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Journal articles on the topic 'National Stock Exchange NATIONAL STOCK EXCHANGE (NSE)'

Author: Grafiati

Published: 11 September 2023

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1

Shah, Bansi Rajnikant. "A Comparative Study of Bombay Stock Exchange (BSE) and National Stock Exchange (NSE)." International Journal of Scientific Research 1, no. 7 (2012): 26–31. http://dx.doi.org/10.15373/22778179/dec2012/11.

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2

SAMADDER, SWETADRI, KOUSHIK GHOSH, and TAPASENDRA BASU. "FRACTAL ANALYSIS OF PRIME INDIAN STOCK MARKET INDICES." Fractals 21, no. 01 (2013): 1350003. http://dx.doi.org/10.1142/s0218348x13500035.

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The purpose of the present work is to study the fractal behaviour of prime Indian stock exchanges, namely Bombay Stock Exchange Sensitivity Index (BSE Sensex) and National Stock Exchange (NSE). To analyze the monofractality of these indices we have used Higuchi method and Katz method separately. By applying Mutifractal Detrended Fluctuation Analysis (MFDFA) technique we have calculated the generalized Hurst exponents, multifractal scaling exponents and generalized multifractal dimensions for the present indices. We have deduced Hölder exponents as well as singularity spectra for BSE and NSE. I

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Kotha, Kiran Kumar, and Shreya Bose. "Dynamic Linkages between Singapore and NSE listed NIFTY Futures and NIFTY Spot Markets." Journal of Prediction Markets 10, no. 2 (2017): 1–13. http://dx.doi.org/10.5750/jpm.v10i2.1253.

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This study examines the dynamic linkages of Nifty stock index and Nifty index futures contract traded on the home market, National Stock Exchange (NSE) and on the off-shore market, Singapore Stock Exchange (SGX). The study uses daily closing prices of the Nifty index and the Nifty futures contract traded on both the exchanges for the period July 15, 2010 to July 15, 2016. The study finds a causality running from the returns of the spot market to the returns from the Nifty futures market in both the exchanges, NSE and SGX, with the help of Vector Error Correction model and Granger causality tes

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Malhotra, Nidhi, Kamini Tandon, and Deepak Tandon. "Testing Weak Form of Efficient Market Hypothesis: Evidence from Bombay Stock Exchange (BSE) & National Stock Exchange (NSE)." Asian Journal of Research in Social Sciences and Humanities 5, no. 6 (2015): 178. http://dx.doi.org/10.5958/2249-7315.2015.00144.6.

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5

Agrawal, Ashita, Pitabas Mohanty, and Navindra Kumar Totala. "Does EVA Beat ROA and ROE in Explaining the Stock Returns in Indian Scenario? An Evidence Using Mixed Effects Panel Data Regression Model." Management and Labour Studies 44, no. 2 (2019): 103–34. http://dx.doi.org/10.1177/0258042x19832397.

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We study a panel data of 1,700 Indian firms listed in either National Stock Exchange (NSE) or Bombay Stock Exchange (BSE) for the period 2001 to 2016 to see if economic value added (EVA) explains the annual stock returns of these Indian firms better than return on assets (ROA) and return on equity (ROE). Using mixed effect model, we find that EVA does explain the annual stock returns of these Indian firms better than ROA and ROE.

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Dhamija, Sanjay, and Ravinder Kumar Arora. "Initial and After-market Performance of SME IPOs in India." Global Business Review 18, no. 6 (2017): 1536–51. http://dx.doi.org/10.1177/0972150917713081.

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This article examines the initial and after-market performance of the initial public offerings (IPOs) listed on the recently launched platform for small and medium enterprises (SMEs) by the Bombay Stock Exchange (BSE), Mumbai and the National Stock Exchange (NSE). The study does find evidence of underpricing of IPOs by SMEs in line with other studies internationally. However, the level of underpricing is found to be lower than that of IPOs listed on the main board stock exchanges in India, reported by earlier studies. This may be partially due to the fact that the SME platform is at an infancy

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Selvam, M., G. Indhumathi, and J. Lydia. "Impact on Stock Price by the Inclusion to and Exclusion from CNX Nifty Index." Global Business Review 13, no. 1 (2012): 39–50. http://dx.doi.org/10.1177/097215091101300103.

