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Adaptive and Sophisticated Learning in Repeated Normal Form Games.
We show how to enhance the performance of a Smolyak method for solving dynamic economic models. First, we propose a more efficient implementation of the Smolyak method for interpolation, namely, we s...
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...
Discusses an approach to economics related to optimality and general equilibrium theory that is relevant to natural resources policy. View of some economists on resource shortages; Basic problem of ad...
We consider a dynamic game model of a two-country monetary union. Governments (fiscal policies) pursue national goals while the common central bank’s monetary policy aims at union-wide objectives. For...
A Bayesian estimation of a GARCH model is performed for US Dollar/Japanese Yen exchange rate by the Metropolis-Hastings algorithm with a proposal density given by the adaptive construction scheme. In ...
We present an online approach to portfolio selection. The motivation is within the context of algorithmic trading, which demands fast and recursive updates of portfolio allocations, as new data arrive...
Discrete time hedging in a complete diffusion market is considered. The hedge portfolio is rebalanced when the absolute difference between delta of the hedge portfolio and the derivative contract reac...
This paper develops a matrix-variate adaptive Markov chain Monte Carlo (MCMC) methodology for Bayesian Cointegrated Vector Auto Regressions (CVAR). We replace the popular approach to sampling Bayesian...
Based on the daily data of American and Chinese stock markets, the dynamic behavior of a financial network with static and dynamic thresholds is investigated. Compared with the static threshold, the ...
Adaptive Monte Carlo methods are recent variance reduction techniques. In this work, we propose a mathematical setting which greatly relaxes the assumptions needed by for the adaptive importance samp...
Adaptive wave model for financial option pricing is proposed, as a high-complexity alternative to the standard Black--Scholes model. The new option-pricing model, representing a controlled Brownian mo...
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 ...

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