Essays about: "Learning Stocks"

Showing result 1 - 5 of 34 essays containing the words Learning Stocks.

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

    University essay from Lunds universitet/Statistiska institutionen

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

    Abstract : 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. READ MORE

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

    University essay from KTH/Matematisk statistik

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

    Abstract : 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. READ MORE

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

    University essay from Handelshögskolan i Stockholm/Institutionen för finansiell ekonomi

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

    Abstract : 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. READ MORE

  5. 4. Evaluating the Effect of Meta-Labeling on Equity Market Neutral Strategy

    University essay from Lunds universitet/Statistiska institutionen

    Author : Niclas Wölner-Hanssen; [2023]
    Keywords : Meta-Labeling; Probabilistic Sharpe Ratio; Equity Market Neutral; Mathematics and Statistics;

    Abstract : This thesis aims to construct an Equity Market Neutral (EMN) strategy framework to predict intraday excess returns of stocks within the S&P 500 index by utilizing machine learning techniques proposed by (López de Prado, 2018). The constructed EMN strategies within the framework utilizes techniques such as Stacked Single Feature Importance (SSFI), sample weighting, Probabilistic Sharpe Ratio (PSR), and meta-labeling. READ MORE

  6. 5. Personalized Investment Recommendations Using Recommendation Systems

    University essay from Lunds universitet/Nationalekonomiska institutionen

    Author : Lorik Sadriu; [2023]
    Keywords : Recommendation systems; Deep learning; Institutional investors; Investment decision-making; Mean-variance spanning test; Cross-Selling; Business and Economics;

    Abstract : 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