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In this study, we predict the daily volatility of the S&P CNX NIFTY market index of India using the basic "heterogeneous autoregressive" (HAR) and its variant. In doing so, we estimated several HAR and Log form of HAR models using different regressor. The different regressors were obtained by...
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In this study, a vector autoregression (VAR) model with time-varying parameters (TVP) to predict the daily Indian rupee (INR)/US dollar (USD) exchange rates for the Indian economy is developed. The method is based on characterization of the TVP as an optimal control problem. The methodology is a...
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"This book enumerates the challenges and creative solutions and tools to apply when using big data in operations management, outlining revolutionary concepts and applications that help businesses predict customer behavior along with applications of artificial neural networks, predictive...
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