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Stock Price Prediction Using Facebook Prophet and Arima Models

Publication Type : Conference Paper

Publisher : IEEE

Source : 2021 6th International Conference for Convergence in Technology (I2CT), Maharashtra, India, 2021, pp. 1-7

Url : https://ieeexplore.ieee.org/document/9418057

Campus : Amritapuri

School : School of Engineering

Department : Electronics and Communication

Year : 2021

Abstract : With the ongoing pandemics alike COVID-19 patronage such as stock markets, textiles become subsided. Stock market prognostication is the appearance of seeking to circumscribe the anticipated marketability of stocks and different financial apparatuses patronized on an exchange. Prophesying how the retail valuation will execute is one of the ultimate back-breaking contrivances to the predicament. Retail prediction is significant for quantitative interpreters and investment organizations. Retail valuation prophecy is predominant for merit expenditure in the retail market. Analyzing the valuation interrelationship of duplet assets for the anticipated period of time is essential in portfolio optimization. The recommended explication is catholic as it comprises preprocessing of the retail advertise dataset, application of various exploratory analysis procedures, collaboration beside custom-built algorithms for retail valuation bias prognosis. In this case, Facebook Prophet and Arima models are used in forecasting the retail valuation of future stocks that are used to analyze future values of stock markets and how it varied from previous stock markets. With the circumstantial architecture and consideration of conjecture premises and data pre-processing techniques, this effort commits to retail estimate analysis.

Cite this Research Publication : A. Garlapati, D. R. Krishna, K. Garlapati, N. m. Srikara Yaswanth, U. Rahul and G. Narayanan, "Stock Price Prediction Using Facebook Prophet and Arima Models," 2021 6th International Conference for Convergence in Technology (I2CT), Maharashtra, India, 2021, pp. 1-7, doi: 10.1109/I2CT51068.2021.9418057.

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