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Changes in an index are a regular phenomenon and they take place due to the inclusion and exclusion of stocks from the index. The inclusion or exclusion of stocks creates great impact on the value of the firm. However, these changes are simply a short-lived event with no permanent valuation effect. The present research study analyzed the impact of the inclusion into and exclusion of certain stocks from National Stock Exchange (NSE) S&P CNX Nifty index with Indian perspective. The study provides evidence on whether the announcements of Nifty index maintenance committee have any information

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Bagade, Mr Ketan, and Prof Varsha Bhosale. "Artificial Intelligence based Stock Market Prediction Model using Technical Indicators." International Journal of Innovative Technology and Exploring Engineering 11, no. 6 (2022): 34–39. http://dx.doi.org/10.35940/ijitee.f9915.0511622.

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The indian stock market is highly volatile and complex by nature. However, notion of stock price predictability is typical, many researchers suggest that the Buy & Sell prices are predictable and investor can make above-average profits using efficient Technical Analysis (TA).Most of the earlier prediction models predict individual stocks and the results are mostly influenced by company’s reputation, news, sentiments and other fundamental issues while stock indices are less affected by these issues. In this work, architecture of project is given.As a part of prediction model the Long Short-

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9

Manickam, Tamilselvan, and R. Madhumitha. "Random Walk Investigation in Indian Market with special reference to S&P Nifty – Fifty Stocks." International Journal of Finance & Banking Studies (2147-4486) 4, no. 4 (2015): 52–61. http://dx.doi.org/10.20525/ijfbs.v4i4.40.

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The competence of a financial system is entirely depending upon the stock market efficiency. The gradual growth of equity investor’s participation is inevitable to enrich the overall growth of emerging economies.Hence the necessity is felt to provide an empirical support to the investing community. For the purpose, this study attempts to examine the weak-form efficiency of Indian stock market – National Stock Exchange (NSE). The study has used the daily closing price of the Nifty fifty stocks from 3rdJanuary 2011 to 24thApril 2015. To test the weak form efficiency both parametric and non-param

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Shacheendran, V. "Dematerialisation of Securities in Indian Capital Market; A Paradigm Shift through Depository System." Shanlax International Journal of Commerce 8, no. 3 (2020): 29–32. http://dx.doi.org/10.34293/commerce.v8i3.3264.

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Dematerialization has initiated a new trend in securities trading and settlement. Indian capital market has embraced technological sophistication by permitting electronic trading in securities. Depositors Act, 1996 has facilitated the setting up of depositories and dematerialization of securities. This paper attempts to evaluate the progress of dematerialization in India. For the study, data has been used that of the National Stock Exchange of India Ltd. (NSE), the largest stock exchange in India.

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11

Arasu, B. Senthil, Desti Kannaiah, Nancy Christina J., and Malik Shahzad Shabbir. "Selection of Variables in Data Envelopment Analysis for Evaluation of Stock Performance." Management and Labour Studies 46, no. 3 (2021): 337–53. http://dx.doi.org/10.1177/0258042x211002511.

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This study deploys data envelopment analysis (DEA) to identify the appropriate variables for the performance valuation of stocks. For this purpose, sixty-nine non-financial stocks of the Nifty 100 index of The National Stock Exchange of India Ltd (NSE) were selected as a sample for this study. We segregated the selected stocks into three groups of inputs and outputs for DEA based on fundamental indicators (financial ratios); technical indicators (momentum indicators); and both, fundamental and technical indicators. The stock performance indicators are sourced from the ACE database from financi

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12

Sangh, Neeraj. "Static Systematic Risk Profile of Nifty 100 Stocks: A Year on Year Analysis of Beta." GIS Business 12, no. 5 (2017): 75–83. http://dx.doi.org/10.26643/gis.v12i5.3346.

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Beta Coefficient, as a measurement statistic of systematic risk of securities, was initially explained by Sharpe as a slope of simple linear regression function using rate of return on a market index as independent variable and a securitys rate of return as dependent variable. National Stock Exchange (NSE), the leading stock exchange of India, practice this ordinary least square (OLS) regression based single index market model for disseminating beta coefficients of prominent NIFTY 100 stocks. OLS regression based index model presumes that beta coefficients of securities should remain stable fo

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13

Amanulla, S., and M. Thiripalraju. "Week-end Effect: New Evidence from the Indian Stock Market." Vikalpa: The Journal for Decision Makers 26, no. 2 (2001): 33–50. http://dx.doi.org/10.1177/0256090920010204.

