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  1. International Journal of Management Volume 11, Issue 03, March 2020, pp. 408-418. Article ID: IJM_11_03_043 Available online at http://www.iaeme.com/ijm/issues.asp?JType=IJM&VType=11&IType=3 Journal Impact Factor (2020): 10.1471 (Calculated by GISI) www.jifactor.com ISSN Print: 0976-6502 and ISSN Online: 0976-6510 © IAEME Publication Scopus Indexed IMPACT OF DEMONETIZATION ON STOCK PRICE VOLATILITY OF PUBLIC SECTOR BANKS IN INDIA: SPECIAL REFERENCE TO BSE Kasilingam Lingaraja Assistant Professor, Department of Business Administration Thiagarajar College (Autonomous), Madurai, Tamil Nadu, India Veluchamy Ramanujam Associate Professor Bharathiar School of Management and Entrepreneur Development (BSMED), Bharathiar University, Coimbatore, Tamil Nadu, India Lakshmanan Eswaran Assistant Professor, Department of Commerce Thiagarajar College (Autonomous), Madurai, Tamil Nadu, India Thangaraj Viswanathan Assitant Professor, Symbiosis Institute of Business Management, Bangaluru, Karnataka, India Chellaswamy Dhayanand Assistant Professor, Department of Extension and Career Guidance Bharathiar University, Coimbatore, Tamil Nadu, India ABSTRACT This research paper investigates the impact of Demonetization on public sector banks stock price volatility in BSE. The purpose of the above objective, this study used the secondary daily closing stock price data of selected top five largest public sectors banks in India in 2018, based on their market capitalization, for the period of two years, after demonetarization i.e., from 01st January 2017 to 31st December, 2018. The statistical tools and models such as descriptive statistics, ADF, GARCH (1,1) Model and graphical price movement diagram were used for estimating the public sector banks stock price movements and Volatility during the study period. It is found that all the sample public sector banking stocks may not be benefited from demonetization impact. Finally this study conclude that the stock prices of selected public sector banks initially, http://www.iaeme.com/IJM/index.asp 408 editor@iaeme.com
  2. Kasilingam Lingaraja, Veluchamy Ramanujam, Lakshmanan Eswaran, Thangaraj Viswanathan and Chellaswamy Dhayanand the effect of demonetization announcement was seen for a short duration but slowly the market recovered and bounced back to normal. Keywords: Demonetization, Public Sector Banks, Descriptive Statistics, GARCH (1, 1) Model, Stock Price Volatility and Bombay Stock Exchange JEL Classification: B23; E44; E51; E52; G21; K35 Cite this Article: Kasilingam Lingaraja, Veluchamy Ramanujam, Lakshmanan Eswaran, Thangaraj Viswanathan and Chellaswamy Dhayanand, Impact of Demonetization on Stock Price Volatility of Public Sector Banks in India: Special Reference to BSE, International Journal of Management, 11 (3), 2020, pp. 408-418. http://www.iaeme.com/IJM/issues.asp?JType=IJM&VType=11&IType=3 1. INTRODUCTION Demonetization is the act of stripping a currency unit of its status as legal tender. Demonetisation is not the first time experience for India. Demonetisation was initiated for the first time in pre-independence era in the 1946 when then British government decided to strip currency notes of Rs.1,000 and Rs.10,000 from its status of legal tender (Taqi, M., et al., 2018). India went for Demonetisation for the second time in the year 1978 to crack down black money and counterfeited currency on the recommendation of Wanchoo Committee. However, the process failed to achieve its object because the recommendation of the committee was in public domain and it gave the tax evaders and money hoarders time to find solution even prior to demonetisation. On 16th January 1978, Morarji Desai’s government passed the High Demonetisation Bank Notes (Demonetisation) bills to withdraw Rs.1,000, Rs.5,000 and Rs.10,000 which was later reintroduced in the year 1954 (Burse, 2018). India went for demonetisation for the third time On 8 November 2016, India’s Prime Minister Narendra Modi announced the Government of India’s decision to cancel the legal tender character of Rs.500 and Rs.1,000 banknotes with effect from 9 November 2016. He also announced the issuance of new Rs.500 and Rs.2,000 banknotes in exchange for the old banknotes (Baswan, T., 2017). Basically, Stock market is considered to be an independent animal and some policy changes barely impact the indices and stock prices in the market. However, post demonetization, the scenario was quite different in the stock market. Hence, this research is to investigate the impact of demonetization on stock price movements of selected public sector banks in India. 