Economic Crisis and Investor Behaviour

This study investigates the effects of crises on domestic and foreign investors’ behaviours by utilizing a nonlinear approach. Considering the nonlinearity inherent in many financial variables, this study proposes an appropriate econometric modelling for analysing the investors’ behaviour, particularly during turbulent times. Specifically, STAR-STGARCH family models and generalized impulse response function analysis (GIRF) are employed to understand the different reactions of foreign and domestic investors at the Malaysian Stock Exchange market during the 1997 Asian crisis. The results of the model and the GIRF analysis have shown that foreign investors exhibited a herding behavior during the crisis and responded the shock more quickly than the domestic investors. When the same analysis is applied to understand the effects of the 2008 Subprime Mortgage Crisis in the Malaysian market, the behaviors of foreign and domestic investors are found to be very similar

Estimation of Financial Agent-Based Models with Simulated Maximum Likelihood

This paper proposes a general computational framework for empirical estimation of financial agent based models, for which criterion functions do not have known analytical form. For this purpose, we adapt a nonparametric simulated maximum likelihood estimation based on kernel methods. Employing one of the most widely analysed heterogeneous agent models in the literature developed by Brock and Hommes (1998), we extensively test properties of the proposed estimator and its ability to recover parameters consistently and efficiently using simulations. Key empirical findings point us to the statistical insignificance of the switching coefficient but markedly significant belief parameters defining heterogeneous trading regimes with superiority of trend-following over contrarian strategies. In addition, we document slight proportional dominance of fundamentalists over trend following chartists in main world markets