Analysis of the Different Models for Stock Price Prediction
DOI:
https://doi.org/10.54097/6zq6mp91Keywords:
Stock price prediction; ARIMA; recurrent neural network; Logistic regression model.Abstract
As a matter of fact, the stock price prediction is sustained for many years when stocks appeared. People are finding ways to predict the stock prices and find the best price for earning most profits. On this basis, this study will discuss about the stock price prediction in terms of various models including time series models as well as machine learning and deep learning schemes, there are different types of models, and these models have different uses and methods. According to the analysis, this paper find ARIMA model, recurrent neural model, and logistic regression model are available for calculating the stock prices. This is proved by using the data before and calculate the data afterwards. The prices calculated is similar to the real prices. Which means these methods or models are useful for predicting. Overall, these results shed light on guiding further exploration of stock price prediction based on the state-of-art machine learning scenarios.
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