1.2. Banking sector in India Indian banks can be divided into public sector and private sector banks. In India has over 100 banks, with just a small number of 27 of them being public sector banks, it is the public sector banks that have a major stake in the economy of the country. Among the 27 public sector banks five Banks namely state bank of India, Bank of Baroda, Punjab National Bank, Central Bank of India and IDBI Bank in India have been able to prove their strengths over time. They are banks that are well spread across the country and even beyond, through their well-established branches in all over India. 1.2.1. Highlights of top five public sector banks in India. 1.2.1.1. State Bank of India It is inarguably the king of the Indian banks. Incorporated in 1955, SBI brags of at least 13,000 branches across India together with at least 190 foreign offices across the continents. It has its headquarters in Mumbai. The banks are popular for its technologically advanced products such as the recently launched SBI in Touch cards that give its users the effective ability to execute http://www.iaeme.com/IJM/index.asp 409 editor@iaeme.com
  3. Impact of Demonetization on Stock Price Volatility of Public Sector Banks in India: Special Reference to BSE payment by just touching or waving their cards near contactless readers. Other than banking products, the bank is also known for offering other services and products mainly in the fields of capital markets, General Insurance and Life Insurance via its subsidiaries. 1.2.1.2. Bank of Baroda It is the second biggest banks not only among the public sector banking but in the entire banking industry. It was incorporated in 1908 and is headquartered in Vadodara (Previously known as Baroda), in Gujarat. The bank has widely been spread across the country and beyond, having in the excess of 5,000 branches across India and about 100 others in at least 25 foreign countries. A leading institution in the provision of banking and financial services, Bank of Baroda is a winner of a number of major awards such as the Excellence in Banking (PSU Sector) Award. 1.2.1.3. Punjab National Bank It is the oldest of the top three public sector banks having been founded in 1894. The bank has a strong presence in India with at least 6,000 branches spread across the domestic market with another 5 overseas branches. Its headquarters is in New Delhi and is currently supported by a workforce of at least 62,000 employees. Punjab National Bank is yet another award winner, having won the Winner of Golden Peacock Award among others. The bank returns to the society by performing Corporate Social Responsibilities such as organizing tree planting sessions, blood donation camps, and medical camps. 1.2.14. The Central Bank of India It is one of the oldest and one of the topmost public sector banks in the country founded in 1911. Its headquarters are in Mumbai with at least other 4,000 branches having been spread across the country. The bank was among the first to launch credit cards in the country and is served by a workforce of at least 40,000 workers. Upon its establishment, the bank became the first commercial bank in India that was not only wholly owned but also managed by Indians. 1.2.1.5. The IDBI Bank It was incorporated in 1964. It has its headquarters in Mumbai and is served by a workforce of about 18,000 employees. Through time, the IDBI bank has been able to spread across the country, having about 1,800 branches and 3350 ATMs. Its operations are driven by a cutting edge in Banking IT platform. Under its belt are personalized financial and banking solutions to the corporate as well as retail banking arena through this large network. IDBI already has a formidable name but is still steadily scaling higher heights. However, it is also argued among economists, policy makers and researchers that the affect is transient and will recover once normalcy is attained. The Banks stock price movements in the stock market would be a good indicator to evaluate the impact of demonetization on the performance of various stocks in public sector banks listed on a recognized stock exchange like BSE. Hence