Financial Time Series Analysis and Forecasting with Statistical Inference and Machine Learning

Abstract:

Time series data and its practical applications lie across diverse domains: Finance, Medicine, Environment, Education and more. Comprehensive analysis and optimized forecasting can help us understand the nature of the data and better prepare us for the future. Financial Time series data has been a heavily researched subject in the present and in the previous decades. Statistics, Machine Learning (ML) & Deep Learning (DL) models have been implemented to forecast the stock market and make data informed decisions. However, these methods have not been thoroughly explored, analysed in context of the Indian Stock Market. In this paper we attempt to implement evaluate the avant-garde statistical, machine learning methods for Financial Time Series Analysis & Forecasting on Indian Stock Market Data.

• Periodical: Advances in Science and Technology (Volume 124)
• Pages: 418-425
• DOI: https://doi.org/10.4028/p-sp20ub
• Online since: February 2023
• Authors: Sarvesh Vishnu, M. Uma*
• Keywords: ARIMA, Financial Time Series, Indian Stock Market, Stacked – LSTM, Statistical Inference

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