Time is limited on the road to asymptopia

• Tác giả: Mark Kirstein, Ivonne Schwartz
• Ngôn ngữ: eng
• Ký hiệu phân loại: 153.753 Time and rhythm perception
• Thông tin xuất bản: 2022
• Bộ sưu tập: Báo, Tạp chí
• ID: 195632

Tóm tắt

One challenge in the estimation of financial market agent-based models (FABMs) is to infer reliable insights using numerical simulations validated by only a single observed time series. Ergodicity (besides stationarity) is a strong precondition for any estimation, however it has not been systematically explored and is often simply presumed. For finite-sample lengths and limited computational resources empirical estimation always takes place in pre-asymptopia. Thus broken ergodicity must be considered the rule, but it remains largely unclear how to deal with the remaining uncertainty in non-ergodic observables. Here we show how an understanding of the ergodic properties of moment functions can help to improve the estimation of (F)ABMs. We run Monte Carlo experiments and study the convergence behaviour of moment functions of two prototype models. We find infeasibly-long convergence times for most. Choosing an efficient mix of ensemble size and simulated time length guided our estimation and might help in general.