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This paper tests whether the carry-forward transactions in different periods have any impact on week-end effect in the Indian stock market during the period January 1990-December 1999. This study uses the daily stock return of 82 companies traded in the Bombay Stock Exchange (BSE) and three stock market price indices, viz., BSE sensitive index, BSE national index, and S&P CNX Nifty index to investigate the weekend effect The results from the subsample period strongly support the existence of week-end effect during the period of ban on carry-forward (badld] transactions. This study also evi

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Hajam, Murtaza Ali, and Mohammad Shafi. "Volatility on India’s National Stock Exchange (NSE) Effected by FIIs : An Empirical Analysis." Kuwait Chapter of Arabian Journal of Business and Management Review 9, no. 4 (2020): 175–82. http://dx.doi.org/10.12816/0059144.

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Singh, Kamaljit, and Vinod Kumar. "Dynamic linkage between nifty-fifty and sectorial indices of national stock exchange." American Journal of Economics and Business Management 3, no. 2 (2020): 17–27. http://dx.doi.org/10.31150/ajebm.v3i2.148.

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The main objective of this paper is to analyze the trend and pattern of the Nifty-Fifty and sectorial indices. An attempt has been also made to find out the causal relationship among the Nifty-Fifty and NSE sectorial Indices. The unit root test and Granger-causality test has been applied to check the causal relationship between Nifty-Fifty and sectorial indices. The finding of the study shows that the financial service sector had performed better and followed by the banking sector among all the indices while the Pharma sector and the Realty sector were Under-performed in comparison to other in

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Kumar, K., and Dattatray P. Gandhmal. "An intelligent indian stock market forecasting system using LSTM deep learning." Indonesian Journal of Electrical Engineering and Computer Science 21, no. 2 (2021): 1082. http://dx.doi.org/10.11591/ijeecs.v21.i2.pp1082-1089.

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<p><span>Stock market data is considered to be one of the chaotic data in nature. Analyzing the stock market and predicting the stock market has been the area of interest among the researchers for a long time. In this paper, we have stepped forward and used a deep learning algorithm with classification to predict the behavior of the stock market. LSTM deep learning algorithm is used with an optimization algorithm to formulate the hyperparameters. To further improve the accuracy of prediction the stock data is first given to a classification algorithm to reduce the number of input p

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Sehgal, Sanjay, and Mala Dutt. "Domestic and International Information Linkages for the US Dollar/Indian Rupee Contracts: An Empirical Study." Management and Labour Studies 43, no. 4 (2018): 205–33. http://dx.doi.org/10.1177/0258042x18791625.

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This study examines price discovery and volatility linkages between USD/INR spot and futures contracts in India and between USD/INR futures contracts on National Stock Exchange of India Limited (NSE), India and on three international exchanges, namely Singapore Exchange (SGX), Dubai Gold and Commodity Exchange (DGCX) and Chicago Mercantile Exchange (CME), from 29 August 2008 to 30 March 2015. Findings show that, at domestic level, the futures dominate spot in the Indian currency market; these findings are stronger than those in an earlier study, indicating improved pricing as well as hedging e

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18

Chakraborty, Jayant Kumar, and Sudeshna Sarkar. "Examining the Impact of Revised XBRL Mandate on the Performance of Firms in India." SEDME (Small Enterprises Development, Management & Extension Journal): A worldwide window on MSME Studies 48, no. 4 (2021): 330–40. http://dx.doi.org/10.1177/09708464211069446.

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Extensible Business Reporting Language (XBRL) is becoming increasingly popular in the area of financial accounting data. On 2 May 2018, it was announced that public listed companies (PLC) must document their reports in XBRL format at the three cross-country exchanges, namely, the Bombay Stock Exchange (BSE), National Stock Exchange (NSE) and MCX. This article examines whether such PLCs' operational performance has improved since the mandate began. The performance variables of the company are investigated. Our findings reveal that the XBRL-adopted PLC's success is mostly driven by growth (sales

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19

Patni, Ity, and Nishu Gupta. "Construction of Optimal Portfolio and Selection of Stock using Fuzzy Approach." International Journal of Engineering & Technology 7, no. 3.30 (2018): 118. http://dx.doi.org/10.14419/ijet.v7i3.30.18214.

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Stock selection methods and strategies have been the prominent area of research since long. Portfolio theory is a connotation how an intelligent bias free investor should make an optimal portfolio. The line of the work is first inclined towards construction of optimal portfolio using Sharpe-Single Index model, CAPM, Jenson’s Measure, Treynor & Sharpe Ratio. These measures consider total risk i.e. systematic and unsystematic risk and suggests a rational investor in what proportion an investment can be made to a particular stock. Further, the purpose of the work is to combine the fuzzy appro

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20

Singh, Amit Kumar, and Shivani Kalra. "Short Run Underpricing of Initial Public Offerings (IPOs) in the National Stock Exchange (NSE)." Ramanujan International Journal of Business and Research 4, no. 1 (2019): 223–47. http://dx.doi.org/10.51245/rijbr.v4i1.2019.157.

