KMS Of Academy of mathematics and systems sciences, CAS
| Uncertainty shocks of Trump election in an interval model of stock market | |
| Sun, Yuying1,2; Qiao, Kenan1,2,3; Wang, Shouyang1,2,4 | |
| 2020-08-29 | |
| Source Publication | QUANTITATIVE FINANCE
 |
| ISSN | 1469-7688 |
| Pages | 15 |
| Abstract | This paper proposes a new class of nonlinear interval models for interval-valued time series. By matching the interval model with interval observations, we develop a nonlinear minimum-distance estimation method for the proposed models, and establish the asymptotic theory for the proposed estimators. Superior to traditional point-based methods, the proposed interval modelling approach can assess the change in both the trend and volatility simultaneously. Within the proposed interval framework, this paper examines the impact of the 2016 US presidential election (henceforth Trump election) on the US stock market as a case study. Considering the validity of daily high-low range as a proxy of market efficiency, we employ an interval-valued return to jointly measure the fundamental value movement and market efficiency simultaneously. Empirical results suggest a strong evidence that the Trump election has increased the level/trend and lowered the volatility of the S&P 500 index in both ex ante and ex post analysis. Furthermore, a longer half-life period for the impact on fundamental value (62.4 days) than high-low range (15.9 days) has shown that the impact of Trump's victory on fundamental value is more persistent than its impact on market efficiency. |
| Keyword | Interval dummy variables Interval time series Nonlinear minimum-distance estimator Range volatility Trump election |
| DOI | 10.1080/14697688.2020.1800070 |
| Indexed By | SCI |
| Language | 英语 |
| Funding Project | National Natural Science Foundation of China[71703156] ; National Natural Science Foundation of China[71701199] ; National Natural Science Foundation of China[71871213] ; National Natural Science Foundation of China[71988101] ; National Natural Science Foundation of China[71973116] ; National Natural Science Foundation of China[201601] ; Fujian Provincial Key Laboratory of Statistics (Xiamen University)[201601] |
| WOS Research Area | Business & Economics ; Mathematics ; Mathematical Methods In Social Sciences |
| WOS Subject | Business, Finance ; Economics ; Mathematics, Interdisciplinary Applications ; Social Sciences, Mathematical Methods |
| WOS ID | WOS:000566956600001 |
| Publisher | ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/52173 |
| Collection | 中国科学院数学与系统科学研究院 |
| Corresponding Author | Qiao, Kenan |
| Affiliation | 1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 2.Chinese Acad Sci, Ctr Forecasting Sci, Beijing, Peoples R China 3.Univ Groningen, Fac Econ & Business, Groningen, Netherlands 4.Univ Chinese Acad Sci, Sch Econ & Management, Beijing, Peoples R China |
| Recommended Citation GB/T 7714 | Sun, Yuying,Qiao, Kenan,Wang, Shouyang. Uncertainty shocks of Trump election in an interval model of stock market[J]. QUANTITATIVE FINANCE,2020:15. |
| APA | Sun, Yuying,Qiao, Kenan,&Wang, Shouyang.(2020).Uncertainty shocks of Trump election in an interval model of stock market.QUANTITATIVE FINANCE,15. |
| MLA | Sun, Yuying,et al."Uncertainty shocks of Trump election in an interval model of stock market".QUANTITATIVE FINANCE (2020):15. |
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment