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Visar resultat 1 - 5 av 7 uppsatser som matchar ovanstående sökkriterier.

1. 1. Backtesting of simulated method for Counterparty Credit Risk

   Uppsats för yrkesexamina på avancerad nivå, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Love Lundström; Oscar Öhman; [2020]
   Nyckelord :Counterparty Credit Risk; Risk Factor; Monte Carlo Simulation; Quantitative Backtesting; Statistical Backtesting; OTC Derivative;

   Sammanfattning : After the financial crisis of 2008 regulators found that the derivative market, where financial institutions traded OTC derivatives with each other, played a significantrole in triggering the crisis. This led to the emergence of Counterparty Credit Risk(CCR) which is used to measure the exposure banks have to their counterparties. LÄS MER

3. 2. Machine Learning in credit risk : Evaluation of supervised machine learning models predicting credit risk in the financial sector

   Kandidat-uppsats, Umeå universitet/Institutionen för matematik och matematisk statistik

   Författare :Love Lundström; Oscar Öhman; [2019]
   Nyckelord :Credit risk; probability of default; Logistic regression; Neural network; Decision tree; Random Forest; Kredit risk; sannolikheten att fallera; Logistisk regression; Neurala nätverk; Decision Tree; Random Forest;

   Sammanfattning : When banks lend money to another party they face a risk that the borrower will not fulfill its obligation towards the bank. This risk is called credit risk and it’s the largest risk banks faces. According to the Basel accord banks need to have a certain amount of capital requirements to protect themselves towards future financial crisis. LÄS MER

4. 3. Rating corrumption within insurance companies using Bayesian network classifiers

   Magister-uppsats, Umeå universitet/Statistik

   Författare :Oscar Öhman; [2019]
   Nyckelord :;

   Sammanfattning : Bayesian Network (BN) classifiers are a type of probabilistic models. The learning process consists of two steps, structure learning and parameter learning. Four BN classifiers will be learned. These are two different Naive Bayes classifiers (NB), one Tree Augmented Naive Bayes classifier (TAN) and one Forest Naive Bayes classifier (FAN). LÄS MER

5. 4. Effekter av svält, krig och epidemi : En studie i överlevnadsanalys

   Kandidat-uppsats, Umeå universitet/Statistik

   Författare :Oscar Öhman; Alexander Boman; [2018]
   Nyckelord :;

   Sammanfattning : Finska kriget mellan 1808 och 1809, nödåren under den senare delen av 1860-talet, samt spanska sjukan mellan 1918 och 1919 var händelser som fick katastrofala konsekvenser för befolkningen i Umeå- samt Skellefteåtrakterna. Denna studie har som syfte att undersöka vilken av dessa händelser som hade störst effekt på dödligheten bland invånarna i dessa områden. LÄS MER

7. 5. Macroeconomic factors that correlate with the performance of IndustrialTransportation Companies : A study using multiple linear regression

   Kandidat-uppsats, KTH/Matematisk statistik

   Författare :Oscar Wijkström; Sofia Öhman; [2017]
   Nyckelord :;

   Sammanfattning : This thesis in Applied Mathematics and Industrial Economics examines which macroeconomic factors, related to the business cycle, that correlate with the performance of Industrial Transportation Companies. The data for the thesis is collected with the help of Nordea and from reports of each variable. LÄS MER