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Singh, Amit Kumar, and Shivani Kalra. "Short Run Underpricing of Initial Public Offerings (IPOs) in the National Stock Exchange (NSE)." Ramanujan International Journal of Business and Research 4, no. 1 (2019): 223–47. http://dx.doi.org/10.51245/rijbr.v4i1.2019.157.

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22

Thappa, Sankar. "A study on the performance in national stock exchange (NSE) sectoral indices of India." Journal of Global Information and Business Strategy 14, no. 1 (2022): 50–62. http://dx.doi.org/10.5958/2582-6115.2022.00007.8.

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23

Sinha, Paritosh Chandra. "Herd Behaviour: How Decisive is the Noise in the NSE and BSE Stock Markets?" GIS Business 11, no. 6 (2016): 01–16. http://dx.doi.org/10.26643/gis.v11i6.3381.

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Do investors in the stock markets act/react on true information or noise? Do they believe on their own information or simply herd? The study seeks to explore these typical research queries from the behavioral finance perspectives. In particular, it develops a new theory of herding behavior and extends the models of Banerjee (1992) and Bikhchandani, Hirshleifer, and Welch (1992). The study also empirically tests the same on the Indian context with the high frequency intraday trading data for the real trade-time or time-stamp, trade-volume, and trade-price of ten sample scripts listed for their

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Fattah, Doaa A., Amany A. Naim, Abeer S. Desuky, and Mervat S. Zaki. "AutoKeras and particle swarm optimization to predict the price trend of stock exchange." Bulletin of Electrical Engineering and Informatics 11, no. 2 (2022): 1100–1109. http://dx.doi.org/10.11591/eei.v11i2.3373.

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The stock price varies depending on time, so stock market data is time-series data. The prediction of the trend of a stock price is a more interesting topic for investors to take an investment decision in a specific stock. Prediction of stock price always depends on machine learning algorithms. In this work, optimizing deep neural network (DNN) is used for predicting if the close price is reached to the profit which is determined by the investor or not and improve the prediction accuracy. Particle swarm optimization (PSO) and auto machine learning (AutoML) are used as optimizers with DNNs. The

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Kumar, Rakesh. "Examining the Dynamic and Non-linear Linkages between Crude Oil Price and Indian Stock Market Volatility." Global Business Review 18, no. 2 (2017): 388–401. http://dx.doi.org/10.1177/0972150916668608.

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The present study is an attempt to examine the dynamic impact of crude oil price variations in the international market on the Indian stock market volatility. For the purpose, the study uses crude oil monthly price expressed in dollar per barrel, Bombay Stock Exchange (BSE)-listed index BSE Sensex and National Stock Exchange (NSE)-listed CNX Nifty prices for the period from January 2001 to December 2014. GARCH (1,1) model with net crude oil price change as exogenous variable is used to estimate the impact of net oil price change in international market on the conditional volatilities of both t

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Amuthan, R. "Co relating NIFTY 50 Index Trend’s impact on NSE’s Sector based Indices Growth Momentum in Post COVID-19 led Indian Economy with Special reference to NIFTY Bank, NIFTY Consumer Durables, NIFTY IT and NIFTY Pharma Indices using Arithmetic Modelling." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 6 (2021): 2184–89. http://dx.doi.org/10.17762/turcomat.v12i6.4824.

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The NIFTY 50 is the flagship index on the National Stock Exchange of India Ltd. (NSE). The Index tracks the behavior of a portfolio of blue chip companies, the largest and most liquid Indian securities. It includes 50 of the approximately 1600 companies traded (listed & traded and not listed but permitted to trade) on NSE, captures approximately 65% of its float-adjusted market capitalization and is a true reflection of the Indian stock market. This study probed in to the correlation between NIFTY 50 and NIFTY Bank, NIFTY 50 and NIFTY Consumer Durables, NIFTY 50 and NIFTY IT and NIFTY 50 a

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27

Pandey, Ram Prakash. "A Study on Performance Evaluation and Computation of Stock Market Index with Special Reference to BSE and NSE." International Journal for Research in Applied Science and Engineering Technology 11, no. 8 (2023): 1023–46. http://dx.doi.org/10.22214/ijraset.2023.55292.

