早稲田大学理工学研究所研究重点研究「統計科学と金融工学」セミナー
(Project Research Seminar on Statistical
Science & Financial Engineering by
Kiban(A)(15H02061), Research Institute for Science & Engineering, & 早稲田大学理工談話会))
new (2017/2/23)
【Waseda International Symposium】
Topic: Recent Developments in Time series Analysis: Quantile Regression, High Dimensional Data
& Causality
Date: February 26 -28, 2018
Venue:Waseda University, Nishi-Waseda Campus, Building 63, 2nd Floor, Room 5
(Access map:https://www.waseda.jp/top/en/access/nishiwaseda-campus)
Organizer:Masanobu TANIGUCHI (Research Institute for Science & Engineering, Waseda University)
program⇒http://www.taniguchi.sci.waseda.ac.jp/2017_WASEDA_SP.pdf
Supported by:
(1) Kiban (A-15H02061) M. Taniguchi, Research Institute for Science & Engineering, Waseda University
(2) Tokutei-Kadai (B) M. Taniguchi, Research Institute for Science & Engineering, Waseda University
過去のセミナーのお知らせ
日時:2017年8月1日(火)15:30-17:00
Date: August 1, 2017,
15:30 - 17:00
場所:早稲田大学理工
63号館
1階 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
(http://www.sci.waseda.ac.jp/access/)
題目:
Is a matrix exponential specification suitable for the modeling of spatial correlation structures?
講演者:
Maura Mezzetti,
(University of Rome "Tor Vergata", Italy)
Abstract.
This paper investigates the adequacy of the matrix exponential
spatial specification (MESS) as an alternative to the widely used
spatial autoregressive model (SAR). We first analyze the partial and
marginal covariance structures, finding similar behavior for the MESS
and SAR models in particular cases. We then propose a new
implementation of Bayesian parameter estimation for the MESS model with
vague prior distributions, which is shown to be precise and
computationally efficient, and whose predictive accuracy is comparable
to that of the SAR model. Our further proposal of a model including
spatial splines among the regressors increases the predictive accuracy
of the matrix exponential specification with regard to the modeling of
the covariance matrix.
日時:2017年6月23日(金)15:30-17:00
Date: June 23, 2017, 15:30 - 17:00
場所:早稲田大学理工
63号館
1階 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
(http://www.sci.waseda.ac.jp/access/)
題目:
Estimation of time varying covariance matrices
for large datasets
講演者:
Liudas Giraitis.
Queen Mary University of London , UK
Abstract.
This paper investigates the adequacy of the matrix exponential spatial
specification (MESS) as an alternative to the widely used spatial
autoregressive model (SAR). We first analyze the partial and marginal
covariance structures, finding similar behavior for the MESS and SAR
models in particular cases. We then propose a new implementation of
Bayesian parameter estimation for the MESS model with vague prior
distributions, which is shown to be precise and computationally
efficient, and whose predictive accuracy is comparable to that of the
SAR model. Our further proposal of a model including spatial splines
among the regressors increases the predictive accuracy of the matrix
exponential specification with regard to the modeling of the covariance
matrix.
日時:11月30日(水) 16:00 - 17:30
場所:63号館1F 数学応数会議室
講演者:河合玲一郎(The University of Sydney)
Title: Computable Bounding Functions for Expectation, Boundary Value and Obstacle Problems
Abstract: The computation of expectations involving stochastic
processes has long been one of the central issues, in one form or
another, in various fields of natural and social sciences, such as the
Fokker-Planck equation, financial derivatives pricing, the assessment
of ruin probabilities of an insurance company, to name just a few.
In this talk, we propose novel methods for obtaining hard bounding
functions, without recourse to sample path simulation, without
truncating the naturally unbounded domain that arises in this problem,
and without discretizing the time and state variables. Unlike accurate
approximate solutions via the existing discretization-based methods,
our hard bounding functions are free from statistical error and act as
pointwise 100% confidence intervals within which the unknown solution
is guaranteed to exist. The proposed approaches can be applied to a
variety of problem settings, such as mixed boundary conditions,
stochastic volatility, stochastic processes with jumps,
regime-switching and obstacle problems. Numerical results are presented
throughout to support our theoretical developments and to illustrate
the effectiveness of the proposed approaches.
This talk consist of two parts; (i) optimization and (ii) perturbation.
(i)
We propose a novel method for obtaining and tightening hard bounding
functions for the expected value on stochastic differential equations
with the help of the mathematical programming and the Dynkin formula.
