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  <doi_batch_id>aspg-1-4334-1792176608</doi_batch_id>
  <timestamp>20261016185008</timestamp>
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   <depositor_name>American Scientific Publishing Group</depositor_name>
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  <journal>
   <journal_metadata language="en">
    <full_title>American Journal of Business and Operations Research</full_title>
    <abbrev_title>AJBOR</abbrev_title>
    <issn media_type="print">2770-0216</issn>
    <issn media_type="electronic">2692-2967</issn>
   </journal_metadata>
   <journal_issue>
    <publication_date media_type="online">
     <year>2026</year>
    </publication_date>
    <journal_volume>
     <volume>14</volume>
    </journal_volume>
    <issue>2</issue>
   </journal_issue>
   <journal_article publication_type="full_text">
    <titles>
     <title>Intelligent Data Analysis of Asymmetric Oil Price Transmission and Financial Development: Evidence from an Emerging Market Economy</title>
    </titles>
    <contributors>
     <person_name sequence="first" contributor_role="author">
      <given_name>Heba</given_name>
      <surname>Moselhy</surname>
      <affiliations>
       <institution>
        <institution_name>Business Administration Department, Delta Higher Institute for Management and Accounting Information Systems, Egypt</institution_name>
       </institution>
      </affiliations>
     </person_name>
     <person_name sequence="additional" contributor_role="author">
      <given_name>Noura</given_name>
      <surname>Metawa</surname>
      <affiliations>
       <institution>
        <institution_name>College of Business Administration, University of Sharjah, United Arab Emirates</institution_name>
       </institution>
       <institution>
        <institution_name>College of Business Administration, Mansoura University, Egypt</institution_name>
       </institution>
      </affiliations>
     </person_name>
    </contributors>
    <jats:abstract>
     <jats:p>This article provides a data analysis framework to study asymmetric macro-financial relationships in an emerging market economy with significant energy dependence. Using annual observations for Egypt over 1990–2024, we estimate a nonlinear autoregressive distributed lag (NARDL) error-correction model in which changes in Brent crude prices are algorithmically decomposed into positive and negative cumulative partial-sum series. A composite financial development index, constructed from banking-sector depth indicators, enters the model both as a direct regressor and as an interaction term with each shock component. The results show that positive oil-price shocks carry a substantially larger long-run penalty on real GDP growth than negative shocks of equal magnitude—consistent with the cost-side exposure of a net oil-importing economy. Financial deepening conditions the transmission of these shocks but does not neutralise them; the allocation of credit toward productive private-sector activity, rather than the aggregate volume of intermediation, determines the direction of the moderating effect. Rolling-window and dynamic multiplier analyses confirm structural instability in the oil–growth relationship across sub-periods, validating the nonlinear modelling approach over standard linear alternatives. Unit root tests with structural breaks, NARDL bounds tests, and a battery of diagnostic checks support the robustness of the estimated long-run relationships. The findings carry direct implications for energy-risk management, financial-sector reform, and growth-stability policy in emerging market settings.</jats:p>
    </jats:abstract>
    <publication_date media_type="online">
     <year>2026</year>
    </publication_date>
    <pages>
     <first_page>37</first_page>
     <last_page>42</last_page>
    </pages>
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     <item_number item_number_type="article-number">4334</item_number>
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     <doi>10.54216/AJBOR.140206</doi>
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