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Abstract: The Stock market index in India play a lcrucial roe in the country’s economic growth and development. The Investors, policymakers, and market participants closely monitor the performance of stock market indices. In general, people tend to be unaware of Indian indices, their weights, and their composition patterns. This research paper aims to analyze the performance of stock market indices and focuses on important indexes from the Bombay Stock Exchange and the National Stock Exchange while taking into account their development, calculation method, and historical value. This Study is m

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Pandey, Ram Prakash. "A Study on Performance Evaluation and Computation of Stock Market Index with Special Reference to BSE and NSE." International Journal for Research in Applied Science and Engineering Technology 11, no. 8 (2023): 1023–46. http://dx.doi.org/10.22214/ijraset.2023.55292.

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Abstract: The Stock market index in India play a lcrucial roe in the country’s economic growth and development. The Investors, policymakers, and market participants closely monitor the performance of stock market indices. In general, people tend to be unaware of Indian indices, their weights, and their composition patterns. This research paper aims to analyze the performance of stock market indices and focuses on important indexes from the Bombay Stock Exchange and the National Stock Exchange while taking into account their development, calculation method, and historical value. This Study is m

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Sen, Abhibasu, and Karabi Dutta Choudhury. "On the co-movement of crude, gold prices and stock index in the Indian market." International Journal of Financial Engineering 07, no. 03 (2020): 2050036. http://dx.doi.org/10.1142/s242478632050036x.

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The nonlinear relationship in the joint time-frequency domain has been studied for the Indian National Stock Exchange (NSE) with the international Gold price and WTI Crude Price being converted from Dollar to Indian National Rupee based on that week’s closing exchange rate. Though a good correlation was obtained during some period, but as a whole no such cointegration relation can be found out. Using the Discrete Wavelet Analysis, the data was decomposed and the presence of Granger Causal relations was tested. Unfortunately, no significant relationships are being found. We then studied the Wav

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Agrawal, Tarunika Jain, Sanjay Sehgal, and Rahul Agrawal. "Disruptive Innovations, Fundamental Strength and Stock Winners: Implications for Stock Index Revisions." Vision: The Journal of Business Perspective 24, no. 3 (2020): 356–70. http://dx.doi.org/10.1177/0972262920928890.

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Globally, disruptions driven by technological advancements are visible in the form of unicorns and declining lifespan of the index constituents. Sectors such as information technology, financial services, energy, consumer goods and automobile are found to be more prone to disruptive innovation. Assessing the financial strength of the incumbents is crucial to assess their strength to endure disruption. We construct a fundamental strength index (FSI) using 11 financial performance measures covering 7 key attributes, namely profitability, efficiency, solvency, liquidity, net investments, pursuanc

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31

Wanaputra, Farisan, and Siti Nurwahyuningsih Harahap. "Analisis pengaruh XBRL terhadap kinerja perusahaan di India." Jurnal Ekonomi dan Bisnis 21, no. 2 (2018): 219–40. http://dx.doi.org/10.24914/jeb.v21i2.1686.

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Penelitian ini bertujuan untuk menganalisis pengaruh adopsi XBRL terhadap kinerja perusahaan, khususnya Return on Assets (ROA) sebagai ukuran kinerja akuntansi dan Market to Book Ratio (MTB) sebagai ukuran kinerja pasar. Penelitian ini menggunakan sebanyak 100 sampel perusahaan yang terdaftar pada National Stock Exchange (NSE) maupun Bombay Stock Exchange (BSE) pada tahun 2008 hingga 2013. Metode pengambilan sampel yang digunakan adalah metode purposive sampling. Pengujian hipotesis dilakukan dengan menggunakan metode Ordinary Least Square. Hasil penelitian menunjukkan bahwa adopsi XBRL berpen

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Yadav, Naveen Ramesh, Hirak Dasgupta, and Rashmy Moray. "Short Term Performance Analysis of IPOs in India." Asian Journal of Empirical Research 8, no. 11 (2018): 392–403. http://dx.doi.org/10.18488/journal.1007/2018.8.11/1007.11.392.403.

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The research is aimed at the short term IPO returns that are issued on the National Stock Exchange (NSE) and Bombay Stock Exchange (BSE). The evaluation of IPO is done on the basis of the returns generated on the day of issue, 10 and 30 days after the day of issue. The significance of this paper can be realized from the fact whether the return generated in short term in comparison to the market are more or less i.e. the IPO has outperformed the index as a benchmark. The study includes a sample of 28 IPO’s issued from the year 2013 to 2015. The results showed that the mean % performance of IPO

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Bhuva, Krunal K., and Vijay H. Vyas. "Expiry day Impact on return on Indian Stock market (NSE)- an Empirical Study." Journal of Management and Science 1, no. 3 (2013): 402–9. http://dx.doi.org/10.26524/jms.2013.45.

