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RMB Exchange Rate Prediction Based on Bayesian

  • Wenyuan HuEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1117)

Abstract

The traditional time series analysis and prediction methods do not take into account the prior information of samples and parameters, resulting in a large deviation between the prediction results and the actual data, and the Bayesian parameter estimation method can make full use of the prior information of the parameters. The variance of the estimated parameters is smaller, the estimated results are more accurate, and the predicted results are more real. In order to correctly analyze and predict the changing trend of RMB exchange rate, this paper selects exchange rate data of 995 working days from August 1, 2015 to August 30, 2019 to model the exchange rate of RMB against US dollar in time series autoregressive model. By using the MCMC method, I carry out the model parameters with Gibbs sampling estimation, which makes the prediction of the model more accurate.

Keywords

Autoregressive model Bayesian parameter estimation MCMC method Gibbs sampling 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  1. 1.Shanghai UniversityShanghaiChina

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