The Gambit for Augmenting Sustainable Development
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