Sökning: "loss models"
Visar resultat 1 - 5 av 658 uppsatser innehållade orden loss models.
1. Tau-Leaping Implementations outside of chemistry
Kandidat-uppsats, Lunds universitet/Statistiska institutionenSammanfattning : Tau-leaping is an algorithm for model simulations most often used in kinetic chemistry. It was created to make simulations more efficient at the cost of some accuracy. However, its uses outside of chemistry are limited but could help make some model simulations more efficient. LÄS MER
2. Predicting Counter-Strike Matches using Machine Learning Models
Kandidat-uppsats, Lunds universitet/Statistiska institutionenSammanfattning : Sports betting is a widespread industry where predictive modeling play a big role. The goal of this thesis is to explore the possibilities of machine learning within the realm of e-sport prediction. The data used for this thesis is publicly available data was recorded over a three year period. LÄS MER
3. Regularization Methods and High Dimensional Data: A Comparative Study Based on Frequentist and Bayesian Methods
Kandidat-uppsats, Lunds universitet/Statistiska institutionenSammanfattning : As the amount of high dimensional data becomes increasingly accessible and common, the need for reliable methods to combat problems such as overfitting and multicollinearity increases. Models need to be able to manage large data sets where predictor variables often outnumber the amount of observations. LÄS MER
4. Volatility Forecasting - A comparative study of different forecasting models.
Kandidat-uppsats,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
5. Forecasting Volatility of Ether- An empirical evaluation of volatility models and their capacity to forecast one-day-ahead volatility of Ether
Master-uppsats, Göteborgs universitet/Graduate SchoolSammanfattning : This study evaluates the performance of volatility models in forecasting one-day-ahead volatility of the cryptocurrency Ether. The selected models are: GARCH, EGARCH, GJR-GARCH, SMA9, SMA20, and EWMA. We investigate both in-sample performance and out-of-sample performance. LÄS MER
