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Description:
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Financial market and its various components are currently in turmoil . Many large
corporations are devising new ways to overcome the current market instability .
Consequently , any study fostering the understanding of financial markets and the
dependencies of various market components would greatly benefit both the practitioners
and academicians . To understand different parts of the financial market , this dissertation
employs time series methods to model causality and structure and degree of dependence .
The relationship of housing market prices for nine U .S . census divisions is studied in the
first essay . The results show that housing market is very interrelated . The New England
and West North Central census divisions strongly lead house prices of the rest of the
country . Further evidence suggests that house prices of most census divisions are mainly
influenced by house price changes of other regions .
The interdependence of oil prices and stock market indices across countries is
examined in the second essay . The general dependence structure and degree is estimated
using copula functions . The findings show weak dependence between stock market
indices and oil prices for most countries except for the large oil producing nations which show high dependence . The dependence structure for most oil consuming (producing )
countries is asymmetric implying that stock market index and oil price returns tend to
move together more during the market downturn (upturn ) than a market boom
(downturn ) .
In the third essay , the relationship among stock returns of ten U .S . sectors is
studied . Copula models are used to explore the non -linear , general association among the
series . The evidence shows that sectors are strongly related to each other . Energy sector
is relatively weakly connected with the other sectors . The strongest dependence is
between the Industrials and Consumer Discretionary sectors . The high dependence
suggests small (if any ) gains from industry diversification in U .S .
In conclusion , the correct formulation of relationships among variables of interest
is crucial . This is one of the fundamental issues in portfolio analysis . Hence , a thorough
examination of time series models that are used to understand interactions of financial
markets can be helpful for devising more accurate investment strategies . |