Agent-based models of financial markets

Abstract

This review deals with several microscopic ("agent-based") models of financial markets which have been studied by economists and physicists over the last decade: Kim-Markowitz, Levy-Levy-Solomon, ContBouchaud, Solomon-Weisbuch, Lux-Marchesi, Donangelo-Sneppen and Solomon-Levy-Huang. After an overview of simulation approaches in financial economics, we first give a summary of the DonangeloSneppen model of monetary exchange and compare it with related models in economics literature. Our selective review then outlines the main ingredients of some influential early models of multi-agent dynamics in financial markets (Kim-Markowitz, Levy-Levy-Solomon). As will be seen, these contributions draw their inspiration from the complex appearance of investors' interactions in real-life markets. Their main aim is to reproduce (and, thereby, provide possible explanations) for the spectacular bubbles and crashes seen in certain historical episodes, but they lack (like almost all the work before 1998 or so) a perspective in terms of the universal statistical features of financial time series. In fact, awareness of a set of such regularities (power-law tails of the distribution of returns, temporal scaling of volatility) only gradually appeared over the nineties. With the more precise description of the formerly relatively vague characteristics ( e.g. moving from the notion of fat tails to the more concrete one of a power-law with index around three), it became clear that financial markets dynamics give rise to some kind of universal scaling laws. Showing similarities with scaling laws for other systems with many interacting sub-units, an exploration of financial markets as multi-agent systems appeared to be a natural consequence. This topic was pursued by quite a number of contributions appearing in both the physics and economics literature since the late nineties. From the wealth of different flavors of multi-agent models that have appeared by now, we discuss the ContBouchaud, Solomon-Levy-Huang and Lux-Marchesi models. Open research questions are discussed in our concluding section.

Optimal monetary policy in a new Keynesian model with animal spirits and financial markets

“…His approach provides a perfect real sector submodel to an integrated (i.e. macro-finance-interaction) model framework because 1 A litereture overview can be found in Samanidou et al (2007), an empirical model contest in Franke and Westerhoff (2012a). For illustrative examples on exchange rate modeling consult Grauwe and Grimaldi (2005) and Bauer et al (2009).…”

Using Agent-Based Modeling to Assess Liquidity Mismatch in Open-End Bond Funds

“…For an interesting review of influential early projects (see [11]), and, for a more wide ranging (and very entertaining) look at agent-based modeling in finance, see [12]. Of course, simulation methods (apart from agent-based approaches) have been used to study economic phenomena for a long time.…”

“…For example, Stigler's pioneering work that uses Monte Carlo simulations to study trading behaviors in securities markets dates back to 1964 [13]. As further noted in [12], Kim and Markowitz developed one of the first "multi-agent" models to investigate the 1987 stock market crash [14]. Their model has two agent types, "rebalancers" and "portfolio insurers" that trade stocks and hold cash balances.…”

Mechanisms in dynamically complex systems

“…15 In the last decade economists and physicists investigated various microscopic (or ‗agent-based') models of financial markets, for instance the Kim-Markowitz, the Levy-Levy-Solomon, the Cont-Bouchaud, the Solomon-Weisbuch, the Lux-Marchesi, the Donangelo-Sneppen and the Solomon-Levy-Huang model. See Samanidou et al (2007) for a review of these models. 16 See Voit (2001) and Johnson et al( 2003) as well as Casti (1997) for the wider background.…”