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Derivative products are alleged to have a sharp affect on the stock market in various ways ever since their inception in June 2000. Currently, derivative trading constitutes approximately 90% of the total turnover of the NSE (National Stock Exchange). Launching of derivatives and their expiration (last Thursday of every month) in the Indian stock market has been perceived to have direct corollary on the return, volatility, efficiency and marketability of the stock market. This paper tries to analyze empirically the expiration day effect of stock derivatives on underlying securities. This study

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Islam, Khalid Ul, and M. M. Goyal. "Examining the Fisher Effect in Short and Long Run: A Study of NSE Sectoral Indices." GIS Business 12, no. 5 (2017): 20–29. http://dx.doi.org/10.26643/gis.v12i5.3341.

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The belief that stock market provides hedge against inflation has been put to test by many researchers over the past few decades. The present study aims at testing the Fisher effect in the Indian context. We have used monthly data, from July 2006 to June 2016, of the National Stock Exchange sectoral indices and consumer price index. The ordinary least square regression and Johansen cointegration approach have been used to test whether or not Indian sectoral indices provide hedge against inflation in short and long run respectively. The weak exogenity test under VECM has been used to establish

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35

Keshari Jena, Sangram, and Ashutosh Dash. "Does contract size matter for price discovery and risk management in stock index futures?" Investment Management and Financial Innovations 13, no. 3 (2016): 62–74. http://dx.doi.org/10.21511/imfi.13(3).2016.05.

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In an effort to increase the liquidity and accessibility to the investors, National Stock Exchange of India (NSE) had reduced contract size of its Nifty index futures two times from 200 to 100 and, subsequently, to 50 units. How does this change in contract size of index futures impact the informed and hedge based trading, thereby contributing to the twin objectives of price discovery and risk management, respectively? VAR model is applied to daily return volatility, volume and open interest to study the impact. Significant feedback relationship between volume and volatility following the redu

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KUMAR, K. KIRAN, and SHREYA BOSE. "HEDGING EFFECTIVENESS OF CROSS-LISTED NIFTY INDEX FUTURES." Global Economy Journal 19, no. 02 (2019): 1950011. http://dx.doi.org/10.1142/s2194565919500118.

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This paper investigates the hedging effectiveness of cross-listed Nifty Index futures and compares the performance of constant and dynamic optimal hedging strategies. We use daily data of Nifty index traded on the National Stock Exchange (NSE), India and cross-listed Nifty futures traded on the Singapore Stock Exchange (SGX) for a period of six years from July 15, 2010 to July 15, 2016. Various competing forms of Multivariate Generalised Autoregressive Conditional Heteroscedasticity (MGARCH) models, such as Constant Conditional Correlation (CCC) and Dynamic Conditional Correlation (DCC), have

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Khanra, Sayantan, and Sanjay Dhir. "Creating Value in Small-cap Firms by Mitigating Risks of Market Volatility." Vision: The Journal of Business Perspective 21, no. 4 (2017): 350–55. http://dx.doi.org/10.1177/0972262917733166.

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Extant research has explored numerous ideal approaches to predict and anticipate the unpredictability in stocks to mitigate business risks. This article attempts to offer an important insight on creating values in terms of financial returns dodging the risks associated with the market volatility in emerging market economies by exploring the context of National Stock Exchange (NSE), India. The study establishes that Small-cap companies, which are included in NSE Small 100 index, are less inclined to be impacted by the market volatility index (NVIX) compared to the Large-cap companies and Mid-ca

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Narang, Monika, Mahesh Chandra Joshi, Kiran Bisht, and Arun Pal. "Stock portfolio selection using a new decision-making approach based on the integration of fuzzy CoCoSo with Heronian mean operator." Decision Making: Applications in Management and Engineering 5, no. 1 (2022): 90–112. http://dx.doi.org/10.31181/dmame0310022022n.

