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

Battle Count: 66

The LPPLS model provides a framework for bubble detection and critical time estimation, which is directly relevant to risk management and timing strategies. However, the Iranian market's isolation, capital controls, and limited foreign investor access significantly reduce practical trading applicability. The universality findings are more relevant for academic understanding of market dynamics and for risk monitoring in other emerging/restricted markets. The ±5% daily price limit and T+2 settlement further constrain trading strategies.

LPPLS fitting requires careful grid search over nonlinear parameters (tc, beta, omega) with OLS for linear parameters. The Filimonov-Sornette method is well-documented but requires proper parameter constraints and window selection. Lagrange regularization adds complexity for bubble inception detection. Lomb-Scargle periodogram with surrogate testing (4 null models, 100 realizations each) adds computational overhead. Overall moderate complexity with established algorithms but sensitive to parameter choices and data quality.

Data obtained from TSE official website (tsetmc.com) but automated extraction is restricted and limited accessibility from outside Iran. Code for LPPLS calibration, window optimization, and Lomb-Scargle analysis available only upon reasonable request from the corresponding author. No public repository provided. Single-author work with detailed methodology description in Appendix I.