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.
| Identifer | oai:union.ndltd.org:tamu.edu/oai:repository.tamu.edu:1969.1/ETD-TAMU-3093 |
| Date | 15 May 2009 |
| Creators | Zohrabyan, Tatevik |
| Contributors | Bessler, David A., Leatham, David J. |
| Source Sets | Texas A and M University |
| Language | en_US |
| Detected Language | English |
| Type | Book, Thesis, Electronic Dissertation, text |
| Format | electronic, application/pdf, born digital |
Page generated in 0.0018 seconds