نوع مقاله : علمی
نویسندگان
1 گروه اقتصاد دانشکده علوم اجتماعی و اقتصاد دانشگاه الزهرا
2 استاد گروه اقتصاد، دانشکده علوم اجتماعی و اقتصاد، دانشگاه الزهرا، تهران، ایران
3 دانشیار گروه اقتصاد، دانشکده علوم اجتماعی و اقتصاد، دانشگاه الزهرا، تهران، ایران
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Financial markets, as one of the main pillars of the economic system, are constantly exposed to price fluctuations driven by both fundamental and non-fundamental factors. Among the most critical phenomena in this context is the formation of asset price bubbles, which represent persistent deviations of asset prices from their fundamental values and can significantly affect investors’ decisions, market stability, and policymaking. This study aims to identify and compare the effectiveness of three econometric approaches—Kalman filter, Martingale test, and Time Series Decomposition—in detecting asset price bubbles in emerging financial markets. Using daily data from the Iranian foreign exchange market, gold market prices (18-carat), and the Tehran Stock Exchange index over the period from April 28, 2014, to March 18, 2025, the study evaluates each method’s ability to detect deviations from fundamental values and capture speculative behavior. The results indicate that the Kalman filter provides the most consistent and reliable estimates of fundamental prices across all three markets, showing higher stability and lower sensitivity to outliers. In contrast, time series decomposition captures more volatile and extreme bubble episodes but exhibits greater variability and dispersion in its estimates, while the Martingale test offers complementary insights into systematic price deviations. Overall, the findings suggest that the Kalman filter serves as a flexible and robust tool for identifying asset price bubbles, offering valuable guidance for policymakers and investors in designing effective risk management strategies and promoting financial market stability in emerging economies.
کلیدواژه‌ها [English]
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