96 research outputs found

    Does the Nature of Index and Liquidity Influence the Mispricing in Future Contracts in India?

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    In this study, we investigate the variations in the mispricing of futures in Nifty (benchmark index), Bank Nifty and Nifty IT. Using a regression model on 1230 observations for the period of 1 January 2014 to 31 December 2018, we find no significant mispricing exists in the last week to the expiry of the contract in all three indices. This finding supports the existing literature that as the contract moves towards the maturity date, its value converges the market value. However, the main highlight of the paper is to reveal the difference in the life of mispricing in different indices. This difference in mispricing can be allocated to the liquidity in that indices. We report that being the most liquid, Bank Nifty is having mispricing only in 1 week (first week) of the contract, after that no significant mispricing exists in mispricing, Nifty shows significant mispricing for the first two weeks and Nifty IT shows mispricing for all weeks except last week. This is the pioneering work which considers the sectoral differences while evaluating futures mispricing. The findings of this study will provide a useful insight to the regulator and investors

    Testing of Semi–Strong Form of Efficiency: an Empirical Study on Stock Market Reaction Around Dividend Announcement

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    Purpose: The purpose of this study is to examine the efficiency of the Indian stock market of the Nifty IT index over the dividend announcement for five years from 2016 to 2020.   Theoretical framework: A reward procured by the shareholders on their equities is, of course, the dividend. A leading area of concern is the dividend announcement. According to the theory of efficient markets, stock prices accurately reflect all available information. This demonstrates that the prices are correct and fair. The market should therefore respond immediately to an event in this instance the dividend announcement. Therefore, depending on publicly available information will not provide investors with the possibility to consistently generate extraordinary returns.   Design/ methodology/ approach: The study attempts to validate the event study approach while investigating the semi-strong form of efficiency. Daily share prices of five companies out of ten of the Nifty IT index were observed to test the Efficient Market Hypothesis. 31 days event window has been employed to calculate the abnormal returns of the selected sample around dividend issue announcements also t-test was applied to assess the level of significance.   Findings: The study found that the stock market was efficient in its semi strong form and the investors could not make excess returns over the dividend announcement of the Nifty IT index.   Research, Practical & social implications: This study eliminates the possibility for investors to beat the average market returns. It is significant since it affects stock market investment choices.   Originality/ Values: The majority of studies are only able to analyse the overall average abnormal return and cumulative average abnormal return of chosen companies; it is difficult to locate studies that focus on the abnormal return for each individual company. The t test for each company-wise abnormal returns, overall average abnormal returns, and cumulative average abnormal returns were acquired and tested at the 5% level of significance in order to determine the significance.

    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

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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 and NIFTY Pharma Indice

    Interest Rate and Stock Prices – Evidence from India

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    This paper analyses the relationship between interest rates and stock prices in the context of India. The objectives of the paper are to investigate the impact of interest rates on stock prices and build a model for forecasting stock prices based on interest rates. Karl Pearson’s coefficient of correlation and linear regression model have been applied on the time series data of eleven sectoral indices published by National Stock Exchange and Bank rates published by Reserve Bank of India for a 10 year period from 2005 and 2014. Karl Pearson’s coefficient of correlation is tested for significance and coefficient of determination is also computed to assess the extent of fit of the regression model in forecasting the stock prices. The results show that six sectors (auto, bank, FMCG, financial services, IT and Pharma) out of eleven sectors were significantly impacted by the interest rate. The overall market represented by the market index (Nifty Fifty) was also impacted by the interest rate. Keywords: Interest rate, Stock prices, Karl Pearson’s coefficient of correlation, Linear Regression Mode

    The Impact of Demonetization Process on the Performance of Nifty

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    This paper investigates the impact of demonetization process on the performance of Nifty 50 and its Sectorial Indices. The study uses data of closing prices from 28 June 2016 up to 20 March 2017. The study employs descriptive statistics, paired sample T test and ANOVA to evaluate the impact of demonetization process on the performance of Nifty 50 and its Sectorial Indices. It has found that there is statistical significance at the level of 5% that Nifty 50 dropped after the demonetization event as compared to the pre demonetization event. Further, the results reveal that most of Sectorial Indices of Nifty 50 sloped downward post demonetization event and the significance of the statistical results are varied from one sector to another. It is recommended that periodic review of the policy should be made to iron out the negative impacts of demonetization. Also, it is imperative to evaluate the impact of demonetization on the short, medium, and long run to avoid any grey areas for any future policy regarding cashless economy or demonetization

    ANALYSIS OF IT COMPANIES USING TOOLS AND TECHNIQUES OF TECHNICAL ANALYSIS

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    Technical analysis in its basic sense is the analysis of the market action through charts to predict future price movements. There are various tools and techniques to perform technical analysis like moving averages, charting techniques, MACD, ROC, RSI, etc. For this research, RSI (Relative Strength Index) indicator will be used to predict future price movements and to determine whether the shares are overbought or not. The samples selected from the NIFTY-IT index based on market capitalization are Infosys Ltd., Tech-Mahindra Ltd. and Wipro Ltd. The objectives of this research are to study the price movement of the shares of selected companies and use RSI indicator to know the momentum of price change and advice the investors in taking investing decisions

    Impact of Covid19 lockdown on NSE India indexes

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    The covid19 pandemic had forced the Government of India to impose a nationwide lockdown. The present study aims to investigate the impact of lockdown on various NSE India indexes. Event study technique which is used to calculate the abnormal return of a stock has been used. The closing price of 11 NSE India indexes has been used for the analysis. A window period of (+40, -40) days pre and post the event day has been selected. Two-tailed test has been used to test the null hypothesis both at 5% and 1% level of significance. The result of the study shows that most of the indexes had abnormal returns
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