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The main objective of stock portfolio selection is to distribute capital to selected stocks to get the most profitable returns at a lower risk. The performance of a stock depends on a number of criteria based on the risk-return measures. Therefore, the selection of shares is subject to fulfilling a number of criteria. In this paper, we have adopted an integrated approach based on the two-stage framework. First, the heronian mean operator (improved generalized weighted heronian mean and improved generalized geometric weighted heronian mean) is combined with the traditional Combined compromise s

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Peswani, Shilpa Girish. "Returns to Low Risk Investment Strategy." Applied Finance Letters 6, no. 01 (2017): 2–15. http://dx.doi.org/10.24135/afl.v6i01.65.

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The paper studies the low risk anomaly in the Indian market using entire National Stock Exchange (NSE) as sample from January 2001 to June 2016. It provides evidence that low risk portfolio sorted for total risk, systematic risk as well as unsystematic risk individually for the large cap, mid cap, small cap and the entire NSE universe give higher returns to the investor as compared to high risk portfolio. The difference of returns from low risk portfolio versus high risk portfolio is positive as well as economically and statistically significant for all the risk measures. The results also prov

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Majumder, Sayantan Bandhu, and Ranjanendra Narayan Nag. "Shock and Volatility Spillovers Among Equity Sectors of the National Stock Exchange in India." Global Business Review 19, no. 1 (2017): 227–40. http://dx.doi.org/10.1177/0972150917713290.

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The basic thrust of this article is to examine how shocks and volatility are transmitted across sector indices. This article employs the autoregressive asymmetric BEKK-GARCH model. The study is based on daily data from the National Stock Exchange (NSE) of India from January 2004 to January 2014. Volatility spillover was found to be bidirectional among the two pro-cyclical sectors: Finance and IT. But, there was a unidirectional shock and volatility spillover from the non-cyclical FMCG sector to both the pro-cyclical sectors. The FMCG sector has remained almost unaffected by the spillover from

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Agarwal, Samiksha, and Lekha Chakraborty. "Business Taxation in an Emerging Economy: Analysing Corporate Tax Incidence." Review of European Studies 11, no. 2 (2019): 8. http://dx.doi.org/10.5539/res.v11n2p8.

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This paper estimates the incidence of corporate taxes in an emerging economy &ndash;India- using the data from 5,666 business firms listed in the Bombay Stock Exchange (BSE) and the National Stock Exchange of India (NSE) for the period 2000-15. Using the dynamic panel models, we find that capital bear the burden of corporate taxation relatively more than the labour. Our findings highlight that the effective tax rate is higher for the small corporate firms than the gigantic firms. The tax policy implications for strengthening the wage bargaining frameworks is insignificant as we found the w

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Saji, T. G., and S. Harikumar. "Earnings Growth and Value Premium: The Indian Experience." Vikalpa: The Journal for Decision Makers 40, no. 4 (2015): 444–54. http://dx.doi.org/10.1177/0256090915608542.

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Executive Summary This article addresses two main questions: Does a value premium exist in emerging market like India? If so, how pervasive is it in different market conditions? Value premium is assumed to be the difference in stock returns of undervalued and overvalued firms with a unique industry profile. The sample for the study consisted of 32 companies from the Information Technology (IT) sector, the stocks of which had traded continuously in the National Stock Exchange (NSE) during the period 2000–2010. Prowess and Capitaline constitute the sources for the firm-level financial data, and

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Dixit, Jitendra Kumar, and Vivek Agrawal. "Foresight for stock market volatility – a study in the Indian perspective." foresight 22, no. 1 (2019): 1–13. http://dx.doi.org/10.1108/fs-05-2019-0040.

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Purpose Volatility is a permanent behavior of the stock market around the globe. The presence of the volatility in the stock price makes it possible to earn abnormal profits by risk seeking investors and creates hesitancy among risk averse investors as high volatility means high return with high risk. Investors always consider market volatility before making any investment decisions. Random fluctuations are termed as volatility of stock market. Volatility in financial markets is reflected because of uncertainty in the price and return, unexpected events and non-constant variance that can be me

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Osuala, A. E., U. A. Onoh, and G. U. Nwansi. "Presidential Election Results and Stock Market Performance: Evidence From Nigeria." Applied Economics and Finance 5, no. 2 (2018): 117. http://dx.doi.org/10.11114/aef.v5i2.3016.

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The study investigates the effect of Presidential election results on the performance of an emerging stock market using the case of the 2011 and 2015 Presidential elections in Nigeria. Adopting Event Study methodology to analyse the secondary data obtained from the Nigerian Stock Exchange (NSE) and some national dailies, the results of the study suggest that the 2011 presidential election result had negative significant impact on the performance of the stock market. On the other hand, the 2015 Presidential election result had positive but insignificant impact on the stock market as evidenced b

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Pathak, Rajesh, Thanos Verousis, and Yogesh Chauhan. "Information Content of Implicit Spot Prices Embedded in Single Stock Future Prices: Evidence from Indian Market." Journal of Emerging Market Finance 16, no. 2 (2017): 169–87. http://dx.doi.org/10.1177/0972652717712373.

