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Adaptive and Sophisticated Learning in Repeated Normal Form Games.
This paper examines the adaptive market hypothesis of Lo (2004, 2005) using the Ito and Noda’s (2012) non-Bayesian time-varying AR model in Japan. As shown in Ito and Noda (2012), their degree of mar...
We consider a model in which a trader aims to maximize expected risk-adjusted profit while trading a single security. In our model, each price change isa linear combination of observed factors, impact...
We study the performance of the adaptive construction scheme for a Bayesian inference on the Quadratic GARCH model which introduces the asymmetry in time series dynamics.In the adaptive construction s...
We perform Markov chain Monte Carlo simulations for a Bayesian inference of the GJR-GARCH model which is one of asymmetric GARCH models. The adaptive construction scheme is used for the construction ...
We perform the Bayesian inference of a GARCH model by the Metropolis-Hastings algorithm with an adaptive proposal density. The adaptive proposal density is assumed to be the Student’s t-distribution a...
We propose a method to construct a proposal density for the Metropolis-Hastings algorithm in Markov Chain Monte Carlo (MCMC)simulations of the GARCH model. The proposal density is constructed adaptive...

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