Analyzing the Interaction Between Leading Stocks and Exchange Rate Shocks Using Network Analysis and VAR-GARCH: Evidence from the Tehran Stock Exchange

Document Type : Research Paper

Authors

1 Department of Economics, Firuzkuh Branch, Islamic Azad University, Firuzkuh, Iran.

2 Department of Economics, Tehran Central Branch, Islamic Azad University, Tehran, Iran.

Abstract

Identifying leading stocks is critical for investors, particularly in markets lacking comprehensive analytical tools. Effective stock selection necessitates an integrated approach that combines financial network analysis, performance evaluation, and predictive modeling. This study examines firm-level interconnections within the Tehran Stock Exchange, focusing on the implications of exchange rate shocks. A dual-phase analytical framework is applied: first, Minimum Spanning Tree network analysis identifies leading stocks and quantifies the effects of exchange rate fluctuations; second, VAR-GARCH models assess volatility dynamics of leading stocks, while the iterated cumulative sum of squares method detects structural breaks in market behavior. The dataset includes daily returns of 50 top-performing stocks and the free-market USD exchange rate across two periods: pre-shock (March 24, 2016–April 3, 2018) and post-shock (April 4, 2018–July 21, 2020). Pre-shock, Pars Khodro, Foulad, and Kegol dominated the market. Post-shock, export-driven sectors such as metals retained leadership due to competitive advantages, while import-dependent industries like automotive declined significantly. Later, stocks including Veghadir, Foulad, Sharak, and Tipico emerged as new leaders, reflecting structural realignments driven by currency volatility. The findings highlight the efficacy of network-driven methodologies in portfolio optimization and risk management, offering empirical clarity on sectoral dependencies and exchange rate sensitivities in emerging economies.

Keywords

Main Subjects

Article Title [Persian]

تحلیل تعامل سهام‌های پیشرو و شوک‌های نرخ ارز با استفاده از تحلیل شبکه و الگوی VAR-GARCH: شواهدی از بورس اوراق بهادار تهران

Authors [Persian]

  • مصطفی برات پور 1
  • قدرت الله امام وردی 2
  • محمود محمودزاده 1
  • پروانه سلاطین 1
1 گروه اقتصاد، واحد فیروزکوه، دانشگاه آزاد اسلامی، فیروزکوه، ایران.
2 گروه اقتصاد، واحد تهران مرکزی، دانشگاه آزاد اسلامی، تهران، ایران.
Abstract [Persian]

شناسایی سهام پیشرو برای سرمایه‌گذاران، به ویژه در بازارهایی که فاقد ابزارهای تحلیلی جامع هستند، امری حیاتی است. انتخاب مؤثر سهام مستلزم رویکردی یکپارچه است که تحلیل شبکه مالی، ارزیابی عملکرد و مدل‌سازی پیش‌بینانه را ترکیب می‌کند. این مطالعه به بررسی پیوندهای بین‌شرکتی در بورس اوراق بهادار تهران  با تمرکز بر پیامدهای شوک‌های نرخ ارز می‌پردازد. یک چارچوب تحلیلی دو مرحله‌ای به کار گرفته شد: نخست، تحلیل شبکه درخت پوشای کمینه (MST) برای شناسایی سهام پیشرو و اندازه‌گیری تأثیرات نوسانات نرخ ارز استفاده شد. سپس، مدل‌های VAR-GARCH برای تحلیل پویایی‌های نوسان در سهام پیشرو به کار رفتند، در حالی که روش مجموع تجمعی مربعات تکراری (ICSS) برای شناسایی شکست‌های ساختاری در رفتار بازار مورد استفاده قرار گرفت. داده‌ها شامل بازده روزانه ۵۰ سهام برتر و نرخ دلار در بازار آزاد در دو بازه زمانی است: پیش از شوک (05/01/1395تا14/01/1397) و پس از شوک (15/01/1397تا31/4/1399). در دوره پیش از شوک، شرکت‌های پارس خودرو، فولاد و کگل به‌عنوان سهم‌های رهبر شناسایی شدند. پس از شوک ارزی، بخش‌های صادرات‌محور مانند فلزات به دلیل مزیت رقابتی جایگاه رهبری خود را حفظ کردند، در حالی که صنایع واردات‌محور نظیر خودروسازی با افول قابل توجهی مواجه شدند. در مراحل بعدی، سهام‌هایی مانند وغدیر، فولاد، شاراک و تیپیکو به عنوان رهبران جدید ظهور یافتند که بازآرایی ساختاری ناشی از نوسانات ارزی را منعکس می‌کنند. یافته‌ها بر کارایی روش‌های مبتنی بر شبکه در بهینه‌سازی سبد سرمایه‌گذاری و مدیریت ریسک تأکید می‌کنند و وابستگی‌های بخشی و حساسیت به نرخ ارز را در اقتصادهای نوظهور به شکلی تجربی تبیین می‌نمایند.

Keywords [Persian]

  • جهش نرخ ارز.سهم‌های رهبر .درخت پوشای کمینه. VAR
  • GARCH

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  • Receive Date: 07 February 2025
  • Revise Date: 15 March 2025
  • Accept Date: 17 March 2025

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