An Econophysics Model of Financial Bubbles

Abstract

Usually financial crises go along with bubbles in asset prices, such as the housing bubble in the US in 2007. This paper attempts to build a mathematical model of financial bubbles from an econophysics, and thus a new perspective. I find that agents identify bubbles only with a time delay. Furthermore, I demonstrate that the detection of bubbles is different on either the individual or collective point of view. Second, I utilize the findings for a new definition of asset bubbles in finance. Finally, I extend the model to the study of asset price dynamics with news. In conclusion, the model provides unique insights into the properties and developments of financial bubbles.

An Ensemble Method: Case-Based Reasoning and the Inverse Problems in Investigating Financial Bubbles

“…Various definitions are available in the Finance literature for asset bubbles [22][23][24], however, broadly described, asset bubbles are significant growths in the market that are not based on substantial change in market or industry performance, and usually escalate and equally dissipate with little or no warning.…”

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“…The current study therefore fills these gaps by first extending the scope of the period of our analysis from February 1, 1986 to October 30, 2018. We equally followed (Herzog, 2015) to employ a more appropriate estimation techniques -Econophysics frequency domain model that allows for stochastic bubbles, not prone to model identification problems to test for the existence of bubble as well as to identify the periods of explosive pricing behavior with focus on obtaining the dates of the beginning and the end of explosive behavior in the WTI, Brent and OPEC oil prices. Furthermore the study attempted to examine the linkages among the series by employing the DCC-GARCH model.…”

“…Other methods includes Markovswitching model that fails to distinguish between periods likely to appear spuriously explosive resulting from high variance and periods with genuine explosive behavior (Funke et al, 1994;Phillips, 2011) PSY; (Phillips et al, 2015) (PWY) that have high chances of erroneously interpreting the presence of explosive behaviour for the presence of rational bubbles (Balcilar et al, 2016;Caspi and Graham, 2018;Ye et al, 2011). We extends extant literature by employing (Herzog, 2015) econophysics frequency domain model that allows for stochastic bubbles, not prone to model identification problem to examine the existence of bubbles in the three leading oil market price indexes. The models allow for nonlinear structure in data with breaks, can detect multiple breaks.…”

An Empirical Approach to Detection of Topic Bubbles in Tweets

“…Several authors have proposed bubble models for financial markets [Herzog 2015] [Johansen 2000] [Protter 2013] [Yan 2011].…”

“…Protter's treatment of bubble is based on stochastic theory and defines a bubble process of an asset as the difference between market price and fundamental price of an asset. Herzzog's [Herzog 2015] approach is based on particle dynamics in Physics and does not base on stochastic theory. Herzog and other authors observe that herd behavior of humans and news are important driving forces of bubbles.…”