Predictable markets? A news-driven model of the stock market

Maxim Gusev, Dimitri Kroujiline (), Boris Govorkov, Sergey V. Sharov, Dmitry Ushanov and Maxim Zhilyaev
Additional contact information
Maxim Gusev: IBC Quantitative Strategies, Postal: Tärnaby, Sweden
Dimitri Kroujiline: LGT Capital Partners, Postal: Pfäffikon, Switzerland
Boris Govorkov: IBC Quantitative Strategies, Postal: Tärnaby, Sweden
Sergey V. Sharov: N.I. Lobachevsky State University, Postal: Advanced School of General & Applied Physics, Nizhny Novgorod, Russia
Dmitry Ushanov: Department of Mechanics and Mathematics, Postal: Moscow State University, Moscow, Russia
Maxim Zhilyaev: Mozilla Corporation, Postal: Mountain View, CA, USA

Algorithmic Finance, 2015, vol. 4, issue 1-2, 5-51

Abstract: We attempt to explain stock market dynamics in terms of the interaction among three variables: market price, investor opinion and information flow. We propose a framework for such interaction and apply it to build a model of stock market dynamics which we study both empirically and theoretically. We demonstrate that this model replicates observed market behavior on all relevant timescales (from days to years) reasonably well. Using the model, we obtain and discuss a number of results that pose implications for current market theory and offer potential practical applications.

Keywords: Stock market; market dynamics; return predictability; news analysis; language patterns; investor behavior; herding; business cycle; sentiment evolution; reference sentiment level; volatility; return distribution; Ising; agent-based models; price feedback; nonlinear dynamical systems (search for similar items in EconPapers)
JEL-codes: C00 (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:ris:iosalg:0035

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