an attempt has been made in this research to analyse the Impact of Demonetization on Stock Price Volatility of Public Sector Banks in India: Special Reference to BSE. 2. REVIEW OF LITERATURE An attempt has been made to review the earlier research works undertaken in the area of Demonetization, market efficiency, stock price movements and volatility among public sector bans to understand research gaps, tools used and findings of earlier studies. Jokipii, T and Monnin, P (2013), investigated the relationship between the degree of banking sector stability and the subsequent evolution of real output growth and inflation. This http://www.iaeme.com/IJM/index.asp 410 editor@iaeme.com
  4. Kasilingam Lingaraja, Veluchamy Ramanujam, Lakshmanan Eswaran, Thangaraj Viswanathan and Chellaswamy Dhayanand study applied a panel VAR methodology for a sample of 18 OECD countries. It is found that banking sector stability (instability) results in a significant underestimation (overestimation) of GDP growth in the subsequent quarters. Choudhry, T and Jayasekera, R. (2014), empirically investigated the return, volatility and leverage spillover effects between banking industrial stock markets of the major economies (ME) (Germany, UK and US) and the smaller stressed European Union countries (SE), (Italy, Ireland, Greece, Spain and Portugal) from 2002 to 2014. It was suggested that the existence of exploitable trading strategies and has important implications to investors in the areas of option pricing, portfolio optimization and risk management. Lingaraja et al. (2014) analyzed the market efficiency and the performance among the emerging stock markets in Asia. It was found that the four emerging Asian countries indices, namely, India, Indonesia, Malaysia and Philippines recorded random distribution at 95% confidence level and these markets were highly efficient during the study period. Birău, R et al., 2015 investigated the volatility patterns of the S&P Bombay Stock Exchange (BSE) BANKEX index which is the Indian banking sector index. It is to be found that the stock fluctuations are abnormal and highly volatile since the evidence presence in year 2004 for down effect shocks and 2009 for positive shocks. ACF and PACF shows less degree of negative patterns and more positive patterns and presence of AR effect in series. Chellasamy and Anu’s (2017) study aimed to analyse the impact of demonetization on the Sectoral Indices of the NSE. Ordinary least square was used for the study, and the data consisted of 47 observations, 25 trading days before the event and 22 trading days after the event. The result showed that most sectors exhibited negative values, and the public-sector banking segment, pharma, energy and IT recorded a rise in returns. Sunil and Shenoy’s (2017) study examines the impact of demonetization on stock prices of selected sectors. Five sectors and top five companies of each of these sectors and the closing prices 2 months prior to and 4 months post-demonetization were considered for the study. The data were collected from the BSE. The returns were calculated using the holding period return (HPR), buy-and-hold abnormal return (BHAR) and expected returns were calculated using the Capital Asset Pricing Model. The study concluded that the impact on the market was temporary but overall it has not affected the markets to the extent expected. Dungey, M et al., 2018, analyzed the transmission of shocks between global banking, domestic banking and the non-financial sector for eleven Eurozone countries. It is found that the shocks originated in the non-financial sector trigger contagious effects for both the domestic banking sector and, to a lesser extent global banking, thereby acting as a source of fragility for the financial sector during crisis periods. Danisman, G. O., and Demirel, P (2019), examined the impact of market power and bank regulatory variables, such as capital stringency, restrictions in activities and the power of supervisory agencies, on bank stability. It considered various dimensions of bank risk exposures. It is interesting to note that the capital requirements are the strongest regulatory tool for decreasing bank risk, and they decrease bank risk more for banks with more market power. It is to be noted that the above cited literature covered the financial crisis, banking regulation, transmission of shocks and demonetarization