Author : Shahryar Haghighifard 1
Date of Publication :1st April 2018
Abstract: The stochastic nature of the stock market has made it difficult to forecast its performance. Therefore, vigilance is crucial in making the best decisions. Presidential elections have been observed to be a factor that causes uncertainty in stock market's performance. In this article, the researchers aimed to determine Artificial Neural Network's (ANN) capability to forecast stock market index with and without an influence of presidential election uncertainty. Historical data of Philippines stock exchange market for past eight years was obtained and divided into five different datasets based on different time frames leading to the presidential election. The researchers grouped the data into complete data, data without one month before the presidential election, data without six months before the presidential election, data containing only one month before presidential polls and data comprising just six months before presidential elections. A test dataset also collected to measure the performance of each network trained by above datasets. Then a NARX neural network was trained using each dataset. After examining all datasets, the datasets in which the data of six months and one month before elections were eliminated, showed better learning rate comparing to other datasets. This study shows a new way to consider presidential polls as one of the factors to predict the stock market. Although it is not possible to forecast the market by examining a sole consideration, the findings of this research can help market analysts to make better decisions.
Reference :
-
- Dennis Bams, Gildas Blanchard, Iman Honarvar, Thorsten Lehnert, Does oil and gold price uncertainty matter for the stock market?, In Journal of Empirical Finance, 2017, , ISSN 0927-5398, https://doi.org/10.1016/j.jempfin.2017.07.003.
- Xinwei Zheng, Dan Su, “Impacts of oil price shocks on Chinese stock market liquidity”, In International Review of Economics & Finance, Volume 50, 2017, Pages 136-174, ISSN 1059-0560
- G. Naresh, Gopala Vasudevan, S. Mahalakshmi, S. Thiyagarajan, „Spillover effect of US dollar on the stock indices of BRICS‟, In Research in International Business and Finance, 2017, , ISSN 0275-5319
- Amin Hedayati Moghaddam, Moein Hedayati Moghaddam, Morteza Esfandyari, “Stock market index prediction using artificial neural network”, In Journal of Economics, Finance and Administrative Science, Volume 21, Issue 41, 2016, Pages 89-93, ISSN 2077-1886
- Michael Negnevitsky, “Identification of failing banks using Clustering with self-organising neural networks”, In Procedia Computer Science, Volume 108, 2017, Pages 1327-1333, ISSN 1877-0509
- Cuixia Jiang, Ming Jiang, Qifa Xu, Xue Huang, “Expectile regression neural network model with applications”, In Neurocomputing, Volume 247, 2017, Pages 73-86, ISSN 0925-2312
- Lean Yu, Shouyang Wang, Kin Keung Lai, “Credit risk assessment with a multistage neural network ensemble learning approach”, In Expert Systems with Applications, Volume 34, Issue 2, 2008, Pages 1434- 1444, ISSN 0957-4174, https://doi.org/10.1016/j.eswa.2007.01.009.
- Esteban Alfaro, Noelia García, Matías Gámez, David Elizondo, “Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks”, In Decision Support Systems, Volume 45, Issue 1, 2008, Pages 110-122, ISSN 0167-9236, https://doi.org/10.1016/j.dss.2007.12.002.
- JÄ™drzej BiaÅ‚kowski, Katrin Gottschalk, Tomasz Piotr Wisniewski,” Stock market volatility around national elections”, In Journal of Banking & Finance, Volume 32, Issue 9, 2008, Pages 1941-1953, ISSN 0378-4266,http://https://doi.org/10.1016/j.jbankfin.2007.12.021.
- Christine Fauvelle-Aymar, Mary Stegmaier, “The stock market and U.S. presidential approval”, In Electoral Studies, Volume 32, Issue 3, 2013, Pages 411-417, ISSN 0261-3794, https://doi.org/10.1016/j.electstud.2013.05.024.
- John W. Goodell, Frank McGroarty, Andrew Urquhart, “Political uncertainty and the 2012 US presidential election: A cointegration study of prediction markets, polls and a stand-out expert”, In International Review of Financial Analysis, Volume 42, 2015, Pages