The Adaptiveness in Stock Markets: Testing the Stylized Facts in the DAX 30

Xuezhong He,Youwei Li

doi:10.2139/ssrn.2666231

Abstract

By testing a simple asset pricing model of heterogeneous agents to characterize the power-law behavior of the DAX 30 from 1975 to 2007, we provide supporting evidence on empirical findings that investors and fund managers use combinations of fixed and switching strategies based on fundamental and technical analysis when making investment decisions. By conducting econometric analysis via Monte Carlo simulations, we show that the autocorrelation patterns, the estimates of the power-law decay indices, (FI)GARCH parameters, and tail index of the model match closely the corresponding estimates for the DAX 30. A mechanism analysis based on the calibrated model provides further insights into the explanatory power of heterogeneous agent models.

Highlights

Empirical evidence suggests that investors and fund managers use combinations of fixed and switching strategies based on fundamental and technical analysis when making investment decisions
By conducting econometric analysis via Monte Carlo simulations of the model with estimated parameters, we show that the autocorrelation patterns, the estimates of the power-law decay indices, (FI)GARCH parameters, and tail index of the model match closely to the corresponding estimates for the DAX 30
The results show that the calibrated model closely generates the characterization of the power-law behavior of the DAX 30 in the return autocorrelation, volatility clustering and tails

Summary

INTRODUCTION

The use of fundamental and technical analysis by financial market professionals is well documented. Empirical evidence suggests that investors and fund managers use combinations of fixed and switching strategies based on fundamental and technical analysis when making investment decisions. In this paper we empirically test a simple asset pricing model of heterogeneous agents using both fixed and switching strategies and show that the model is able to characterize the power-law behavior of the daily DAX 30 index from 1975 to 2007. In this paper, following Li et al (2010) and He and Li (2015) we take the weak econometric interpretation of Geweke (2006) based on the power-law decay patterns of the autocorrelation of returns, the squared returns and the absolute returns for the DAX 30 stock market daily closing price index We do this by choosing the interesting parameters in the whole model class that minimize the distance between particular actual data based autocorrelations and HAMs based autocorrelations.

THE MODEL

ESTIMATION OF THE POWER-LAW BEHAVIOR IN THE DAX 30

MECHANISM EXPLANATION OF THE CALIBRATION RESULTS

Return Normal

CONCLUSION