impact on price volatility of different sectors and countries stock market (prices and indices). But no detailed research focused on demonietaization and its impact on public sector banks stock price volatility and risk. Hence an attempt has been made in this study to examine the Impact of Demonetization on Stock Price Volatility of Public Sector Banks in India: Special Reference to BSE. 3. STATEMENT OF THE PROBLEM As stated earlier, there are limited number of studies have investigated on this topic in the past. But no comprehensive literature was focused on demonetization and stock price performance of public sector banks. Therefore, it impels the author to do research on the topic and thus contribute to the sparse literature. This study intends to examine the impact of demonetization http://www.iaeme.com/IJM/index.asp 411 editor@iaeme.com
  5. Impact of Demonetization on Stock Price Volatility of Public Sector Banks in India: Special Reference to BSE on the stock price performance of top five public sector banks in India. In order to measure the impact of demonetization on stock price of BSE top five public sector banks has been used as a good indicator of the stock market. The BSE is the oldest stock exchange in Asia and is the tenth largest stock exchange in the world Therefore, for the purpose of the study, BSE has been chosen. 4. OBJECTIVES OF THE STUDY To investigate the impact of demonetization on stock price volatility of selected Public Sector Banks in India. 5. HYPOTHESES OF THE STUDY The present study were formulated and tested the following null hypotheses to accomplish the objective of the study. NH1: There is no normal distribution among the stock price of selected public sector banks after demonetization period. NH2: There is no stationarity among the stock price of selected public sector banks after demonetization period. NH3: There is no volatility among the stock price of selected public sector banks after demonetization period. 6. RESEARCH METHODOLOGY 6.1. Period of Study To examine the impact of demonetization on stock price volatility of selected Public Sector Banks in India, the study covered a period of two year after demonetization i.e., from 1st January, 2017 to 31st December, 2018. 6.2. Sample Design The study focused on top five public sector banks in India i.e., state bank of India, Bank of Baroda, Punjab National Bank, Central Bank of India and IDBI Bank ltd were as sample based on market capitalization. 6.3. Data variables and Sources The data of daily closing prices of five public sector banks i.e., state bank of India, Bank of Baroda, Punjab National Bank, Central Bank of India and IDBI Bank ltd were collected from the official website of Bombay Stock Exchange website (www.bseindia.com). The other relevant data were collected from reputed books, Journals and Articles. The daily closing stock price were transformed by taking natural logarithm of the raw data. 6.4. Tools Used for Analysis The following tools were used for the purpose of analysis and testing the null Hypotheses of this study • Descriptive Statistics (to find out the normal distribution of sample banks) • ADF Test (to experiment the stationarity among the Sample banks) • GARCH (1,1) Model (to investigate the Volatility among the Sample), and • Graphs (to express the sample banks stock price movements) http://www.iaeme.com/IJM/index.asp 412 editor@iaeme.com
  6. Kasilingam Lingaraja, Veluchamy Ramanujam, Lakshmanan Eswaran, Thangaraj Viswanathan and Chellaswamy Dhayanand 7. LIMITATIONS OF THE STUDY The following were the select limitations of the study • This study considered only five public sector banks not in the whole banks in India. • As the study was based on secondary data i.e., daily closing stock price of sample banks from BSE, it is beset with certain limitations which are bound to arise dealing exclusively with secondary data. • This research work was limited to two year period (after demonetization) from 01st January, 2017 to 31st December, 2018. • All the limitations, associated with statistical tools used, are applicable to this study also. 8. ECONOMETRIC ANALYSIS AND EMPIRICAL RESULTS For the purpose of analyse the stock price volatility by using Descriptive Statistics, Unit Root Test (ADF), GARCH and Graph. 