ITM Web Conf.
Volume 36, 2021The 16th IMT-GT International Conference on Mathematics, Statistics and their Applications (ICMSA 2020)
|Number of page(s)||8|
|Section||Statistics and Data Science|
|Published online||26 January 2021|
The asymmetric responses of stock prices in US market
Faculty of Science, Universiti Tunku Abdul Rahman, 31900 Kampar, Perak, Malaysia
* Corresponding author: firstname.lastname@example.org
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.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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