In a single implementation of semi-definite programming, the proposed
approach obtains explicit bounds in the form of piecewise polynomial
functions, which bound the expectation over the whole domain both in
time and state. As a consequence, these global bounds store a continuum
of bounding information in the form of a finite number of polynomial
coefficients.
In this talk, we pay particular attention to the American style option pricing problem.
(ii)
It is often the case that expectations are easy to compute for a simple
model, while small perturbations make the computation of expectation
suddenly prohibitive. We propose a novel method for measuring the
impact of such small perturbations in expectations without significant
computing effort. Our hard bounding functions are deterministic in the
form of Markov-type inequalities, parametrized by the perturbation
parameter, so that the upper and lower bounds converge to each other
when the perturbation tends to vanish. The proposed method requires
only well-developed numerical methods for boundary value problems for
partial differential equations and elementary numerical integration of
smooth functions.
================================================
10月のプロジェクトセミナーは下記との共催とさせていただきます
------------------
(I) Waseda International Symposium
”High Dimensional Statistical Analysis for Time Spatial Processes, Quantile and Empirical Likelihood Analysis for Time Series”
Date: October 24 - 26, 2016
Venue: Waseda University Nishi-Waseda Campus Building 55S 2nd Floor, Room 3
(Access map: http://www.sci.waseda.ac.jp/en g/access/)
Organizer: Masanobu TANIGUCHI
プログラム:http://www.taniguchi.sci.wased a.ac.jp/WIS_ver3.pdf
-------------------
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早稲田大学理工学研究所「統計数理および金融数理研究」セミナー
(Research Seminar on Statistics and Financial Mathematics (supported by
Kiban(A)))
および、早稲田大学理工学術院講演会共催
----------------------------------------------------------------------
日時: 9月2日(金) 13:30 - 17:00
Date: September 2 (Fri) 13:30 - 17:00
場所:早稲田大学理工63号館1階 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
(http://www.sci.waseda.ac.jp/access/)
(I) 13:30 - 15:00
講演者(Speaker): Ilia Negri,
Department of Management, Information and
Production Engineering, University of Bergamo (Italy)
題目( Title ): Moment convergence of Z-estimators with applications
(II) 15:30 - 17:00
講演者(Speaker): 近重 裕次,
情報通信研究機構・未来ICT研究所, フロンティア創造総合研究室
題目( Title ): 増殖細胞における遺伝子発現レベルの配分について
================================================
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セミナーのお知らせ
日時: 7月29日(金) 15:00-17:00
場所: 51号館 17階 06室
(http://www.sci.waseda.ac.jp/access/)
講演者: 明石 郁哉 ・ 劉 言 (早稲田大学応用数理学科)
(I) 15:00-16:00
講演題目:L1-自己加重経験尤度を用いた非正則・無限分散モデルの頑健な検定法の構成
講演者:明石 郁哉(早稲田大学応用数理学科)
Abstract:本公演では、経験尤度法を用いた検定方式を統一的に構成することを目的
とする。特に、モデルの計画行列に対する 正則性の仮定と、誤差項の有限分散性の仮
定を緩和し、結果として
無限分散を持つ確率過程や、古典的な分散分析の手法を含む
一般的な枠組みの構成を行う。具体的には、自己加重と分位点回帰の
手法を用いて
計画行列および誤差項の無限分散性をそれぞれ制御し、
経験尤度法を用いて尤度比
検定統計量を構成する。結果として、
無限分散を持つモデルを仮定しながらも統計量は
カイ二乗分布に収束し、
未知母数の推定を省略した検定を行うことが可能となる。さらに
数値例を用いて、
本講演の提案する統計量のパフォーマンスを、従来から用いられてきた
random weighting bootstrap法に基づく検定統計量や
自己加重型Wald統計量と比較
し、経験尤度法の利点を明らかにする。
(II) 16:00-17:00
講演題目:Statistical theory for quantiles in frequency domain
講演者:劉 言(早稲田大学応用数理学科)
Abstract:In this talk, we discuss estimation and hypothesis
testing
for quantiles
in frequency domain of time series models.
For second order stationary stochastic
processes,
the spectral distribution function is uniquely determined
by
the autocovariance functions of the processes. We focus on
the sinusoidal models,
which are contained in the second order
stationary processes. The sinusoidal
components, which show
the nonlinear feature, correspond to jumps in the spectral
distribution function. We define the quantiles of the spectral
distribution function and
propose quantile estimator in frequency
domain as it in time domain. Although the
quantile estimator
has consistency, it is not asymptotically normal, which is
a peculiarity
compared with the estimator in time domain.
We propose a modified quantile estimator
for asymptotic normality
with tractability in hypothesis testing for sinusoid models.