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This study examines the information content of pricing error, measured by the difference between the implied price computed using the cost of carry model and the spot price of Single Stock Futures (SSFs), traded on National Stock Exchange (NSE), India. The returns of portfolios, based on ranking of such pricing errors, are investigated. The consistency of results is verified by controlling for established risk factors, that is, market, size, value and momentum premium, and idiosyncratic factors such as firm’s liquidity and size. Our study reveals that the pricing error is a priced risk factor

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Ali, Farman, Pradeep Suri, Tarunpreet Kaur, and Deepa Bisht. "Cointegration and causality relationship of Indian stock market with selected world markets." F1000Research 11 (November 1, 2022): 1241. http://dx.doi.org/10.12688/f1000research.123849.1.

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Background: The purpose of this study is to explore the trends and causes of established and emerging nations' stock market integration with India. The National Stock Exchange (NSE) indices act as a counterweight to international market indices. This study investigates the sustained interest of foreign investors in the Indian stock market in the wake of capital market reforms, as well as whether it moves in tandem with other markets in Asia and the United States. Methods: Our study examined the possibility of cross-country cointegration between the largest economies and indices around the worl

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Ali, Farman, Pradeep Suri, Tarunpreet Kaur, and Deepa Bisht. "Cointegration and causality relationship of Indian stock market with selected world markets." F1000Research 11 (August 10, 2023): 1241. http://dx.doi.org/10.12688/f1000research.123849.2.

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Background: The purpose of this study is to explore the trends and causes of established and emerging nations' stock market integration with India. The National Stock Exchange (NSE) indices act as a counterweight to international market indices. This study investigates the sustained interest of foreign investors in the Indian stock market in the wake of capital market reforms, as well as whether it moves in tandem with other markets in Asia and the United States. Methods: Our study examined the possibility of cross-country cointegration between the largest economies and indices around the worl

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Camilleri, Silvio John. "Do call auctions curtail price volatility? Evidence from the National Stock Exchange of India." Managerial Finance 41, no. 1 (2015): 67–79. http://dx.doi.org/10.1108/mf-10-2013-0292.

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Purpose – The purpose of this paper is to empirically investigate whether call auctions which batch orders for simultaneous execution, may restrain stock market volatility. Design/methodology/approach – The authors use high-frequency data to investigate volatility changes following the suspension of opening and closing call auctions on the National Stock Exchange (NSE) of India in 1999. The authors evaluate this issue by considering both modelled and realised volatility. Using a GARCH approach the authors model intra-day volatility for the trading days preceding and succeeding the auction susp

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Debata, Byomakesh, and Jitendra Mahakud. "Interdependence between Monetary Policy and Stock Liquidity: A Panel VAR Approach." Margin: The Journal of Applied Economic Research 12, no. 4 (2018): 387–413. http://dx.doi.org/10.1177/0973801018786270.

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This article examines the relationship between monetary policy and individual stock liquidity in an order-driven emerging stock market like India. This study considers stocks listed in National Stock Exchange of India (NSE) and continuously traded from April 2002 to March 2015. Considering the multiple dimensions of liquidity, this study uses five different liquidity proxies to capture the various facets of liquidity such as trading activity, price impact and transaction cost. An array of macroeconomic and firm-specific control variables are used while analysing the liquidity and monetary poli

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Mangla, Divya, and Bharti Parkar. "A STUDY ON CALCULATING, RISK, RETURN AND PROPORTION OF EACH SECURITY IN THE PORTFOLIO DIVERSIFICATION." International Journal of Social Sciences & Economic Environment 6, no. 1 (2021): 08–14. http://dx.doi.org/10.53882/ijssee.2021.0601002.

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Objectives: Applying Sharpe's single index model, the current study seeks to create an optimum capital structure. This is the simplest and most generally utilised model for putting together an ideal portfolio. Design Methodology: The Nifty 50 index data was gathered from the NSE website during a five-year timeframe. The study employs a descriptive research design. The study relies on secondary data. Secondary data is gathered from sources such as the National Stock Exchange (NSE), the Reserve Bank of India (RBI), Money Control, and Yahoo Finance. Findings: Precisely eight equities were identif

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