Papers - Nakatsuma, Teruo

階層ベイズ・モデルによる資本コストの推定ー主観確率に基づく企業価値評価の試み

NAKATSUMA TERUO

応用計量経済学ハンドブック (朝倉書店)     455 - 496 2010.05

Research paper (scientific journal), Single Work

A Bayesian model averaging approach for portfolio selection

NAKATSUMA TERUO

MTECジャーナル (三菱UFJトラスト投資工学研究所)  21 ( 1 ) 3-41 2009.12

Research paper (scientific journal), Single Work

ベイズ統計学とファイナンスーBlack-Littermanアプローチを例として

NAKATSUMA TERUO

ジャフィー・ジャーナル (朝倉書店)  8 ( 1 ) 1 - 62 2009.03

Research paper (scientific journal), Single Work

状態空間モデルのベイズ分析

NAKATSUMA TERUO

計量経済学のフロンティア (慶應義塾大学出版会)     107-146 2006.03

Research paper (scientific journal), Single Work

経済成長の収束仮説―隠れマルコフ・モデルによる検証―

NAKATSUMA TERUO

ベイズ計量経済分析―マルコフ連鎖モンテカルロ法とその応用 (東洋経済新報社)     175-212 2005.06

Research paper (scientific journal), Single Work, Accepted

A new control variate estimator for an Asian option

NAKATSUMA TERUO

Asia-Pacific Financial Markets 11 ( 2 ) 143 - 160 2004.06

Research paper (scientific journal), Joint Work, Accepted,  ISSN  1387-2834

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There exist several estimators for valuing the Asian option on the arithmetic mean. Among all variance reduction estimators, the one with the control variate derived from the geometric mean has been shown by Boyle et al. (1997) to perform best so far. In this paper, a new improved control variate estimator for this type of Asian option is proposed and investigated. Simulation results confirm that it does perform better than the control variate derived from the geometric mean. The improvement becomes more significant as the volatility increases and/or as the time to expiration lengthens. © Springer 2006.

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Exact inference using variable integrating constant importance distributions

NAKATSUMA TERUO

Computational Economics 23 ( 1 ) 45-70 - 70 2004.02

Research paper (scientific journal), Joint Work, Accepted,  ISSN  0927-7099

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In this paper a new class of importance distributions that are based on normal and t-distributions are introduced. They are labeled variable integrating constant distributions or VIC distributions. The main innovation in this class of distributions is that the standard error associated with each prameter is expanded in an exponential polynomial function of the scaled distance from its mode, with a different polynomial used in each direction and for each parameter. Resulting variances differ at each point in the parameter space, thereby breaking the flexibility limitations that are inherent in normal and t-distributions allowing them to be closely matched to the posterior distribution whose moments are the goal of the inference exercise. Two illustrations are presented in which the performance of normal, t, normal-VIC, and t-VIC importance distributions are compared. Results show the VIC distributions to produce globally stable weights and substantial improvements in the numerical efficiency of importance sampling and independence Metropolis estimates. © 2004 Kluwer Academic Publishers.

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Ratio Tests of a Unit Root

T Nakatsuma, E Gouskova, J Uemura, H Tsurumi

Communications in Statisfics:Theory and Methods (MARCEL DEKKER INC)  29 ( 11 ) 2547 - 2571 2000.11

Research paper (scientific journal), Joint Work, Accepted,  ISSN  0361-0926

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Based on the maximal invariant principle, we derive two ratio tests (locally best invariant test and point optimal test) for a unit root and compare them with previously proposed ratio tests. We also show that our ratio tests tend to have better powers than the Dickey-Fuller test and the modified Dickey-Fuller test.

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Structural changes in volatility of foreign exchange rates after the Asian financial crisis

NAKATSUMA TERUO

Asia-Pacific Financial Markets (Springer Science and Business Media Deutschland GmbH)  7 ( 1 ) 69-82 - 82 2000

Research paper (scientific journal), Single Work,  ISSN  1387-2834

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Regime-shift models of daily returns are estimated for the foreign exchange rates of the Asian currencies that suffered from drastic devaluation during the Asian financial crisis in 1997, and the change points are detected for their volatility structures. Furthermore, how the persistence in the volatility of their exchange rates changed after the crisis is examined. © 2000 Kluwer Academic Publishers.

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Bayesian analysis of ARMA-GARCH models: A Markov chain sampling approach

NAKATSUMA TERUO

Journal of Econometrics (ELSEVIER SCIENCE SA)  95 ( 1 ) 57-69 - 69 2000

Research paper (scientific journal), Single Work, Accepted,  ISSN  0304-4076

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We develop a Markov chain Monte Carlo method for a linear regression model with an ARMA(p, q)-GARCH(r, s) error. To generate a Monte Carlo sample from the joint posterior distribution, we employ a Markov chain sampling with the Metropolis-Hastings algorithm. As illustration, we estimate an ARMA-GARCH model of simulated time series data. (C) 2000 Elsevier Science S.A. All righter reserved. JEL classification: C11; C22.

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

NAKATSUMA TERUO

Asia-Pacific Financial Markets (Springer Science and Business Media Deutschland GmbH)  6 ( 1 ) 71-84 - 84 1999

Research paper (scientific journal), Joint Work, Accepted,  ISSN  1387-2834

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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. © 1999 Kluwer Academic Publishers.

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A Markov-chain sampling algorithm for GARCH models

NAKATSUMA TERUO

Studies in Nonlinear Dynamics and Econometrics (M I T PRESS)  3 ( 2 ) 107-117 - 117 1998

Research paper (scientific journal), Single Work, Accepted,  ISSN  1081-1826

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This paper describes a GAUSS program of a Markov-chain sampling algorithm for GARCH models proposed by Nakatsuma (1998). This algorithm allows us to generate Monte Carlo samples of parameters in a GARCH model from their joint posterior distribution. The samples obtained by this algorithm are used for Bayesian analysis of the GARCH model. As numerical examples, GARCH models of simulated data and of weekly foreign exchange rate series are estimated and analyzed.