The asymmetric responses of stock prices in US market
Machine learning and data analytics are so popular in making trading much more efficient by helping the investors to identify opportunities and reduce trading costs. Before applying suitable predictive modelling algorithms, it is crucial for investors or policymaker to understand the nature of the s...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2021-01-01
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| Series: | ITM Web of Conferences |
| Online Access: | https://www.itm-conferences.org/articles/itmconf/pdf/2021/01/itmconf_icmsa2021_01013.pdf |
| _version_ | 1818737424082141184 |
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| author | Beh Woan Lin Yew Wen Khang |
| author_facet | Beh Woan Lin Yew Wen Khang |
| author_sort | Beh Woan Lin |
| collection | DOAJ |
| description | Machine learning and data analytics are so popular in making trading much more efficient by helping the investors to identify opportunities and reduce trading costs. Before applying suitable predictive modelling algorithms, it is crucial for investors or policymaker to understand the nature of the stock data properly. This paper investigates the dependency of macroeconomic factors against the stock markets in the United States using the nonlinear Autoregressive Distributed Lag (NARDL) approach. The analysis considered the Dow Jones Industrial Average Index, NASDAQ Composite Index, and S&P 500 Index. Macroeconomic factors in this country such as consumer price index, export, interest rates, money supply, real effective exchange rates, total reserves, and gold price are considered in this study. In the findings, the NARDL approach shows that the Dow Jones Industrial Average Index and S&P500 Index are having bi-directional positive asymmetric effects to each other in the short run. In short-run, increasing the consumer price index is found to have a negative effect on Dow Jones Industrial Average Index but with a positive effect on S&P500 Index. In conclusion, this study aids investors and other market participants in making a more efficient investment decision. |
| first_indexed | 2024-12-18T00:52:49Z |
| format | Article |
| id | doaj.art-c8da964fbb70427abb2809c1e7c1d924 |
| institution | Directory Open Access Journal |
| issn | 2271-2097 |
| language | English |
| last_indexed | 2024-12-18T00:52:49Z |
| publishDate | 2021-01-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | ITM Web of Conferences |
| spelling | doaj.art-c8da964fbb70427abb2809c1e7c1d9242022-12-21T21:26:37ZengEDP SciencesITM Web of Conferences2271-20972021-01-01360101310.1051/itmconf/20213601013itmconf_icmsa2021_01013The asymmetric responses of stock prices in US marketBeh Woan Lin0Yew Wen Khang1Faculty of Science, Universiti Tunku Abdul RahmanFaculty of Science, Universiti Tunku Abdul RahmanMachine learning and data analytics are so popular in making trading much more efficient by helping the investors to identify opportunities and reduce trading costs. Before applying suitable predictive modelling algorithms, it is crucial for investors or policymaker to understand the nature of the stock data properly. This paper investigates the dependency of macroeconomic factors against the stock markets in the United States using the nonlinear Autoregressive Distributed Lag (NARDL) approach. The analysis considered the Dow Jones Industrial Average Index, NASDAQ Composite Index, and S&P 500 Index. Macroeconomic factors in this country such as consumer price index, export, interest rates, money supply, real effective exchange rates, total reserves, and gold price are considered in this study. In the findings, the NARDL approach shows that the Dow Jones Industrial Average Index and S&P500 Index are having bi-directional positive asymmetric effects to each other in the short run. In short-run, increasing the consumer price index is found to have a negative effect on Dow Jones Industrial Average Index but with a positive effect on S&P500 Index. In conclusion, this study aids investors and other market participants in making a more efficient investment decision.https://www.itm-conferences.org/articles/itmconf/pdf/2021/01/itmconf_icmsa2021_01013.pdf |
| spellingShingle | Beh Woan Lin Yew Wen Khang The asymmetric responses of stock prices in US market ITM Web of Conferences |
| title | The asymmetric responses of stock prices in US market |
| title_full | The asymmetric responses of stock prices in US market |
| title_fullStr | The asymmetric responses of stock prices in US market |
| title_full_unstemmed | The asymmetric responses of stock prices in US market |
| title_short | The asymmetric responses of stock prices in US market |
| title_sort | asymmetric responses of stock prices in us market |
| url | https://www.itm-conferences.org/articles/itmconf/pdf/2021/01/itmconf_icmsa2021_01013.pdf |
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