Sökning: "predict stock"

Visar resultat 11 - 15 av 248 uppsatser innehållade orden predict stock.

1. 11. Aktiemarknadsprognoser: En jämförande studie av LSTM- och SVR-modeller med olika dataset och epoker

   Kandidat-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)

   Författare :Mads Nørklit Johansen; Jagtej Sidhu; [2023]
   Nyckelord :Stock Market Prediction; Long-Short Term Memory; Support Vector Regression; Prediction Accuracy; Financial Investments;

   Sammanfattning : Predicting stock market trends is a complex task due to the inherent volatility and unpredictability of financial markets. Nevertheless, accurate forecasts are of critical importance to investors, financial analysts, and stakeholders, as they directly inform decision-making processes and risk management strategies associated with financial investments. LÄS MER

3. 12. Predicting the Movement of the S&P 500 Index using Machine Learning

   Magister-uppsats, Lunds universitet/Nationalekonomiska institutionen; Lunds universitet/Statistiska institutionen

   Författare :Bakary Bah; [2023]
   Nyckelord :Machine Learning; S P 500 Index; Random Forest; Logistic Regression; Business and Economics;

   Sammanfattning : 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. LÄS MER

4. 13. Exploring the Impact of Centrality Measures on Stock Market Performance in Stockholm Market: A Comparative Study

   Kandidat-uppsats, Mälardalens universitet/Utbildningsvetenskap och Matematik

   Författare :Tarek Hasna; [2023]
   Nyckelord :Centrality measures; Degree centrality; Eigenvector centrality; Betweenness centrality; Closeness centrality;

   Sammanfattning : Centrality measures in network analysis have become a popular measurement tool for identifying coherent nodes within a network. In the context of stock markets, the centrality measure helps to identify key performing ele- ments and strengths for specific stocks and determine their impact on disrupting market value and performance. LÄS MER

5. 14. Extraction of Global Features for enhancing Machine Learning Performance

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Abyel Tesfay; [2023]
   Nyckelord :Machine Learning; Deep Learning; Feature Extraction; Global Features; Time-series data; Bioprocessing; Maskininlärning; Djupinlärning; Funktionsextraktion; Globala Funktioner; Tidsserie data; Biobearbetning;

   Sammanfattning : 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. LÄS MER

7. 15. Building Predictive Models for Stock Market Performance : En studie om maskininlärning och deras prestanda

   Kandidat-uppsats, Uppsala universitet/Institutionen för informatik och media

   Författare :Gabriel Wennmark; Felix Lindgren; [2023]
   Nyckelord :machine learning; classification; stock market; OMXSPI; support vector machine; logistic regression; decision tree; prediction model; maskininlärning; klassifikation; aktiemarknad; OMXSPI; support vector machine; logistisk regression; beslutsträd; prediktionsmodell;

   Sammanfattning : Today it is important for investors to identify which stocks that will result in positive returns in order for the right decision to be made when trading on the stock market. For decades it has been an area of interest for academics, and it is still challenging due to many difficulties and problems. LÄS MER