0% Complete
English
صفحه اصلی
/
دوازدهمین کنفرانس بین المللی فناوری اطلاعات و دانش
Analysing effect of news polarity on stock market prediction: a machine learning approach
نویسندگان :
Golshid Ranjbaran
1
Mohammad-Shahram Moin
2
Sasan H Alizadeh
3
Abbas Koochari
4
1- دانشگاه آزاد اسلامی واحد علوم و تحقیقات تهران
2- مرکز تحقیقات مخابرات ایران
3- مرکز تحقیقات مخابرات ایران
4- دانشگاه آزاد اسلامی واحد علوم و تحقیقات تهران
کلمات کلیدی :
News, stock price prediction, sentiment analysis, machine learning
چکیده :
In finance, the stock market and its trends are volatile in nature. In the stock market, which is dynamic, complex, nonlinear and non-parametric, accurate forecasting is crucial for trading strategy. This need attracted researchers to detect fluctuations and to predict the next move. It is assumed that news articles affect the stock market. In this work, non-measurable data like financial news headlines has been transferred into the measurable data. We investigated the relationship between news and their impact on stock prices. To show this relationship, we applied the sentiment analysis data and the price difference between the day before the news was published and the day of the news to the classic machine learning models such as SVR, BayesianRidge, LASSO, Decision tree and Random forest. The observations showed that SVM performs well in all tests. The prediction error in this model is 0.35, which is much less than that of the random news tagging. Also based on our tests, using a computer for tagging is as good as manual tagging.
لیست مقالات
لیست مقالات بایگانی شده
Writer-Independent Signature Verification with Enhanced AlexNet and Preprocessing Analysis
Mohammadreza Gholipour Shahraki - Mohammad Ghasemzadeh
خوشه بندی ویسیلاب های دو آوایی زبان فارسی در کاربرد لب خوانی
مهسا هدایتی پور - دکتر یاسر شکفته - دکتر محسن ابراهیمی مقدم
شناسایی جایگاه مالونیلاسیون در پروتئینها با بهرهگیری از استخراج ویژگی و تکنیکهای پردازش زبان طبیعی
حنانه رجبیون - محمد قاسم زاده - وحید رنجبر بافقی
Sigma: A Secure Federated Network Gaming Platform
Keyhan Mohammadi - Reza Ebrahimi Atani
یک روش کارآمد جهت تشخیص آنلاین حملات DRDoS به سرویس های مبتنی بر UDP درمعماری SDN با استفاده از الگوریتم های یادگیری ماشین
میترا اکبری کهنه شهری - دکتر رضا محمدی - دکتر محمد نصیری میترا اکبری کهنه شهری - رضا محمدی - محمد نصیری -
Non-Linear Control of Cancer Model, Considering the Drug Resistance Using Feedback Based Chemotherapy Approach
Danial Kiaei - Hami Tourajizadeh
An Eco-Friendly Cosmopolitan (EFC) by Recycling Scientific/Industrial Towns (RSITs)
Engineer Reza Khalilian - Dr. Abdalhossein Rezai - Dr. Mohammadreza Talakesh
GanjNet: Leveraging Network Modeling with Large Language Models for Persian Word Sense Induction
Amir Mohammad Kouyeshpour - Hadi Veisi - Saman Haratizadeh
Analysing effect of news polarity on stock market prediction: a machine learning approach
Golshid Ranjbaran - Dr Mohammad-Shahram Moin - Dr Sasan H Alizadeh - Dr Abbas Koochari
A Novel Decentralized Privacy Preserving Federated Learning Model for Healthcare Applications
Saba Ameri - Reza Ebrahimi Atani
بیشتر
ثمین همایش، سامانه مدیریت کنفرانس ها و جشنواره ها - نگارش 42.5.2