Using The NewsInn Algorithm To Predict Stock Market Movements Two Days In Advance

Radu Nicoara

ISBN 10: 3668078858 / ISBN 13: 9783668078857

Published by GRIN Verlag, 2015

About this Item

Using The NewsInn Algorithm To Predict Stock Market Movements Two Days In Advance | Radu Nicoara | Taschenbuch | 16 S. | Englisch | 2015 | GRIN Verlag | EAN 9783668078857 | Verantwortliche Person für die EU: GRIN Publishing GmbH, Waltherstr. 23, 80337 München, info[at]grin[dot]com | Anbieter: preigu Print on Demand.

Seller Inventory # 104110927

Bibliographic Details

• Title: Using The NewsInn Algorithm To Predict Stock Market Movements Two Days In Advance
• Publisher: GRIN Verlag
• Publication Date: 2015
• Language: English
• ISBN 10: 3668078858
• ISBN 13: 9783668078857
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 210W x 148H x 2D millimeters 210 millimeters width by 148 millimeters height by 2 millimeters depth
• Weight: 40 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Research Paper (postgraduate) from the year 2015 in the subject Business economics - Banking, Stock Exchanges, Insurance, Accounting, , language: English, abstract: NewsInn is an Artificial Intelligence Algorithm that parses the major news publications for news articles, groups them based on the main story, and presents them in order of importance. To do a sentiment analysis on each article, the algorithm used a derivative of SentiWord, but it quickly became clear that the library was not created to be used in a news Environment. So a new library was developed, that would better suit the case it was being used in. It manages to provide a good estimate of the impact that the text of an article has. Since the stock market is heavily affected by world problems, and therefore, world news, it is highly likely that a general sentiment analysis of the news would produce a result directly related to the general sentiment of the public on the world affairs. This would theoretically, in time, affect the stock market. The time-to market of world news we estimated to be of a few days, since only huge golbal events have the power to change the stock price in-day. Therefore we started testing at a one-day offset, then went on for two, three, and even four days offset between the news data and the stock data. We only kept the data that provided the highest accuracy in predicting the stock market indexes flow.