基于ARIMA的Prophet时间序列股票市场预测

C. Madhuri, Mukesh Chinta, V. Kumar
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引用次数: 5

摘要

从一开始,人类的根本目标就是让生活变得容易。全世界都认为财富会使生活舒适和奢华。人类最普遍的观念之一是,赚钱的最佳方式之一是投资于预期会产生巨大结果的股票市场。需要开发一个智能系统,根据基本面、统计和技术趋势等各种指标进行预测。然而,没有一个好的预测模型能够成功地持续击败市场趋势。传统上,对于时间序列数据,预测一般是基于过去的历史数据和市场趋势,可以计算历史相关数据和预测。综上所述,没有这样的系统可以根据用户对投资类型的选择和用户愿意承担的风险标准来计算预测。因此,在本文中,我们试图演示该技术以获得最准确的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stock Market Prediction for Time-series Forecasting using Prophet upon ARIMA
Since the beginning, the fundamental goal of man is to make life easy to live. The whole world believes that wealth would make life comfortable and luxurious. One of the most common notion among humans is that one of the best way to make money is to invest in stock markets which are expected to have tremendous results. There is a requirement to develop an intelligent system to perform predictions based on various indicators like fundamental, statistical and technical trends. However, there is no one good predictive model that has been successful to beat the trends in market continuously. Traditionally for time series data, the predictions are in general performed based on past historical data and market trends, historical correlation data and projections can be calculated. Above all said, there is no such system that calculates the predictions based on users selection on investment type and on risk criteria user is willing to take. So in this paper, we tried to demonstrate the technique(s) to get most accurate results.
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