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Hittade 2 uppsatser som matchar ovanstående sökkriterier.

1. 1. Utilizing Hybrid Ensemble Prediction Model In Order to Predict Energy Demand in Sweden : A Machine-Learning Approach

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

   Författare :Binxin Su; [2022]
   Nyckelord :Energy Demand Prediction; Machine Learning; Hybrid Model; Ensemble Model; Random Forest; XGBoost; CatBoost; Prognos av Energiefterfrågan; Maskininlärning; Hybridmodell; Ensemblemodell; Random Forest; XGBoost; CatBoost;

   Sammanfattning : Conventional machine learning (ML) models and algorithms are constantly advancing at a fast pace. Most of this development are due to the implementation of hybrid- and ensemble techniques that are powerful tools to complement and empower the efficiency of the algorithms. LÄS MER

3. 2. Is ROCE a factor that affects the stock return?

   C-uppsats, Handelshögskolan i Stockholm/Institutionen för marknadsföring och strategi

   Författare :Maria Markusjan; Binxin Su; [2018]
   Nyckelord :Profitability Factor; ROCE; Fama-French; Factor model;

   Sammanfattning : This study investigates the profitability factor proposed by Novy-Marx through the application of the methodology developed by Fama-French (1993, 2015). It particularly focuses on investigating Return on Capital Employed (ROCE) as a measurement for profitability and how this influences the stock market behaviour adjusted for market risk and size. LÄS MER