Avancerad sökning
Hittade 2 uppsatser som matchar ovanstående sökkriterier.
1. Credit risk modelling and prediction: Logistic regression versus machine learning boosting algorithms
Kandidat-uppsats, Uppsala universitet/Statistiska institutionenSammanfattning : The use of machine learning methods in credit risk modelling has been proven to yield good results in terms of increasing the accuracy of the risk score as- signed to customers. In this thesis, the aim is to examine the performance of the machine learning boosting algorithms XGBoost and CatBoost, with logis- tic regression as a benchmark model, in terms of assessing credit risk. LÄS MER
2. Macroeconomic variables and their impact on the Swedish stock market
Kandidat-uppsats, Södertörns högskola/Institutionen för samhällsvetenskaperSammanfattning : The objective of this study is to investigate the impact of a few selected macroeconomic variables on the Swedish stock market index OMXS30. The study uses time series monthly data during the period 2000-2019. To investigate these relationships, the time series are transformed into stationary processes. LÄS MER