We conclude our talk with several numerical results.
17:30- 懇親会(参加費無料)
場所:56号館地下、生協食堂
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早稲田大学理工学研究所「統計数理および金融数理研究」セミナー
(Research Seminar on Statistics and Financial Mathematics (supported by
Kiban(A)))
5月のセミナーは、下記、数学・応数談話会に合流しますので、お気軽にご参加ください。
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第 7 回早稲田大学数学・応数談話会
日時: 5/26(木)16:30~17:30 (tea time: 16:00~16:30)
会場: 早稲田大学理工62W号館1階大会議室
(http://www.sci.waseda.ac.jp/access/)
講師: 柴田 里程
早稲田大学客員教授,慶應義塾大学名誉教授,
(株)データサイエンスコンソーシアム代表取締役
講演題目: データサイヤンスのすゝめ
Abstract:
講演者が20年以上にわたって提唱してきたデータサイエンス.これを
単なる流行に終わらせず,一つの新しい科学分野として定着させ,広くその
価値を理解してもらうためには何がポイントなのか,これまでの経験にも
とづき具体例を用いながらわかりやすく解説する.
===================================
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セミナーのお知らせ
日時: 4月25日(月) 15:30-17:00
場所: 55N号館 1階 第二会議室
題目: 「高次元の統計学(再び)」
講演者: 青嶋 誠(筑波大学数理物質系)
概要:次元が数万を超えるような高次元データを扱う統計学が,理論と応用
の両面から世界中で活発に研究されています.ゲノム科学・情報工学・金融
工学に見られるように,高次元データは新しいタイプのデータ科学を生み出
そうとしています.高次元データは,上手に扱わないとノイズしか聞こえて
きません.しかし,適切に扱えば,驚くほど豊富な情報を語ってくれるのです.
本講演は,3月19日に開催された日本数学会市民講演会での拙講演について,
リクエストに応える形で,再びお話をさせて頂くものです.高次元の統計学
には,従来の統計学の枠組みを超えた新しい発想が必要になることをご覧に
入れます.ビッグデータに興味をもつ研究者や実務家,そして学生の皆さん
など,必ずしも専門家ではない方々にも最先端の雰囲気をお伝えできればと
思っております.
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セミナーのお知ら
せ
共催 早稲田理工講演会
日時:1月27日(水)14:40 - 16:10
Date: January 27 (Wed), 2016, 14:40 - 16:10
場所:早稲田大学理工63号館1階 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
講演者(Speaker): Chunhao Cai (Nankai
University)
題目(Topic): Mixed fractional Brownian
motion and application in statistics
概要(Abstract): This talk presents a new approach to the analysis of
mixed processes
$Xt=B_t+G_t, t∈[0,T]$,
where $B_t$ is a Brownian motion and $G_t$ is an independent
centered
Gaussian process. We obtain a new canonical innovation
representation of X,
using linear filtering theory. When the kernel
$\frac{\partial^2}{\partial^2K(s,t)}= \partial s \partial t E
G_sG_t,$
has a weak singularity on the diagonal, our results generalize the
classical innovation formulas beyond the square integrable
setting. For
kernels with stronger singularity, our approach is applicable to
processes with additional “fractional” structure, including the
mixed
fractional Brownian motion from mathematical finance. We show how
previously known measure equivalence relations and semimartingale
properties follow from our canonical representation in a unified
way,
and complement them with new formulas for Radon-Nikodym
densities. For
the application, we will use the asymptotic eigenvalues method to
estimation the drift parameter in the mixed fractional O-U
process.
This work will be published from 'Annals of Probability' in the
near
future.
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セミナーのお知ら
せ
早稲田大学理工学研究所プロジェクト研究
「金融数理および年金数理研究」セミナー
( Project Research Seminar on Financial and Pension Mathematics
(supported
by Kiban(A)(15H02061), Research Institute for Science &
Engineering, & 早稲田理工談話会) )
日時:2015年12月22日(火) 15:30-17:00
Date: December 22 (Tues), 2015, 15:30 ― 17:00
場所: 63号館 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
講演者: 鈴木大慈(東京工業大学)
Speaker: Taiji Suzuki(Tokyo Institute
of Technology)
Topic: Statistical properties of high
dimensional low rank tensor estimators
Abstract: We investigate the statistical convergence rate of a Bayesian
low-rank tensor estimator,
and derive the minimax optimalrate for learning a low-rank tensor. Our
problem setting is the regression problem
where the regression coefficient forms a tensor structure. The
convergence rate of the Bayes tensor estimator
is analyzed in terms of both in-sample and out-of-sample predictive
accuracies. It is shown that
a fast learning rate is achieved without any strong convexity of the
observation. Moreover, we show that
the method has adaptivity to the unknown rank of the true tensor.
