• Title/Summary/Keyword: Nifty Bank Index

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Expiration-Day Effects on Index Futures: Evidence from Indian Market

  • SAMINENI, Ravi Kumar;PUPPALA, Raja Babu;MUTHANGI, Ramesh;KULAPATHI, Syamsundar
    • The Journal of Asian Finance, Economics and Business
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    • v.7 no.11
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    • pp.95-100
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    • 2020
  • Nifty Bank Index has started trading in futures and options (F&O) segment from 13th June 2005 in National Stock Exchange. The purpose of the study is to enhance the literature by examining expiration effect on the price volatility and price reversal of Underlying Index in India. Historical data used for the current study primarily comprise of daily close prices of Nifty Bank which is the only equity sectoral index in India which is traded in derivatives market and its Future contract value is derived from the underlying CNX Bank Index during the period 1st January 2010 till 31st March 2020. To check stationarity of the data, Augmented Dicky Fuller test was used. The study employed ARMA- EGARCH model for analysing the data. The empirical results revealed that there is no effect on the mean returns of underlying Index and EGARCH (1,1) model furthermore shows there is existence of leverage effect in the Bank Index i.e., negative shocks causes more fluctuations in the Index than positive news of similar magnitude. The outcome of the study specifies that there is no effect on volatility on the underlying sectoral index due to expiration days and also observed no price reversal effect once the expiration days are over.

Envisaging Macroeconomics Antecedent Effect on Stock Market Return in India

  • Sivarethinamohan, R;ASAAD, Zeravan Abdulmuhsen;MARANE, Bayar Mohamed Rasheed;Sujatha, S
    • The Journal of Asian Finance, Economics and Business
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    • v.8 no.8
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    • pp.311-324
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    • 2021
  • Investors have increasingly become interested in macroeconomic antecedents in order to better understand the investment environment and estimate the scope of profitable investment in equity markets. This study endeavors to examine the interdependency between the macroeconomic antecedents (international oil price (COP), Domestic gold price (GP), Rupee-dollar exchange rates (ER), Real interest rates (RIR), consumer price indices (CPI)), and the BSE Sensex and Nifty 50 index return. The data is converted into a natural logarithm for keeping it normal as well as for reducing the problem of heteroscedasticity. Monthly time series data from January 1992 to July 2019 is extracted from the Reserve Bank of India database with the application of financial Econometrics. Breusch-Godfrey serial correlation LM test for removal of autocorrelation, Breusch-Pagan-Godfrey test for removal of heteroscedasticity, Cointegration test and VECM test for testing cointegration between macroeconomic factors and market returns,] are employed to fit regression model. The Indian market returns are stable and positive but show intense volatility. When the series is stationary after the first difference, heteroskedasticity and serial correlation are not present. Different forecast accuracy measures point out macroeconomics can forecast future market returns of the Indian stock market. The step-by-step econometric tests show the long-run affiliation among macroeconomic antecedents.