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              <text>Volatility Clustering in Nifty Energy Index Using GARCH Model</text>
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              <text>ARCH LM; GARCH; High-frequency data; Nifty Energy index; Stationarity test; Volatility</text>
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              <text>Volatility has become increasingly important in derivative pricing and hedging, risk management, and portfolio optimisation. Understanding and forecasting volatility is an important and difficult field of finance research. According to empirical findings, stock market returns demonstrate time variable volatility with a clustering effect. Hence, there is a need to determine the volatility in Indian stock market. The authors use Nifty Energy data to analyse volatility since the Nifty Energy data can to be used to estimate the behaviour and performance of companies that represents petroleum, gas, and power sector. The results reflect that Indian stock market has high volatility clustering.  2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.</text>
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              <text>Balaji L.; Anita H.B.; Ashok Kumar B.</text>
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              <text>Lecture Notes on Data Engineering and Communications Technologies, Vol-131, pp. 667-681.</text>
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              <text>Springer Science and Business Media Deutschland GmbH</text>
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              <text>2023-01-01</text>
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              <text>&lt;a href="https://doi.org/10.1007/978-981-19-1844-5_53" target="_blank" rel="noreferrer noopener"&gt;https://doi.org/10.1007/978-981-19-1844-5_53&lt;/a&gt;
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              <text>Restricted Access</text>
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              <text>ISSN: 23674512</text>
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              <text>English</text>
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              <text>Balaji L., Christ University, Bengaluru, 560029, India; Anita H.B., Christ University, Bengaluru, 560029, India; Ashok Kumar B., Bangalore University, Bengaluru, 560056, India</text>
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