Essays about: "Stock Market Learning"
Showing result 16 - 20 of 86 essays containing the words Stock Market Learning.
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16. Scenario Generation for Stress Testing Using Generative Adversarial Networks : Deep Learning Approach to Generate Extreme but Plausible Scenarios
University essay from Umeå universitet/Institutionen för matematik och matematisk statistikAbstract : Central Clearing Counterparties play a crucial role in financial markets, requiring robust risk management practices to ensure operational stability. A growing emphasis on risk analysis and stress testing from regulators has led to the need for sophisticated tools that can model extreme but plausible market scenarios. READ MORE
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17. Classifying High-Growth Manufacturing Firms on the Swedish Stock Market:A Comparative Study Between the Logistic Regression, Support Vector Machine and Artificial Neural Network
University essay from Lunds universitet/Nationalekonomiska institutionenAbstract : This is a comparative study between two modern machine learning algorithms, the Support Vector Machine and Artificial neural network, and one traditional econometric model, the Logistic regression. The main objective is to compare their performance by classifying high-growth companies. READ MORE
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18. Stock Price Prediction with Social Media Sentiment
University essay from Göteborgs universitet/Företagsekonomiska institutionenAbstract : This thesis investigates the correlation effects between social media sentiments and the stock price of AMZN and TSLA, by utilizing pre-trained machine learning models, so-called transformers, and lexicon-based models. The comments were fetched from two sources, Reddit and Twitter. READ MORE
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19. Prediction of Stock Returns Using Accounting Data with a Machine Learning Approach
University essay from Göteborgs universitet/Graduate SchoolAbstract : The relationship between accounting data and stock price prediction has been a hot topic for over half a century. Researchers have been trying to identify the relationship and investigate how it may be useful when trying to improve prediction accuracy. READ MORE
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20. Predicting the Options Expiration Effect Using Machine Learning Models Trained With Gamma Exposure Data
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The option expiration effect is a well-studied phenome, however, few studies have implemented machine learning models to predict the effect on the underlying stock market due to options expiration. In this paper four machine learning models, SVM, random forest, AdaBoost, and LSTM, are evaluated on their ability to predict whether the underlying index rises or not on the day of option expiration. READ MORE
