Essays about: "Stock Market Learning"
Showing result 1 - 5 of 86 essays containing the words Stock Market Learning.
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1. Deep Learning Based Sentiment Analysis
University essay from Blekinge Tekniska Högskola/Institutionen för datavetenskapAbstract : Background: Text data includes things like customer reviews and complaints,tweets from social media platforms. When analyzing text-based data, the SentimentModel is used. Understanding news headlines, blogs, the stock market, politicaldebates, and film reviews some of the areas where sentiment analysis is used. READ MORE
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2. Predicting the Movement of the S&P 500 Index using Machine Learning
University essay from Lunds universitet/Nationalekonomiska institutionen; Lunds universitet/Statistiska institutionenAbstract : Predicting the stock market has been a longstanding topic of interest in financial research. It is regarded as a highly challenging but important task given the vital role the financial markets play in shaping the global economies. In this thesis, the goal is to predict the movement of the S&P 500 Index using machine learning methods. READ MORE
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3. Extraction of Global Features for enhancing Machine Learning Performance
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Data Science plays an essential role in many organizations and industries to become data-driven in their decision-making and workflow, as models can provide relevant input in areas such as social media, the stock market, and manufacturing industries. To train models of quality, data preparation methods such as feature extraction are used to extract relevant features. READ MORE
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4. Empirical Asset Pricing via Machine Learning - Evidence from the Chinese stock market
University essay from Handelshögskolan i Stockholm/Institutionen för finansiell ekonomiAbstract : This thesis builds upon existing research on the application of machine learning in asset pricing in the US and European stock markets, by incorporating unique predictive indicators specific to the Chinese stock market, to explore whether machine learning can also be successfully applied in the Chinese stock market. Empirical results show that machine learning models outperform OLS significantly in predicting A-share returns, and this conclusion also applies to different portfolios we have constructed. READ MORE
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5. Personalized Investment Recommendations Using Recommendation Systems
University essay from Lunds universitet/Nationalekonomiska institutionenAbstract : This paper presents a Deep Learning-based Hybrid Recommendation System (DLHR) designed specifically for institutional investors with public portfolio holdings on the Stockholm Stock Exchange. The objective is to provide personalized investment recommendations, complement existing portfolios, and explore untapped cross-selling opportunities. READ MORE