科学研究
学术报告
Bayesian Inference method and calibration of stochastic financial models
发布时间:2014-01-03浏览次数:

Bayesian Inference method and calibration of stochastic financial models

(贝叶斯估计方法以及随机经济模型的参数估计)

2014年1月3人下午2:00pm-4:00pm

地址: 同济大学数学系致远楼107 演讲厅

田天海教授/Professor Tianhai TIAN

School of Mathematical Sciences,

Monash University, Melbourne, Australia


Abstract

Stochastic models are becoming a more and more important tool to

describe complex natural systems. In finance and economics, stochastic

differential equation is a fundamental method to study the uncertainty

in financial systems. A major challenge in stochastic modeling is how

to estimate unknown model parameters based on the financial market

data. In this talk we will discuss two types of major methods for

estimating model parameters: the optimization method and Bayesian

inference methods. These methods will be applied to infer parameters

in financial models.


随机模型正在成为描述复杂自然生态系统的一个重要的工具。在金融和经济等领域,随机微分方程是研究金融市场不确定性的一个基本方法。随机数学建模的一个主要挑战是如何基于金融市场的数据来估计模型未知参数。这次讲座将讨论两类估计模型参数的主要方法:优化方法和贝叶斯估计方法。并通过例子讨论这些方法在随机经济模型中的应用。