8.1. Descriptive Statistics for the Selected Sample Public Sector Banks Table 1 The Results of Descriptive Statistics for the Selected Sample Public Sector Banks during the Study Period from 01st January, 2017 to 31st December, 2018 Sample Banks Bank of Central Bank of IDBI Bank SBI PNB Baroda India Ltd Statistics Mean 0.00062 -0.00009 -0.00023 -0.00129 0.00060 Median -0.00036 -0.00060 0.00069 -0.00308 0.00000 Maximum 0.27584 0.31471 0.46198 0.15594 0.09274 Minimum -0.05735 -0.16025 -0.12151 -0.19955 -0.16718 Std. Dev. 0.02142 0.02792 0.03372 0.02841 0.02662 Skewness 4.47547 2.58688 4.87744 -0.18665 -0.39308 Kurtosis 57.42210 37.21684 73.89132 14.59763 7.65517 Jarque-Bera 62612.13 24649.77 105401.8 2771.429 458.7745 Probability 0 0 0 0 0 Observations 494 494 494 494 494 Source: http://bseindia.com/ and Computed using E-Views 7 Version. The results of descriptive statistics for the selected sample public sector banks during the study period from 01-01-2017 to 31-12-2018 are shown in Table - 1. It is clear from the above Table that during the study period, the stock price of State Bank of India earned high mean value of 0.00062, followed by IDBI bank ltd (0.00060). In terms of stock price unpredictability as measured by the standard deviation of daily returns, only one sample bank namely Punjab National Bank assumed the highest risk value (0.03372), followed by Central bank of India (0.02841), Bank of Baroda (0.02792), IDBI bank ltd (0.02662), and State Bank of India (0.02142). This indicates the fact that there was high risk (in the order of stocks, namely, PNB, Central bank of India, Bank of Baroda, IDBI Bank Ltd and SBI). It is significant to note that high degree of risk was useful for speculators but the investors may study the market risk and carefully take investment decision. The analysis of skewness shows that values for all sample banks stock price, except SBI, Bank of Baroda and PNB, were negative. It is significant to note from the above Table that all sample banks stock values of kurtosis larger than three or high http://www.iaeme.com/IJM/index.asp 413 editor@iaeme.com
  7. Impact of Demonetization on Stock Price Volatility of Public Sector Banks in India: Special Reference to BSE level fat-tails, which make it Leptokurtic. Besides, the Jarque-Bera (JB) values clearly implied that all the sample were normally distributed. In other words, all the sample banks stock prices were less volatile during the study period. In short, the distribution of return data for all the sample banks stock price data was normal. Hence the Null Hypothesis (NH1), there is no normal distribution among the stock price of selected public sector banks after demonetization period, was rejected. 8.2. Augmented Dickey Fuller (ADF) Test for the Selected Sample Public Sector Banks Table 2 The Results of ADF Test for the Selected Sample Public Sector Banks during the Study Period from 01st January, 2017 to 31st December, 2018 Unit Root Test ADF TEST Statistics Durbin Watson Statistical P- Critical R-squared Test Value Value Value Statistic Sample 1% -22.0706 0 -3.44339 State Bank of 5% -22.0706 0 -2.86718 1.999929 0.498012 India Top Five Public Sector Banks in India 10% -22.0706 0 -2.56984 1% -21.9003 0 -3.44339 Bank of 5% -21.9003 0 -2.86718 1.999881 0.494139 Baroda 10% -21.9003 0 -2.56984 1% -19.8247 0 -3.44339 Punjab 5% -19.8247 0 -2.86718 1.988383 0.444583 National Bank 10% -19.8247 0 -2.56984 1% -18.5989 0 -3.44339 Central Bank 5% -18.5989 0 -2.86718 2.01597 0.413324 of India 10% -18.5989 0 -2.56984 1% -20.253 0 -3.44339 IDBI Bank 5% -20.253 0 -2.86718 1.985245 0.455162 Ltd 10% -20.253 0 -2.56984 Source: http://bseindia.com/ and Computed using E-Views 7 Version. The results of Unit Root Tests (Augmented Dickey Fuller - ADF test), for the selected sample public sector banks during the study period from 01-01-2017 to 31-12-2018, are presented in Table – 2. It is to be noted that the values of test critical for the sample bank closing prices were -3.44339, -2.86718 and -2.56984, at the significant levels of 1%, 5% and 10% respectively. The probability values for the closing stock price of sample banks were zero during the study period. The R-Square statistics and Durbin Watson test statistics, for all the sample, were also nearly 0.50 and 2.00 respectively. It is to be noted that the test statistical (t- statistic) values for all sample stock price of banks were less than the test critical values at 1%, 5% and 10% levels of significance. The results of ADF Test, as given at the above Table, indicate that the returns data of five sample banks attained stationarity during the study period. Hence, the null hypothesis (NH02), namely, There is no stationarity among the stock price of selected public sector banks after demonetization period, was rejected. http://www.iaeme.com/IJM/index.asp 414 editor@iaeme.com
