Abstract
| Original language | English |
|---|---|
| Title of host publication | Econometrics for financial applications |
| Publisher | Springer-Verlag GmbH and Co. KG |
| Pages | 562-583 |
| Number of pages | 22 |
| ISBN (Print) | 9783319731490 |
| DOIs | |
| Publication status | Published - 1 Jan 2018 |
Publication series
| Name | Studies in Computational Intelligence |
|---|---|
| Volume | 760 |
| ISSN (Print) | 1860-949X |
Fingerprint
Cite this
}
Constructing a financial stress index for Vietnam : an application of autoregressive conditional heteroskedastic models. / DUC, Nguyen Chi; HO, Thuy Ai.
Econometrics for financial applications. Springer-Verlag GmbH and Co. KG, 2018. p. 562-583 (Studies in Computational Intelligence; Vol. 760).Research output: Book Chapters | Papers in Conference Proceedings › Book Chapter › Research › peer-review
TY - CHAP
T1 - Constructing a financial stress index for Vietnam : an application of autoregressive conditional heteroskedastic models
AU - DUC, Nguyen Chi
AU - HO, Thuy Ai
PY - 2018/1/1
Y1 - 2018/1/1
N2 - This paper constructs an index to measure financial stress for Vietnam with monthly data from April 2007 to December 2016. Various measures of stress are selected based on literature and Vietnam’s practice. An important stress measure, the volatility of stock market, bond market, money market and banking sector, is estimated by variants of the general autoregressive conditional heteroskedasticity (GARCH) model. Individual stress variables are combined together to make an aggregate index using equal variance weighting scheme. The constructed index is a useful tool for policy makers to monitor the riskiness of domestic financial system as well as academics to conduct further research about financial crisis.
AB - This paper constructs an index to measure financial stress for Vietnam with monthly data from April 2007 to December 2016. Various measures of stress are selected based on literature and Vietnam’s practice. An important stress measure, the volatility of stock market, bond market, money market and banking sector, is estimated by variants of the general autoregressive conditional heteroskedasticity (GARCH) model. Individual stress variables are combined together to make an aggregate index using equal variance weighting scheme. The constructed index is a useful tool for policy makers to monitor the riskiness of domestic financial system as well as academics to conduct further research about financial crisis.
UR - http://commons.ln.edu.hk/sw_master/6671
UR - http://www.scopus.com/inward/record.url?scp=85038855145&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-73150-6_45
DO - 10.1007/978-3-319-73150-6_45
M3 - Book Chapter
SN - 9783319731490
T3 - Studies in Computational Intelligence
SP - 562
EP - 583
BT - Econometrics for financial applications
PB - Springer-Verlag GmbH and Co. KG
ER -