Power-law behaviour, heterogeneity, and trend chasing

By Xue-zhong He, Youwei Li. 2007

114 citations recorded by the source corpus.

Long-range dependence in volatility is one of the most prominent examples in financial market research involving universal power laws. Its characterization has recently spurred attempts to provide some explanations of the underlying mechanism. This paper contributes to this recent line of research by analyzing a simple market fraction asset pricing model with two types of traders---fundamentalists who trade on the price deviation from estimated fundamental value and trend followers whose conditional mean and variance of the trend are updated through a geometric learning process. Our analysis shows that agent heterogeneity, risk-adjusted trend chasing through the geometric learning process, and the interplay of noisy fundamental and demand processes and the underlying deterministic dynamics can be the source of power-law distributed fluctuations. In particular, the noisy demand plays an important role in the generation of insignificant autocorrelations (ACs) on returns, while the significant decaying AC patterns of the absolute returns and squared returns are more influenced by the noisy fundamental process. A statistical analysis based on Monte Carlo simulations is conducted to characterize the decay rate. Realistic estimates of the power-law decay indices and the (FI)GARCH parameters are presented.

Subfields: Condensed Matter Physics, Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/83ac30357089f946ea8c24a6b44372b5fcaaa68f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Condensed Matter Physics

In Economics and Econometrics

In Finance

Citations in the corpus

Time-varying beta: a boundedly rational equilibrium approach (2010, unknown): “Chiarella et al. (2006), Alfarano et al. (2005), Gaunersdorfer and Hommes (2007), and He and Li (2007) .”
Structural stochastic volatility in asset pricing dynamics: Estimation and model contest (2012, background): “2 Recent surveys on this research are Hommes (2006), LeBaron (2006), Chiarella et al.”
Heterogeneity, convergence, and autocorrelations (2008, methodology): “A more detailed analysis of the generating mechanism of the long-range dependence and statistical estimates and tests based on Monte Carlo simulation can be found in He and Li (2007).”