The Non-linear Adjustment of Taiwan Stock Index Returns and Macroeconomic Variables: Using Smooth Transition Autoregressive STAR-ANSTGARCH Model

碩士 === 國立臺北大學 === 企業管理學系 === 100 === This paper attempts to investigate how the TAIEX stock returns were adjusted through time path with and without macroeconomic variables using monthly sample data from June 1996 to June 2011. By employing smooth transition autoregressive model(STAR) and ANSTGARCH...

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Main Authors:	LEE, SONG-SIOU, 李松修
Other Authors:	GOO, YEONG-JIA
Format:	Others
Language:	zh-TW
Published:	2012
Online Access:	http://ndltd.ncl.edu.tw/handle/54661775463446713392

id	ndltd-TW-100NTPU0121078
record_format	oai_dc
spelling	ndltd-TW-100NTPU01210782015-10-13T21:01:52Z http://ndltd.ncl.edu.tw/handle/54661775463446713392 The Non-linear Adjustment of Taiwan Stock Index Returns and Macroeconomic Variables: Using Smooth Transition Autoregressive STAR-ANSTGARCH Model 台灣股價指數報酬率與總體經濟變數非線性調整過程之探討─應用平滑轉換自我迴歸模式 LEE, SONG-SIOU 李松修碩士國立臺北大學企業管理學系 100 This paper attempts to investigate how the TAIEX stock returns were adjusted through time path with and without macroeconomic variables using monthly sample data from June 1996 to June 2011. By employing smooth transition autoregressive model(STAR) and ANSTGARCH model to depict asymmetric and nonlinear behaviors of the TAIEX returns, the findings are listed below. 1. TAIEX returns adjust in non-linear path. 2. The LSTAR model is better than the ESTAR model in measuring TAIEX returns adjustment process. 3. The STAR-ANSTGARCH model could properly estimate the asymmetric and nonlinear behavior of conditional mean and variance of TAIEX returns. 4. The Taiwan Coincident indicator could effectively explain the conditional mean and conditional variance of TAIEX returns. GOO, YEONG-JIA 古永嘉 2012 學位論文 ; thesis 56 zh-TW
collection	NDLTD
language	zh-TW
format	Others
sources	NDLTD
description	碩士 === 國立臺北大學 === 企業管理學系 === 100 === This paper attempts to investigate how the TAIEX stock returns were adjusted through time path with and without macroeconomic variables using monthly sample data from June 1996 to June 2011. By employing smooth transition autoregressive model(STAR) and ANSTGARCH model to depict asymmetric and nonlinear behaviors of the TAIEX returns, the findings are listed below. 1. TAIEX returns adjust in non-linear path. 2. The LSTAR model is better than the ESTAR model in measuring TAIEX returns adjustment process. 3. The STAR-ANSTGARCH model could properly estimate the asymmetric and nonlinear behavior of conditional mean and variance of TAIEX returns. 4. The Taiwan Coincident indicator could effectively explain the conditional mean and conditional variance of TAIEX returns.
author2	GOO, YEONG-JIA
author_facet	GOO, YEONG-JIA LEE, SONG-SIOU 李松修
author	LEE, SONG-SIOU 李松修
spellingShingle	LEE, SONG-SIOU 李松修 The Non-linear Adjustment of Taiwan Stock Index Returns and Macroeconomic Variables: Using Smooth Transition Autoregressive STAR-ANSTGARCH Model
author_sort	LEE, SONG-SIOU
title	The Non-linear Adjustment of Taiwan Stock Index Returns and Macroeconomic Variables: Using Smooth Transition Autoregressive STAR-ANSTGARCH Model
title_short	The Non-linear Adjustment of Taiwan Stock Index Returns and Macroeconomic Variables: Using Smooth Transition Autoregressive STAR-ANSTGARCH Model
title_full	The Non-linear Adjustment of Taiwan Stock Index Returns and Macroeconomic Variables: Using Smooth Transition Autoregressive STAR-ANSTGARCH Model
title_fullStr	The Non-linear Adjustment of Taiwan Stock Index Returns and Macroeconomic Variables: Using Smooth Transition Autoregressive STAR-ANSTGARCH Model
title_full_unstemmed	The Non-linear Adjustment of Taiwan Stock Index Returns and Macroeconomic Variables: Using Smooth Transition Autoregressive STAR-ANSTGARCH Model
title_sort	non-linear adjustment of taiwan stock index returns and macroeconomic variables: using smooth transition autoregressive star-anstgarch model
publishDate	2012
url	http://ndltd.ncl.edu.tw/handle/54661775463446713392
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The Non-linear Adjustment of Taiwan Stock Index Returns and Macroeconomic Variables: Using Smooth Transition Autoregressive STAR-ANSTGARCH Model

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