  8. Kasilingam Lingaraja, Veluchamy Ramanujam, Lakshmanan Eswaran, Thangaraj Viswanathan and Chellaswamy Dhayanand 8.3. GARCH (1,1) Model for the Selected Sample Public Sector Banks Table 3The Results of GARCH (1,1) Model for Selected Sample Public Sector Banks during the Study Period from 01st January, 2017 to 31st December, 2018 Sample Public Sector Banks C α β α+β P Value State Bank of India 0.000100 0.080960 0.914460 0.995420 0 Bank of Baroda 0.000184 0.064659 0.922413 0.987072 0 Punjab National Bank 0.000481 0.074189 0.789811 0.864000 0 Central Bank of India 0.000121 0.063061 0.919408 0.982469 0 IDBI Bank Ltd 0.000009 0.045033 0.932470 0.977503 0 Source: http://bseindia.com/ and Computed using E-Views 7 Version. Table-3 shows the results of volatility, using GARCH (1.1) model, for daily (closing value) returns of selected sample public sector banks during the study period from 01-01-2017 to 31- 12-2018. From the Table, it is clearly observed that value of the probability (P-Value) was zero at 99% confidence level. According to the analysis of GARCH Model, the α+ β values of all the five sample public sector bank were close to one. This indicates the fact that the returns data, for all the closing stock price of sample banks, were highly volatile, during the study period. Thus the null hypothesis (NH03), there is no volatility among the stock price of selected public sector banks after demonetization period, was rejected. Chart 1 Results of Volatility (α+β) for Sample Public Sector Banks during the Study Period from 01st January, 2017 to 31st December, 2018 Source: Data taken from Table-3 and Computed using MS office Excel – 2007 The results of volatility (both α+β value), of all the five sample banks, during the study period from 01st January, 2017 to 31st December, 2018, are shown in Chart – 1. The Chart clearly explains the high rate of volatility in sample Banks. The values of both risk and return (α+ β) were close to one and the Chart represents both high and low volatility of stock price return of banks. The stock price of SBI earned high market volatility, with a value of 0.995420, followed by Bank of Baroda, with a value of 0.987072. The remaining three sample banks, namely, Central Bank of India (0.982469), IDBI bank ltd (0.977503) and Punjab National bank (0.864000) recorded lower volatility during the study period. http://www.iaeme.com/IJM/index.asp 415 editor@iaeme.com
  9. Impact of Demonetization on Stock Price Volatility of Public Sector Banks in India: Special Reference to BSE Graph 1 Graphical Expression for Price Movements (Closing Prices) of Sample Public Sector Banks during the Study Period from 01st January, 2017 to 31st December, 2018 SBI Bank of Baroda 340 200 320 180 300 160 280 140 260 120 240 100 220 80 I II III IV I II III IV I II III IV I II III IV 2017 2018 2017 2018 PNB Central Bank of India 240 140 200 120 100 160 80 120 60 80 40 40 20 I II III IV I II III IV I II III IV I II III IV 2017 2018 2017 2018 350 IDBI 300 90 250 80 200 150 70 100 50 60 0 I II III IV I II III IV 2017 2018 50 SBI Bank of Baroda PNB Central Bank of India 40 IDBI I II III IV I II III IV 2017 2018 Source: http://bseindia.com/ and Computed using E-Views 7 Version. The graphical exposition shows how far during the effect of time different stock prices tend to reflect each other in tune with the public sector banks daily stock price movements after demonetization period from January 01, 2017 to December 31, 2018 ( individual & grouped) price ups and downs are shown in Graph - 1. Besides, the graphical representation is useful to all types of investors who could easily identify their best investment in the public sector banks. 9. CONCLUSION The study examined the impact of the demonetization announcement on Stock Price of Banks in India with special reference to BSE listed public sector banks. The output of all statistical data analysis of this research such as descriptive statistics, unit root test and GARCH Model shows that there is no significant impact of demonetization on the stock price of selected public sector banks during the study period of after demonetization from 01st January, 2017 to 31st December, 2018. However, the Banking sector will be the biggest beneficiary of demonetization. Banks are flush with the money. The demonetization is the beginning of digital http://www.iaeme.com/IJM/index.asp 416 editor@iaeme.com