Finally, we show the minimax optimal learning rate
for the tensor estimation problem, and thus show that the derived bound
of the Bayes estimator is tight
and actually near minimax optimal. If time permitted, we will also
discuss the non-parametric estimation
of a tensor product of non-linear functions.
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セミナーのお知ら
せ
早稲田大学理工学研究所プロジェクト研究
「金融数理および年金数理研究」セミナー案内
(Project
Research Seminar on Financial and Pension Mathematics
(supported by Kiban(A)(15H02061), Research Institute for Science
& Engineering))
10月と11月の上記セミナーは、下記と共催で行いますので、ご参加よろしくお願いします。
題目: "High Dim Statistical Analysis for Spatio-Temporal Processes &
Quantile
Analysis for Time Series"
日時:2015年11月9日(月)~11日(水)
Date: November 9 (Mon.) - 11 (Wed.), 2015
場所:早稲田大学西早稲田キャンパス55号館N棟 1階02A室
Location: Waseda University, Nishi-Waseda Campus, Building 55N 1st
Floor
Room 02A
プログラム&アブストラクト(Program & abstract):
http://www.taniguchi.sci.waseda.ac.jp/2015hokoku/WIS15_final.pdf
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セミナーのお知ら
せ
早稲田大学理工学研究所プロジェクト研究
「金融数理および年金数理研究」セミナー
(Project
Research Seminar on Financial and Pension Mathematics
(supportedby Kiban(A)(15H02061), Research Institute for Science
& Engineering & 早稲田理工談話会))
日時:2015年8月31日(月)15:00 −17:30
Date: August 31 (Mon), 2015, 15:00 — 17:30
場所:早稲田大学理工63号館1階 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
(1) 15:00 − 16:00
Speaker: Shu-Hui Yu, Institute of
Statistics, National University of Kaohsiung
Topic I: Asymptotic inefficiency of
BIC and asymptotic efficiency of TSIC: the case of an I(d) process
Abstract: We consider in this paper an I(d) autoregressive (AR)
process, d>=0 is an unknown integer. While Sin and Yu (2015) show
that Akaike's information criterion (AIC) is
asymptotically inefficient when the lag order is finite, this paper
shows that when the lag order is infinite with (a) exponentially
decaying AR coefficients, or (b) algebraically
decaying AR coefficients, Bayesian information criterion (BIC) is
asymptotically inefficient. These results motivate us to combine the
strengths of AIC and BIC, yielding a so-called
two-stage information criterion (TSIC) for a general I(d) AR process.
We show that TSIC is asymptotically efficient in the
aforementionedthree scenarios.
The paper concludes with a simulation study.
(2) 16:00 − 17:30
Speaker: Ching-Kang Ing, Institute of
Statistical Science, Academia Sinica
Topic II: Model Selection for High-Dimensional Time
Series
Abstract:
In
the past decade, model selection for high-dimensional regression models
is one of the most vibrant research topicsin statistics. However, most
of the attention has been
devoted to situations where observations are independent, and hence
time series data are precluded. Inthis talk, I shall address model
selection problems for some high-dimensional
time series models, including high-dimensional stochastic regression
models and high-dimensional regression models with correlated errors. I
will present rates of convergence of
the orthogonal greedy algorithm (OGA) under various sparsity
conditions. I will also show that when the high-dimensional information
criterion (HDIC) of Ing and Lai (2011) is used in
conjunction with the OGA, the resultant predictor achieves the optimal
error rate. Rates of convergence of the OGA are furtherestablished
under model misspecification. Applications
of this latter result to model selection for high-dimensional
interaction models will also be given.
