Bayesian estimation of ARMA-GARCH model of weekly foreign exchange rates

Teruo Nakatsuma; Hiroki Tsurumi

doi:10.1023/A:1010058509622

Bayesian estimation of ARMA-GARCH model of weekly foreign exchange rates

Teruo Nakatsuma, Hiroki Tsurumi

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

Abstract

Three Bayesian methods (Markov chain Monte Carlo, Laplace approximation and quadrature formula) are developed to estimate the parameters of the ARMA-GARCH model. The ARMA-GARCH model is applied to weekly foreign exchange rate data of five major currencies, and their stochastic volatilities are judged by the posterior probabilities of stationarity and other conditions.

Original language	English
Pages (from-to)	71-84
Number of pages	14
Journal	Asia-Pacific Financial Markets
Volume	6
Issue number	1
DOIs	https://doi.org/10.1023/A:1010058509622
Publication status	Published - 1999
Externally published	Yes

Keywords

Bayesian inference
Foreign exchange rate
GARCH

ASJC Scopus subject areas

Finance

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10.1023/A:1010058509622

Cite this

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abstract = "Three Bayesian methods (Markov chain Monte Carlo, Laplace approximation and quadrature formula) are developed to estimate the parameters of the ARMA-GARCH model. The ARMA-GARCH model is applied to weekly foreign exchange rate data of five major currencies, and their stochastic volatilities are judged by the posterior probabilities of stationarity and other conditions.",

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AB - Three Bayesian methods (Markov chain Monte Carlo, Laplace approximation and quadrature formula) are developed to estimate the parameters of the ARMA-GARCH model. The ARMA-GARCH model is applied to weekly foreign exchange rate data of five major currencies, and their stochastic volatilities are judged by the posterior probabilities of stationarity and other conditions.

KW - Bayesian inference

KW - Foreign exchange rate

KW - GARCH

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Bayesian estimation of ARMA-GARCH model of weekly foreign exchange rates

Abstract

Keywords

ASJC Scopus subject areas

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