Sökning: "Learning Stocks"

Visar resultat 1 - 5 av 40 uppsatser innehållade orden Learning Stocks.

  1. 1. Stock Price Predictions for FAANG Companies Using Machine Learning Models

    Kandidat-uppsats, Lunds universitet/Statistiska institutionen

    Författare :Hugo Dahlquist; Fredrik Fourong; [2024]
    Nyckelord :Random Forest; Artificial Neural Networks; Stock prices; Predictions.; Mathematics and Statistics;

    Sammanfattning : The financial industry is one of the highest grossing sectors in the world as it is estimated to represent 24\% of the global economy. As most companies want their asset value to increase, it is of high interest to make good investments which will increase in either the short or long run. LÄS MER

  3. 2. Dynamik och tillförlighet i finansiell prognostisering : En analys av djupinlärningsmodeller och deras reaktion på marknadsmanipulation

    M1-uppsats, KTH/Hälsoinformatik och logistik

    Författare :Aya Zawahri; Nanci Ibrahim; [2024]
    Nyckelord :LOB; market manipulation; spoofing; layering; DeepLOB; DeepLOB-Attention; TCN; DeepLOB-seq2seq; DTNN; ITCH; parsing.; LOB; marknadsmanipulation; spoofing; layering; DeepLOB; DeepLOB-Attention; TCN; DeepLOB-seq2seq; DTNN; ITCH; parsing.;

    Sammanfattning : Under åren har intensiv forskning pågått för att förbättra maskininlärningsmodellers förmåga att förutse marknadsrörelser. Trots detta har det, under finanshistorien, inträffat flera händelser, såsom "Flash-crash", som har påverkat marknaden och haft dramatiska konsekvenser för prisrörelserna. LÄS MER

  4. 3. Predicting the Impact of Supply Chain Disruptions Using Statistical Analysis and Machine Learning

    Master-uppsats, KTH/Matematisk statistik

    Författare :Hannes Andersson; John Sjöberg; [2023]
    Nyckelord :Supply chain disruption; SMOTE; feature engineering; machine learning; random forest; statistics; applied mathematics; Störning i försörjningskedja; maskininlärning; matematik; statistik;

    Sammanfattning : The dairy business is vulnerable to supply chain disruptions since large safety stocks to cover up losses are not always a viable option, therefore it is crucial to maintain a smooth supply chain to ensure stable delivery accuracies. Disruptions are unpredictable and hard to avoid in the supply chain, especially in cases where production errors cause lost production volume. LÄS MER

  5. 4. Can Machine Be a Good Stock Picker?: Bridging the Gap between Fundamental Data and Machine Learning

    D-uppsats, Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

    Författare :Tomoya Narita; Povilas Stankevicius; [2023]
    Nyckelord :Machine Learning; XGBoost; Relative Valuation; Convergence Trade;

    Sammanfattning : We investigate the efficacy of historical accounting data and consensus forecasts for relative valuation of stocks, employing tree-based machine learning methods. We run an XGBoost model for monthly cross-sections of financial and pricing data of US equities from 1984 to 2021. LÄS MER

  7. 5. 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