Berlin 2018 – wissenschaftliches Programm
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SOE: Fachverband Physik sozio-ökonomischer Systeme
SOE 2: Financial Markets and Risk Management I
SOE 2.1: Vortrag
Montag, 12. März 2018, 09:30–09:45, MA 001
Reality-check for Econophysics: Likelihood-based fitting of physics-inspired market models to empirical data — •Nils Bertschinger1,2, Iurii Mozzhorin2, and Sitabhra Sinha3 — 1Frankfurt Institute for Advanced Studies — 2Goethe University, Frankfurt am Main — 3Institute of Mathematical Sciences, Chennai
The statistical description and modeling of volatility plays a prominent role in econometric, risk management and finance. GARCH and stochastic volatility models have been intensively studied and are routinely fitted to market data, albeit providing a phenomenological description only.
In contrast, the field of econophysics explains observed market statistics as emerging from the collective dynamics of many actors following heterogeneous, yet simple, rather mechanistic rules. While such models generate volatility dynamics qualitatively matching several stylized facts and thus illustrate the possible role of different mechanisms, such as chartist trading, herding behavior etc., rigorous and quantitative statistical fits are still mostly lacking.
Here, we show how Stan, a modern probabilistic programming language for Bayesian modeling, can be used to fit several models from econophysics. In contrast to the method of moment matching, which currently gains popularity, our fits are purely likelihood based with many advantages, including systematic model comparison and principled generation of model predictions. In particular, we investigate the models by Vikram & Sinha and Franke & Westerhoff, and provide quantitative comparisons with standard econometric models.