利用TF-IDF特征预测股票价格的隐马尔可夫模型实现

Proceedings of the International Conference on Advances in Information Communication Technology & Computing Pub Date : 2016-08-12 DOI:10.1145/2979779.2979788

V. Ingle, S. Deshmukh

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引用次数: 12

摘要

股票数据分析是一个具有挑战性的研究领域。本文提出的分析方法是利用在线新闻数据来预测股市的高、低等状态。隐马尔可夫模型和提取的特征(如TF-IDF)被用来找出一组公司第二天的股票市场价值。该方法可进一步推广到调整概率值来计算预测的调谐模型。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Hidden Markov Model Implementation for Prediction of Stock Prices with TF-IDF features

Stock data analysis is challenging research area. The proposed analysis works on online news data for prediction of stock market states such as high, low etc. The Hidden Markov Model along with features extracted such as TF-IDF is used to find out next day's stock market value for group of companies. The method can be further extended to adjustment of probability values to calculate tuned model for prediction.

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Proceedings of the International Conference on Advances in Information Communication Technology & Computing

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