Universal Dynamics of Financial Bubbles in Isolated Markets: Evidence from the Iranian Stock Market

ArXiv ID: 2512.12054 “View on arXiv”

Authors: Ali Hosseinzadeh

Abstract

Speculative bubbles exhibit common statistical signatures across many financial markets, suggesting the presence of universal underlying mechanisms. We test this hypothesis in the Iranian stock market, an economy that is highly isolated, subject to capital controls, and largely inaccessible to foreign investors. Using the Log-Periodic Power Law Singularity (LPPLS) model, we analyze two major bubble episodes in 2020 and 2023. The estimated critical exponents beta around 0.46 and 0.20 fall within the empirical ranges documented for canonical historical bubbles such as the 1929 DJIA crash and the 2000 Nasdaq episode. The Tehran Stock Exchange displays clear LPPLS hallmarks, including faster-than-exponential price acceleration, log-periodic corrections, and stable estimates of the critical time horizon. These results indicate that endogenous herding, imitation, and positive-feedback dynamics, rather than exogenous shocks, play a dominant role even in politically and economically isolated markets. By showing that an emerging and semi-closed financial system conforms to the same dynamical patterns observed in global markets, this paper provides new empirical support for the universality of bubble dynamics. To the best of our knowledge, it also presents the first systematic LPPLS analysis of bubbles in the Tehran Stock Exchange. The findings highlight the usefulness of LPPLS-based diagnostic tools for monitoring systemic risk in emerging or restricted economies.

Keywords: Log-Periodic Power Law Singularity (LPPLS), Speculative Bubbles, Systemic Risk, Emerging Markets, Herding Dynamics

Complexity vs Empirical Score

• Math Complexity: 7.0/10
• Empirical Rigor: 8.0/10
• Quadrant: Holy Grail
• Why: The paper applies a sophisticated mathematical model (LPPLS) from statistical physics with non-linear fitting and multiple parameters, demonstrating high math density. It is data-heavy, analyzing two specific historical bubble episodes with statistical estimates and validation against historical benchmarks, showing strong empirical backing for real-world application.

  flowchart TD
    A["Research Goal: Test universality of<br>financial bubble dynamics<br>in the isolated Iranian stock market"] --> B["Data Source: Tehran Stock Exchange<br>Two major bubble episodes<br>(2020 and 2023)"]
    B --> C["Methodology: Log-Periodic Power Law<br>Singularity (LPPLS) Model"]
    C --> D["Computational Process:<br>1. Model price acceleration<br>2. Estimate critical time (t_c)<br>3. Calculate critical exponent (β)<br>4. Analyze log-periodic oscillations"]
    D --> E1["2020 Bubble Outcome"]
    D --> E2["2023 Bubble Outcome"]
    E1 --> F["Key Findings:<br>• β ≈ 0.46 (2020) & 0.20 (2023)<br>• Values match canonical bubbles<br>(1929 DJIA, 2000 Nasdaq)<br>• Endogenous herding dominates<br>over exogenous shocks<br>• Universality confirmed in<br>isolated markets"]
    E2 --> F