Sökning: "examensarbete matematisk statistik"

Visar resultat 1 - 5 av 125 uppsatser innehållade orden examensarbete matematisk statistik.

1. 1. Optimizing within the Supply Chain: A Mathematical Model for Inventory Optimization with respect to Demand Planning

   Kandidat-uppsats, KTH/Matematisk statistik

   Författare :William Bork; Martynas Giedraitis; [2023]
   Nyckelord :Inventory model; ”Fast Moving Consumer Goods-company” FMCG-company ; Reorder point; Order quantity; ”Software as a Service-Company”; EOQ-model; R; Q -model; Forecast; Holt-Winters model; Inventory model; ”Fast Moving Consumer Goods-company” FMCG-company ; Reorder point; Order quantity; ”Software as a Service-Company”; EOQ-model; R; Q -model; Forecast; Holt-Winters model;

   Sammanfattning : This thesis examines how to design a mathematical inventory model for a ”Fast Moving Consumer Goods”-company (FMCG-company), which determines the optimal reorder point and order quantity such that the average inventory cost is minimized. The thesis was made in collaboration with a ”Software as a Service”- company which provided the data containing information about the products and inventory management of one of their customers, a FMCG-company. LÄS MER

3. 2. Utilizing logistic regression to apply the ELO system in forecasting Premier League odds

   Kandidat-uppsats, KTH/Matematisk statistik

   Författare :Claudio Thegelström; [2023]
   Nyckelord :Premier League; ELO system; Historical odds; Logistic regression; Unbiased prediction; Premier League; ELO systemet; Historiska odds; Logistisk regression; Opartiska prediktioner;

   Sammanfattning : This thesis provides insights into the creation of a model for predicting odds in the Premier League. It illustrates how the ELO system and historical odds, in combination with Monte Carlo simulations, can be implemented through logistic regression to predict odds in an unbiased way. LÄS MER

4. 3. Data Driven Modeling for Aerodynamic Coefficients

   Master-uppsats, KTH/Matematisk statistik

   Författare :Erik Jonsäll; Emma Mattsson; [2023]
   Nyckelord :Master s thesis; System identification; Parameter estimation; Ordinary least squares; Machine learning; Aerodynamic coefficients; F18--HARV; Flight simulations.; Masteruppsats; Systemidentifiering; Parameteruppskattning; Minstakvadratmetoden; Maskininlärning; Aerodynamiska koefficienter; F18-HARV; Flygsimuleringar.;

   Sammanfattning : Accurately modeling aerodynamic forces and moments are crucial for understanding thebehavior of an aircraft when performing various maneuvers at different flight conditions.However, this task is challenging due to complex nonlinear dependencies on manydifferent parameters. LÄS MER

5. 4. Portfolio Risk Modelling in Venture Debt

   Master-uppsats, KTH/Matematisk statistik

   Författare :John Eriksson; Jacob Holmberg; [2023]
   Nyckelord :Startup Default Probability; Venture Debt; Gaussian Copula; Value-at-Risk; Expected Shortfall; Exposure at Default; Loss Given Default; Forecast; Linear Dynamic System; ARIMA Time Series; Monte Carlo Simulation; Linear Regression; Central Limit Theorem;

   Sammanfattning : This thesis project is an experimental study on how to approach quantitative portfolio credit risk modelling in Venture Debt portfolios. Facing a lack of applicable default data from ArK and publicly available sets, as well as seeking to capture companies that fail to service debt obligations before defaulting per se, we present an approach to risk modeling based on trends in revenue. LÄS MER

7. 5. Credit Exposure Modelling Using Differential Machine Learning

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Måns Karp; Samuel Wagner; [2023]
   Nyckelord :Counterparty credit risk; Differential machine learning; Exposure modelling; Heston model; Option pricing; Mathematics and Statistics;

   Sammanfattning : Exposure modelling is a critical aspect of managing counterparty credit risk, and banks worldwide invest significant time and computational resources in this task. One approach to modelling exposure involves pricing trades with a counterparty in numerous potential future market scenarios. LÄS MER