  10. Kasilingam Lingaraja, Veluchamy Ramanujam, Lakshmanan Eswaran, Thangaraj Viswanathan and Chellaswamy Dhayanand payment era. The government will take all steps to make India a cashless economy. It will also positively impact the operational efficiency of the banks. It is found that all the sample public sector banking stocks may not be benefited from demonetization impact. It is to be noted that the Graph -1 was clearly explained that initially, the effect of demonetization announcement was seen for a short duration but slowly the market recovered and bounced back to normal. The findings of the study are reliable because it uses long-term data to study the impact of demonetization. Therefore, this study did not find any significant impact of after demonetization announcement on public sector banks stock prices on BSE Stock Market. REFERENCES [1] Baswan, T. (2018). Demonetization: An Initiative towards Cashless Economy. Journal of General Management Research, 4(1), 12–17. [2] Birău, R., Trivedi, J and Antonescu, M. (2015). Modeling S&P Bombay Stock Exchange BANKEX Index Volatility Patterns Using GARCH Model. Procedia Economics and Finance, 32, 520-525. https://doi.org/10.1016/S2212-5671(15)01427-6 [3] Burse, S. (2018). The Impact of Demonetization on India and Indians. International Journal of Scientific and Research Publications, 8(1), 150-156. [4] Chellasamy, P and Anu, K. M. (2017). Impact of Demonetisation on Indian Stock Market: With Special Reference to Sectoral Indices in National Stock Exchange of India. IOSR Journal of Economics and Finance (IOSR-JEF), 8(3), 51–54. [5] Choudhry, T and Jayasekera, R. (2014). Returns and Volatility Spillover in the European Banking Industry during Global Financial Crisis: Flight to Perceived Quality or Contagion? International Review of Financial Analysis, 36, 36-45. https://doi.org/10.1016/j.irfa.2014.05.003 [6] Dungey, M., Flavin, T. J and Lagoa-Varela, D (2018). Are Banking Shocks Contagious? Evidence from the Eurozone. Journal of Banking and Finance (in press). https://doi.org/10.1016/j.jbankfin.2018.07.010 [7] Dr. Sunil Kulkarni and Dr. Jyoti Singhal (2018), EIC (Economic, Industry Wise and Company) Wise Analysis of Impact of Demonetization. Journal of Management, 5(3), 2018, pp. 226–233 [8] Isaiah Onsarigo, M., Selvam, M., Vasanth, V., Lingaraja, K and Raja, M (2015). Efficiency measurement of Kenyan commercial banks. Mediterranean Journal of Social Sciences, 6(4)S2, 621-631, http://dx.doi.org/10.5901/mjss.2015.v6n4s2p621 [9] Udo Emmanuel Samuel, Abner, Ishaku Prince, Victor Inim, Victor Ndubuaku, Monthly Stock Market Volatility on Economic Growth in Nigeria. International Journal of Mechanical Engineering and Technology 10(10), 2019, pp. 131-144 [10] Jokipii, T and Monnin, P (2013). The Impact of Banking Sector Stability on the Real Economy. Journal of International Money and Finance, 32, 1–16. https://doi.org/10.1016/j.jimonfin.2012.02.008 [11] Dr. Jay Desai and Dr. Nisarg A Joshi. Relation between Open Interest and Volatility in Futures Markets. Journal of Management, 5(1), 2018, pp. 14–21. [12] Kasilingam Lingaraja, Murugesan Selvam, Mariappan Raja and Ramkumar Rajesh (2017). Movements and Linkages between Emerging Stock Market Indices with Currency Returns: A Study with Reference to ASIA, 8th International Conference on Business & Information ICBI– 2017, Faculty of Commerce and Management Studies, University of Kelaniya, Sri Lanka. [13] Lingaraja, K., Jothi Baskar Mohan, C., Selvam, M., Raja, M and Kathiravan, C (2020). Exchange Rate Volatility and Causality Effect of Sri Lanka (LKR) with Asian Emerging Countries Currency against USD, International Journal of Management (IJM), 11 (2), 191–208. http://dx.doi.org/10.34218/IJM.11.2.2020.021 [14] Lingaraja, K., Selvam, M and Vasanth, V. (2014). The Stock Market Efficiency of Emerging Markets: Evidence from Asian Region. Asian Social Science, 10(19), 158-168. http://dx.doi.org/10.5539/ass.v10n19p158 http://www.iaeme.com/IJM/index.asp 417 editor@iaeme.com
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