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Essays on empirical time series mode...

Kim, Jin Woong.

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Essays on empirical time series modeling with causality and structural change.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Essays on empirical time series modeling with causality and structural change./
作者:	Kim, Jin Woong.
面頁冊數:	126 p.
附註:	Source: Dissertation Abstracts International, Volume: 67-08, Section: A, page: 3096.
Contained By:	Dissertation Abstracts International67-08A.
標題:	Economics, Agricultural. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3231641
ISBN:	9780542840975

Essays on empirical time series modeling with causality and structural change.
Kim, Jin Woong.

Essays on empirical time series modeling with causality and structural change. - 126 p.

Source: Dissertation Abstracts International, Volume: 67-08, Section: A, page: 3096.

Thesis (Ph.D.)--Texas A&M University, 2006.

In this dissertation, three related issues of building empirical time series models for financial markets are investigated with respect to contemporaneous causality, dynamics, and structural change. In the first essay, nation-wide industry information transmission among stock returns of ten sectors in the U.S. economy is examined through the Directed Acyclical Graph (DAG) for contemporaneous causality and Bernanke decomposition for dynamics. The evidence shows that the information technology sector is the most root cause sector. Test results show that DAG from ex ante forecast innovations is consistent with the DAG from ex post fit innovations. This supports innovation accounting based on DAGs using ex post innovations.

ISBN: 9780542840975Subjects--Topical Terms:

626648
Economics, Agricultural.

Essays on empirical time series modeling with causality and structural change.
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245 1 0 $a Essays on empirical time series modeling with causality and structural change.
300 $a 126 p.
500 $a Source: Dissertation Abstracts International, Volume: 67-08, Section: A, page: 3096.
500 $a Advisers: David J. Leatham; David A. Bessler.
502 $a Thesis (Ph.D.)--Texas A&M University, 2006.
520 $a In this dissertation, three related issues of building empirical time series models for financial markets are investigated with respect to contemporaneous causality, dynamics, and structural change. In the first essay, nation-wide industry information transmission among stock returns of ten sectors in the U.S. economy is examined through the Directed Acyclical Graph (DAG) for contemporaneous causality and Bernanke decomposition for dynamics. The evidence shows that the information technology sector is the most root cause sector. Test results show that DAG from ex ante forecast innovations is consistent with the DAG from ex post fit innovations. This supports innovation accounting based on DAGs using ex post innovations.
520 $a In the second essay, the contemporaneous/dynamic behaviors of real estate and stock returns are investigated. Selected macroeconomic variables are included in the model to explain recent movements of both returns. During 1971-2004, there was a single structural break in October 1980. A distinct difference in contemporaneous causal structure before and after the break is found. DAG results show that REITs take the role of a causal parent after the break. Innovation accounting shows significantly positive responses of real estate returns due to an initial shock in default risk but insignificant responses of stock returns. Also, a shock in short run interest rates affects real estate returns negatively with significance but does not affect stock returns.
520 $a In the third essay, a structural change in the volatility of five Asian and U.S. stock markets is examined during the post-liberalization period (1990-2005) in the Asian financial markets, using the Sup LM test. Four Asian financial markets (Hong Kong, Japan, Korea, and Singapore) experienced structural changes. However, test results do not support the existence of structural change in volatility for Thailand and U.S. Also, results show that the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) persistent coefficient increases, but the Autoregressive Conditional heteroskedasticity (ARCH) impact coefficient, implying short run adjustment, decreases in Asian markets.
520 $a In conclusion, when the econometric model is set up, it is necessary to consider contemporaneous causality and possible structural breaks (changes). The dissertation emphasizes causal inference and structural consistency in econometric modeling. It highlights their importance in discovering contemporaneous/dynamic causal relationships among variables. These characteristics will likely be helpful in generating accurate forecasts.
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650 4 $a Economics, Agricultural. $3 626648
650 4 $a Economics, Finance. $3 626650
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710 2 0 $a Texas A&M University. $3 718977
773 0 $t Dissertation Abstracts International $g 67-08A.
790 1 0 $a Leatham, David J., $e advisor
790 1 0 $a Bessler, David A., $e advisor
790 $a 0803
791 $a Ph.D.
792 $a 2006
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3231641