title: ÐÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð¸Ð·Ð¼ÐµÐ½ÐµÐ½Ð¸Ð¹ ÑÐµÐ½ Ð°ÐºÑÐ¸Ð¹ ÑÐ¾Ð½Ð´Ð¾Ð²Ð¾Ð³Ð¾ ÑÑÐ½ÐºÐ° Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ ÑÐµÐºÑÑÑÐµÐ½ÑÐ½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð¸ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° ÑÐ¾Ð½Ð°Ð»ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÐºÑÑÐ°
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Forecasting trend in stock market stock prices using recurrent neural network and sentiment analysis
Creators: name: ÐÐ¸Ð½Ð¾Ð³ÑÐ°Ð´Ð¾Ð², ÐÐ°Ð²ÐµÐ»
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2021
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ
Ð°Ð½Ð°Ð»Ð¸Ð· ÑÐ¾Ð½Ð°Ð»ÑÐ½Ð¾ÑÑÐ¸ ÑÐµÐºÑÑÐ°
Ð¼Ð°ÑÐ¸Ð½Ð½Ð¾Ðµ Ð¾Ð±ÑÑÐµÐ½Ð¸Ðµ
ÑÐ¾Ð½Ð´Ð¾Ð²ÑÐ¹ ÑÑÐ½Ð¾Ðº
forecasting
sentiment analysis
machine learning
stock market

description: ÐÐ°Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¿Ð¾ÑÐ²ÑÑÐµÐ½Ð° Ð¿ÑÐ°ÐºÑÐ¸ÑÐµÑÐºÐ¾Ð¼Ñ Ð¿ÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐµÐºÑÑÑÐµÐ½ÑÐ½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð¿ÑÐ¸ ÑÐ°Ð±Ð¾ÑÐµ Ñ ÑÐµÐºÑÑÐ¾Ð¼, ÐºÐ¾ÑÐ¾ÑÑÐ¹ Ð²Ð»Ð¸ÑÐµÑ Ð½Ð° ÑÐµÐ½Ñ Ð°ÐºÑÐ¸Ð¹ ÑÐ¾Ð½Ð´Ð¾Ð²Ð¾Ð³Ð¾ ÑÑÐ½ÐºÐ°. Ð ÑÐ°Ð±Ð¾ÑÐµ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½ Ð¿Ð¾Ð´ÑÐ¾Ð´ Ðº ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ ÑÐ°ÐºÐ¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð¸ Ð¾ÑÐµÐ½ÐºÐ° Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½ÑÑ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð½ÐµÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÐ¾Ð². Ð¦ÐµÐ»Ñ ÑÐ°Ð±Ð¾ÑÑ â Ð¼Ð¾Ð´ÐµÐ»Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ ÑÐ¸ÑÑÐµÐ¼Ñ Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ Ð½Ð°Ð¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð¸Ð·Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐµÐ½ ÐºÐ¾ÑÐ¸ÑÐ¾Ð²Ð¾Ðº ÐºÐ¾Ð¼Ð¿Ð°Ð½Ð¸Ð¹ ÑÐµÐºÑÐ¾ÑÐ° Ð¸Ð½ÑÐ¾ÑÐ¼Ð°ÑÐ¸Ð¾Ð½Ð½ÑÑ ÑÐµÑÐ½Ð¾Ð»Ð¾Ð³Ð¸Ð¹ Ð¸ ÑÐµÐºÑÐ¾ÑÐ° Ð½ÐµÑÑÐ¸ Ð¸ Ð³Ð°Ð·Ð°. Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ Ð±ÑÐ»Ð¸ ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ñ ÑÐ°Ð·Ð»Ð¸ÑÐ½ÑÐµ ÑÐ¿Ð¾ÑÐ¾Ð±Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°Ð½Ð¸Ñ Ð½Ð°Ð¿ÑÐ°Ð²Ð»ÐµÐ½Ð¸Ñ Ð´Ð²Ð¸Ð¶ÐµÐ½Ð¸Ñ ÑÐµÐ½ Ð°ÐºÑÐ¸Ð¹ ÑÐ¾Ð½Ð´Ð¾Ð²Ð¾Ð³Ð¾ ÑÑÐ½ÐºÐ°, ÑÐ°Ð·Ð¾Ð±ÑÐ°Ð½Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ð¸ Ð² ÑÐµÐ°Ð»ÑÐ½ÑÑ ÑÐ°Ð±Ð¾ÑÐ°Ñ. ÐÐ° Ð¾ÑÐ½Ð¾Ð²Ðµ Ð½Ð¸Ñ Ð±ÑÐ» Ð¿ÑÐµÐ´Ð»Ð¾Ð¶ÐµÐ½ Ð¸ ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼ Ð½Ð° Ð¾ÑÐ½Ð¾Ð²Ðµ ÑÐµÐºÑÑÑÐµÐ½ÑÐ½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð¸ Ð°Ð½Ð°Ð»Ð¸Ð·Ð° Ð½Ð¾Ð²Ð¾ÑÑÐ½ÑÑ Ð·Ð°Ð³Ð¾Ð»Ð¾Ð²ÐºÐ¾Ð², Ð¾ÑÐ¾Ð±ÑÐ°Ð½Ð½ÑÑ Ð¿Ð¾ Ð´Ð°Ð½Ð½ÑÐ¼ Ð¸Ð·Ð¼ÐµÐ½ÐµÐ½Ð¸Ñ ÑÐµÐ½ Ð°ÐºÑÐ¸Ð¹. ÐÐ¾Ð´ÐµÐ»Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð° Ð½Ð° ÑÐ·ÑÐºÐµ Python Ñ Ð¿Ð¾Ð´ÐºÐ»ÑÑÐµÐ½Ð¸ÐµÐ¼ Ð´Ð¾Ð¿Ð¾Ð»Ð½Ð¸ÑÐµÐ»ÑÐ½ÑÑ Ð±Ð¸Ð±Ð»Ð¸Ð¾ÑÐµÐº. Ð Ð°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð½Ð°Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð° Ð¿ÑÐ¾Ð´ÐµÐ¼Ð¾Ð½ÑÑÑÐ¸ÑÐ¾Ð²Ð°Ð»Ð° ÑÐ¾ÑÐ½Ð¾ÑÑÑ Ð²ÑÑÐµ, ÑÐµÐ¼ Ñ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼-Ð°Ð½Ð°Ð»Ð¾Ð³Ð¾Ð², Ð¸ÑÐ¿Ð¾Ð»ÑÐ·ÑÑÑÐ¸Ñ ÑÑÐ¾Ð¶Ð¸Ðµ Ð¿Ð¾Ð´ÑÐ¾Ð´Ñ, Ð±Ð»Ð°Ð³Ð¾Ð´Ð°ÑÑ Ð±Ð¾Ð»ÐµÐµ ÑÑÐ°ÑÐµÐ»ÑÐ½Ð¾Ð¼Ñ Ð¾ÑÐ±Ð¾ÑÑ Ð²ÑÐ¾Ð´Ð½ÑÑ Ð´Ð°Ð½Ð½ÑÑ Ð¸ Ð½ÐµÐ±Ð¾Ð»ÑÑÐ¸Ñ Ð¿Ð¾ÑÐ»ÐµÐ´Ð¾Ð²Ð°ÑÐµÐ»ÑÐ½Ð¾ÑÑÐµÐ¹ ÑÐ»Ð¾Ð². Ð ÐµÐ°Ð»Ð¸Ð·Ð¾Ð²Ð°Ð½Ð½Ð°Ñ ÑÐ¸ÑÑÐµÐ¼Ð° Ð±ÑÐ»Ð° ÑÐ°ÑÑÐ¼Ð¾ÑÑÐµÐ½Ð° Ð´Ð»Ñ Ð´Ð²ÑÑ ÑÐµÐºÑÐ¾ÑÐ¾Ð² ÑÐ¾Ð½Ð´Ð¾Ð²Ð¾Ð³Ð¾ ÑÑÐ½ÐºÐ°, Ð½Ð¾ Ð¼Ð¾Ð¶ÐµÑ Ð±ÑÑÑ Ð¿ÑÐ¸Ð¼ÐµÐ½Ð¸Ð¼Ð° Ð¸ Ð´Ð»Ñ Ð¾ÑÑÐ°Ð»ÑÐ½ÑÑ.
description: This master's thesis covers the practical application of recurring neural network when working with text that affects stock prices of the stock market. The paper considers an approach to the implementation of such a neural network and an assessment of the results obtained with its help. The goal of this work is to develop a system for predicting the direction of stock price changes of companies in IT sector and energy sector. In the course of the work, various approaches of implementation the prediction of stock market pricesâ trend were considered and the realizations in real works were analyzed. On this basis, an algorithm was proposed and implemented based on a recurrent neural network and analysis of news headlines selected according to the data of stock pricesâ changes. The model is implemented using Python with the inclusion of additional libraries. The developed program has demonstrated higher accuracy than analog programs using similar approaches, due to more thorough input data pre-processing and small sequences of words. The implemented system was considered for two sectors of the stock market, but it can be applied to the other sectors.