STOCK PRICE PREDICTION USING TIME SERIES - Sateesh Kumar, Kanagala
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The ARIMA model and the EXPONENTIAL SMOOTHING model for stock price prediction were given in this book. Each algorithm identifies the stock data set of all five institutions, according to the evaluations of these two models. The ARIMA model test results showed that it can reliably predict stock prices in the short term. This can lead to beneficial investment decisions for stock market speculators. The ARIMA model may be ready to compete with other short-term prediction models based on the findings obtained. A wide range of frequency values can be used using exponential smoothing. The…mehr

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Produktbeschreibung
The ARIMA model and the EXPONENTIAL SMOOTHING model for stock price prediction were given in this book. Each algorithm identifies the stock data set of all five institutions, according to the evaluations of these two models. The ARIMA model test results showed that it can reliably predict stock prices in the short term. This can lead to beneficial investment decisions for stock market speculators. The ARIMA model may be ready to compete with other short-term prediction models based on the findings obtained. A wide range of frequency values can be used using exponential smoothing. The Exponential smoothing approach was chosen for a single time series that followed a pattern in terms of order selection. There are many well-known time series techniques in the ARIMA. The design section of ARIMA was critical, delivering a nearly straight line.
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Autorenporträt
Il Dr. K Sateesh Kumar lavora come professore assistente presso lo SNIST di Hyderabad. Le sue aree di interesse sono l'elaborazione digitale delle immagini, il telerilevamento e l'apprendimento automatico, ecc. Ha diverse pubblicazioni internazionali in riviste e conferenze rinomate.