{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,6]],"date-time":"2026-05-06T16:25:15Z","timestamp":1778084715135,"version":"3.51.4"},"reference-count":92,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T00:00:00Z","timestamp":1735603200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e a Tecnologia","doi-asserted-by":"publisher","award":["UIDB\/05064\/2020"],"award-info":[{"award-number":["UIDB\/05064\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Economies"],"abstract":"<jats:p>Forecasting stock markets is challenging due to the influence of various internal and external factors compounded by the effects of globalization. This study introduces a data-driven approach to forecast S&amp;P 500 returns by incorporating macroeconomic indicators including gold and oil prices, the volatility index, economic policy uncertainty, the financial stress index, geopolitical risk, and shadow short rate, with ten technical indicators. We propose three hybrid deep learning models that sequentially combine convolutional and recurrent neural networks for improved feature extraction and predictive accuracy. These models include the deep belief network with gated recurrent units, the LeNet architecture with gated recurrent units, and the LeNet architecture combined with highway networks. The results demonstrate that the proposed hybrid models achieve higher forecasting accuracy than the single deep learning models. This outcome is attributed to the complementary strengths of convolutional networks in feature extraction and recurrent networks in pattern recognition. Additionally, an analysis using the Shapley method identifies the volatility index, financial stress index, and economic policy uncertainty as the most significant predictors, underscoring the effectiveness of our data-driven approach. These findings highlight the substantial impact of contemporary uncertainty factors on stock markets, emphasizing their importance in studies analyzing market behaviour.<\/jats:p>","DOI":"10.3390\/economies13010006","type":"journal-article","created":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T14:21:12Z","timestamp":1735654872000},"page":"6","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Integrating Macroeconomic and Technical Indicators into Forecasting the Stock Market: A Data-Driven Approach"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8302-9869","authenticated-orcid":false,"given":"Saima","family":"Latif","sequence":"first","affiliation":[{"name":"Department of Management Sciences, COMSATS University, Park Road, Islamabad 45550, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7308-096X","authenticated-orcid":false,"given":"Faheem","family":"Aslam","sequence":"additional","affiliation":[{"name":"Department of Management Sciences, COMSATS University, Park Road, Islamabad 45550, Pakistan"},{"name":"School of Business Administration (SBA), Al Akhawayn University, Ifrane 53003, Morocco"},{"name":"VALORIZA\u2014Research Center for Endogenous Resource Valorization, 7300-555 Portalegre, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1951-889X","authenticated-orcid":false,"given":"Paulo","family":"Ferreira","sequence":"additional","affiliation":[{"name":"VALORIZA\u2014Research Center for Endogenous Resource Valorization, 7300-555 Portalegre, Portugal"},{"name":"Polytechnic Institute of Portalegre, 7300-110 Portalegre, Portugal"},{"name":"CEFAGE-UE, IIFA, University of \u00c9vora, Largo dos 2 Colegiais, 7000-809 \u00c9vora, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5255-6532","authenticated-orcid":false,"given":"Sohail","family":"Iqbal","sequence":"additional","affiliation":[{"name":"School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad 44000, Pakistan"}]}],"member":"1968","published-online":{"date-parts":[[2024,12,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"998","DOI":"10.47772\/IJRISS.2024.806076","article-title":"Economic policy uncertainty and financial markets in the united state","volume":"8","author":"Adeloye","year":"2024","journal-title":"International Journal of Research and Innovation in Social Science"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1007\/s10690-019-09300-5","article-title":"Us economic policy uncertainty and gcc stock market","volume":"27","author":"Alqahtani","year":"2020","journal-title":"Asia-Pacific Financial Markets"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1093\/rfs\/hhu059","article-title":"Investor attention and stock market volatility","volume":"28","author":"Andrei","year":"2015","journal-title":"The Review of Financial Studies"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.irfa.2017.01.004","article-title":"Oil shocks and stock markets: Dynamic connectedness under the prism of recent geopolitical and economic unrest","volume":"50","author":"Antonakakis","year":"2017","journal-title":"International Review of Financial Analysis"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.frl.2016.04.011","article-title":"Economic policy uncertainty and stock markets: Long-run evidence from the us","volume":"18","author":"Arouri","year":"2016","journal-title":"Finance Research Letters"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"e18114","DOI":"10.1016\/j.heliyon.2023.e18114","article-title":"Interplay of multifractal dynamics between shadow policy rates and stock markets","volume":"9","author":"Aslam","year":"2023","journal-title":"Heliyon"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"e00110","DOI":"10.1016\/j.jeca.2018.e00110","article-title":"Firm-level political risk and asymmetric volatility","volume":"18","author":"Aye","year":"2018","journal-title":"The Journal of Economic Asymmetries"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1016\/j.eswa.2018.07.019","article-title":"Modaugnet: A new forecasting framework for stock market index value with an overfitting prevention lstm module and a prediction lstm module","volume":"113","author":"Baek","year":"2018","journal-title":"Expert Systems with Applications"},{"key":"ref_9","unstructured":"Bai, S., Kolter, J. 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