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Predicting Financial Market Crashes Using Ghost Singularities

Author

Listed:
  • Damian Smug

    (University of Exeter)

  • Peter Ashwin

    (University of Exeter)

  • Didier Sornette

    (ETH Zürich and Swiss Finance Institute)

Abstract

We analyse the behaviour of a non-linear model of coupled stock and bond prices exhibiting periodically collapsing bubbles. By using the formalism of dynamical system theory, we explain what drives the bubbles and how foreshocks or aftershocks are generated. A dynamical phase space representation of that system coupled with standard multiplicative noise rationalises the log-periodic power law singularity pattern documented in many historical financial bubbles. The notion of ‘ghosts of finite-time singularities’ is introduced and used to estimate the end of an evolving bubble, using finite-time singularities of an approximate normal form near the bifurcation point. We test the forecasting skill of this method on different stochastic price realisations and compare with Monte Carlo simulations of the full system. Remarkably, the former is significantly more precise and less biased. Moreover, the method of ghosts of singularities is less sensitive to the noise realisation, thus providing more robust forecasts.

Suggested Citation

  • Damian Smug & Peter Ashwin & Didier Sornette, 2017. "Predicting Financial Market Crashes Using Ghost Singularities," Swiss Finance Institute Research Paper Series 17-23, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp1723
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    More about this item

    Keywords

    Financial Markets; State Space Models; Price Forecasting; Simulation; Bifurcation Theory; Finite-Time Singularity;
    All these keywords.

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G01 - Financial Economics - - General - - - Financial Crises
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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