Avancerad sökning

Visar resultat 1 - 5 av 49 uppsatser som matchar ovanstående sökkriterier.

1. 1. Volatility Forecasting - A comparative study of different forecasting models.

   Kandidat-uppsats,

   Författare :Emil Sturesson; Anton Wennström; [2023-06-29]
   Nyckelord :Volatility; GARCH; EGARCH; t-GAS; HAR-RV; Realized GARCH; Volatility Forecasting; Volatility Modelling;

   Sammanfattning : This study evaluates the out-of-sample forecasting performance of different volatility mod- els. When applied to XACT OMXS30, we use GARCH(1,1), EGARCH(1,1), and t- GAS(1,1) to forecast squared daily returns while Realized GARCH(1,1) and HAR-RV are used to forecast Realized Variance. LÄS MER

3. 2. Forecasting the Temperatures of theWinter 2022/2023 using SARIMA Models

   Kandidat-uppsats, Uppsala universitet/Statistiska institutionen

   Författare :Georg Holmén; Felix Bemark; [2023]
   Nyckelord :;

   Sammanfattning : In this paper the possibility and accuracy of forecasting weekly temperatures for one season,the winter of 2022/2023 is explored. By comparing the forecasted values with normal temper-atures a prediction of the severity of the coming winter can be attained. LÄS MER

4. 3. Exploring Housing Market Dynamics through Google Search : A Case of Taiwan

   Master-uppsats, KTH/Fastigheter och byggande

   Författare :Yi-Chi Yeh; [2022]
   Nyckelord :Housing; Real Estate; Google Trends; Taiwan; Bostad; fastigheter; Google Trender; Taiwan;

   Sammanfattning : To capture house price fluctuations, it is important to combine appropriate factors into the price forecasting model. Fundamental macroeconomic variables have been considered quite completely in many housing price models. However, the ability of these models to predict housing prices are still limited. LÄS MER

5. 4. Volatility Forecasting of an Optimal Portfolio

   Master-uppsats, Mälardalens universitet/Akademin för utbildning, kultur och kommunikation

   Författare :Asima Saleemi; [2022]
   Nyckelord :Optimal Portfolio; Volatility modelling and Forecasting; Minimum Variance; ARCH model; GARCH Model; GJR-GARCH Model;

   Sammanfattning : This thesis aims to construct an optimal portfolio and model as well as forecast its volatility. The performance of the optimal portfolio is then compared to two benchmarks, namely, an equally weighted portfolio and the market index SP 500. The volatility is estimated by employing two GARCH-type models known as standard GARCH, and GJR-GARCH. LÄS MER

7. 5. 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