Crash forecasting in the Korean stock market based on the log-periodic structure and pattern recognition

DOI10.1016/j.physa.2017.09.074OpenAlexW2765358236MaRDI QIDQ2148181

Bonggyun Ko, Woojin Chang, Jae Wook Song

Publication date: 23 June 2022

Published in: Physica A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physa.2017.09.074

zbMATH Keywords

pattern recognitiondiffusion modelfinancial marketprice forecastingnon-linear time serieslog-periodicity

Mathematics Subject Classification ID

Statistical mechanics, structure of matter (82-XX)

Related Items (1)

FORECASTING STOCK MARKET CRASHES VIA REAL-TIME RECESSION PROBABILITIES: A QUANTUM COMPUTING APPROACH

Cites Work

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• Evidence of a worldwide stock market log-periodic anti-bubble since mid-2000
• Stability of money: Phase transitions in an Ising economy
• CRASHES AS CRITICAL POINTS
• Theory of Financial Risk and Derivative Pricing
• Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes

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