News Text Mining for Gold Price Prediction

, M.Sc. Thesis Sharif University of Technology Farzam, Mohammad Sina (Author) ; Izadi, Mohammad (Supervisor)

Abstract

Textual news published in the media on a daily basis is a large and valuable source of unstructured data that can be used to analyze and model the financial market by using text mining methods. The purpose of this study is to design a news-reading system for economic analysis and modeling of gold prices using features extracted from textual news and text mining methods; it seeks to enable the machine to read news like financial analysts then analyze and forecast the economic situation and market trends. For this purpose, we collected news from the website of an Iranian economic news agency. To design the economic analyzer, we extracted important economic, political, and social factors from...

How News Affect the Value of Bitcoin

, M.Sc. Thesis Sharif University of Technology Jahani, Ali (Author) ; Talebian, Masoud (Supervisor) ; Hajizadeh, Iman (Co-Supervisor)

Abstract

This research investigates the impact of Bitcoin and cryptocurrency news along with macroeconomic and financial indicators, on Bitcoin price fluctuations for two years (May 2016-2018). The reason for this examination is due to high variations of Bitcoin price in the late 2017 and beginning of 2018, while academic research focusing on Bitcoin price are mostly conducted before 2017. Findings show that the number of news with positive and negative contexts, and news related to cryptocurrency technology have a direct relationship with Bitcoin price change. The other result shows that among news concentrated on Bitcoin, the most effective is regarding adverse incidents, famous people concerns and...

Cryptocurrency Price Prediction based on Text Analysis

, M.Sc. Thesis Sharif University of Technology Shahsahebi, Mohammad Reza (Author) ; Akhavan Niaki, Taghi (Supervisor)

Abstract

Investors' sentiment toward a coin is very vital in cryptocurrencies' markets. If traders do not invest in a coin, its price will decline; therefore, it is essential for investors to take others' sentiment into account when they want to buy or sell a coin. Text mining on social media is one technique that can help traders understand others' opinions about the coin they are trading. Hence, in this research, we try to predict the top three cryptocurrencies, Bitcoin, Etheruem, and Litecoin, price movement for the next day based on Twitter posts and News title using text mining. In this research, we found out that considering all tweets can reduce our model's accuracy, and for better accuracy,...

Semantic Analysis and Event Detection Using Deep Learning for Stock Prediction

, M.Sc. Thesis Sharif University of Technology Basirian Jahromi, Ali (Author) ; Sameti, Hossein (Supervisor) ; Bokaei, Mohammad Hadi (Supervisor)

Abstract

News plays a very important role in stock market trading. Nowadays news from a different part of the world and about different fields can be accessed easily, and for a successful trade, it is necessary to analyze accurately and use this big data and information as soon as possible. For this reason, this thesis tries to present and study models based on Deep Learning networks and Natural Language Processing for financial news analysis and predicting stock indices movement. This research takes advantage of a language model for learning and representing news text, and beside this language model it uses deep learning networks at multiple levels to extract proper features from each news in a day...