Browsing by Author "Jrideh, Khaled"

Filter results by typing the first few letters
Now showing 1 - 2 of 2
  • No Thumbnail Available
    Item
    Faktorer som påverkar bostadspriserna i Sveriges storstadsregioner - En empirisk undersökning om vilka effekter fundamentala faktorer har på bostadspriser med fokus på arbetslöshet
    (2022-02-15) Jansson, Jasmine; Jrideh, Khaled; University of Gothenburg/Department of Economics; Göteborgs universitet/Institutionen för nationalekonomi med statistik
    Syftet med denna uppsats är att undersöka effekten av makroekonomiska och sociodemografiska faktorer på bostadspriserna i Sveriges storstadsregioner mellan 2010–2019. De faktorer som undersökts är: arbetslöshet, inkomst, bolåneränta, befolkningstäthet och nyproduktion av bostäder. Denna uppsats undersöker även om effekten för arbetslöshet på bostadspriser är lika för olika inkomstnivåer i storstadsregionerna. Studien innehåller årlig data för 45 kommuner från 2010 till 2019. Resultatet av fixed effekt paneldata modellen visar att bostadspriserna i kommuner med hög inkomst är mer känsliga för arbetslöshet än kommuner med låg inkomst. Hushåll med högre inkomster tenderar att ta högre lån för att ha råd med dyrare bostäder. Storstadsregionerna tenderar att ha en större skuldkvot, vilket gör att en ökad arbetslöshet i dessa regioner leder till en högre skuldkvot på grund av inkomstbortfall. Effekten av kvarvarande faktorer på bostadspriser ligger i linje med de förväntade effekterna, förutom effekten av nyproducerade bostäder, vilket var signifikant endast när inkomsten inte var inkluderad i regressionen. The purpose of this paper is to examine the effects of macroeconomic and sociodemographic factors on housing prices in Sweden’s metropolitan regions between 2010 and 2019. The examined factors are: mortgage rate, population density, income, unemployment and new housing construction. This paper also investigates whether the effect of unemployment on housing prices is equal for different income levels. The study accommodate annual data for 45 municipalities from 2010 to 2019. The results of fixed effects panel data regression models show that housing prices for municipalities with higher income are more sensitive for unemployment than municipalities with lower income. Households with higher income tend to take higher loans to afford more expensive housing. Metropolitan regions tend to have a larger debt-to-income ratio, which means that an increased unemployment rate in these leads to a greater debt-to-income ratio due to loss of income. The effects of all the remaining factors on housing prices is in line with the expected effects, except for the effect of new production of housing, which was only significant when income was not included in the regression.
  • No Thumbnail Available
    Item
    Value at Risk Estimation using GARCH Family Models: A Comparison of Different Specifications and Distributions.
    (2023-05-26) Jrideh, Khaled; University of Gothenburg/Department of Economics; Göteborgs universitet/Institutionen för nationalekonomi med statistik
    The objective of this study is to compare the performance of different GARCH models, under various conditional distribution assumptions, to predict one-day-ahead Value-at-Risk (VaR) for three stocks: Swedbank, Handelsbanken, and SEB over the Covid-19 period. The performance is evaluated using Kupiec, Christoffersen tests and the Quadratic Loss. The results show that the assumed distribution, model specification, and confidence level together play an important role in VaR estimation, as these factors can substantially affect the accuracy of the estimate. Models that assume the skew t-distribution and the t-distribution generally perform well, while the performance of models that assume the normal distribution changes dramatically as a function of the confidence level. Regarding the models, the study shows that the EGARCH specification resulted in the lowest losses and that the worst performing model is ARCH, especially when the assumed distribution is normal.