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日時: 2015年6月24日(水)15:30 -- 17:00
Date: June 24 (Wed), 2015 15:30 -- 17:00
場所: 早稲田大学理工63号館1階 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
(1)
正規定常過程の自己共分散行列の縮小推定
須藤 慶大(早稲田大学 基幹理工学研究科)
(2)
Discriminant and cluster analysis of high-dimensional time series data
by a class of disparities
長幡 英明(早稲田大学基幹理工学研究科)*,
劉 言(早稲田大学基幹理工学研究科),
内山 弘隆(早稲田大学基幹理工学研究科),
谷口 正信(早稲田大学 理工学研究所)
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日時:
2015年5月27日(水)15:30 -- 17:00
Date: May 27 (Wed), 2015 15:30 -- 17:00
場所: 早稲田大学理工63号館1階 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
講演者: 筑波大学数理物質科学研究科 矢田 和善
講演題目: 高次元データにおける分類問題について
アブストラクト:
高次元データにおける高精度な判別法とPCAを用いたクラスタ−分析法を紹介する。
判別分析では、判別方式を一般的に与え、高次元のもとで誤判別率の漸近的な評価式
を導出することで最適性について議論する。さらに、その評価式にもとづき、冗長な
変数を除去するための特徴選択を用いた2次判別法を提案する。
クラスター分析では、母集団に混合分布を考え、高次元小標本データの幾何学的表
現を明らかにし、PCAの一致性を導出する。さらに、その一致性により、高次元小標
本データを幾何的に分類できることを示す。本研究は青嶋教授(筑波大学)との共同研究
です。
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日時:2015年4月29日(水) 15:30-17:00
Date:
April 29 (Wed), 2015 15:30 - 17:00
場所:早稲田大学理工63号館1階 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
共
催 早稲田理工学術院談話会
講
演題目 : 高次元中心極限定理に関する話題
講
演者 : 加藤 賢悟 東京大学大学院経済学研究科
ア
ブストラクト:In this talk I will discuss central limit and bootstrap
theorems
for probabilities that sums of centered high-dimensional
random
vectors hit rectangles and sparsely convex sets. Specifically,
we
derive Gaussian and bootstrap approximations for the probabilities
$\Pr(n^{-1/2}\sum_{i=1}^n
X_i\in A)$ where $X_1,\dots,X_n$ are
independent
random vectors in $\R^p$ and $A$ is a rectangle, or, more
generally,
a sparsely convex set, and show that the approximation
error
converges to zero even if $p=p_n\to \infty$ as $n \to \infty$
and
$p \gg n$; in particular, $p$ can be as large as $O(e^{Cn^c})$ for
some
constants $c,C>0$. The result holds uniformly over all
rectangles,
or more generally, sparsely convex sets, and does not
require
any restriction on the correlation structure among coordinates
of
$X_i$. Sparsely convex sets are sets that can be represented as
intersections
of many convex sets whose indicator functions depend
only
on a small subset of their arguments, with rectangles being a
special
case. This talk is based on joint work with Victor
Chernozhukov
(MIT) and Denis Chetverikov (UCLA).
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早稲田シンポジウム「漸近十分性、漸近有効性とセミマルチンゲール」
Organizers:
Masanobu TANIGUCHI (Waseda Univ.), Kiyoshi INOUE (Waseda Univ.),
Yoichi MIYATA (Takasaki Econ Univ.) & Xiaoling DOU (Waseda Univ.)
Supported by Kiban (A) (23244011) (M. Taniguchi)
日時: 2015年3月2日 - 4日
場所: 早稲田
大学西早稲田キャンパス
(i) 3月2日、3日: 55号館S棟2階 第3会議室
(ii) 3月4日: 55号館N棟1階 第1会議室
Program
March 2
13:30 - 13:40: Masanobu TANIGUCHI (Waseda Univ.)
Opening address
13:40 - 14:10: Fumiya AKASHI (Waseda Univ.)
Higher-order asymptotic properties of generalized empirical likelihood
estimator for alpha-stable processes
14:10 - 14:40: Yoichi NISHIYAMA (Inst. Stat. Math. Tokyo)
A stochastic maximal inequality, monotone convergence arguments, and
related topics
14:40 - 15:10: Satoshi KURIKI (Inst. Stat. Math. Tokyo), with
Hsien-Kuei Hwang
A generalization of Anderson-Darling goodness-of-fit statistic based on
multifold integrated empirical distribution functions
15:10 - 15:30: Coffee break
15:30 - 16:10: Stanislav VOLGUSHEV (Ruhr-Univ. Bochum), with Holger
Dette, Marc Hallin and Tobias Kley
Quantile spectral analysis
16:10 - 16:50: Qi-Man SHAO (The Chinese Univ. Hong Kong)
Perspective of self-normalized limit theory
16:50 - 17:30: Marco LIPPI (Einaudi Inst. Economics & Finance),
with Mario Forni, Alessandro Giovannelli and Stefano Soccorsi
Dynamic factor models with infinite dimensional factor space.
Forecasting US monthly macroeconomic series.
March 3
10:00 - 10:30: Yan LIU (Waseda Univ.)
Empirical likelihood methods for quantile regression with long range
dependent errors
10:30 - 11:00: Xiaoling DOU (Waseda Univ.), with Satoshi Kuriki,
Gwodong Lin and Donald Richards
Baker's distribution and the B-spline copula
11:00 - 11:20: Coffee Break
11:20 - 11:50: Toshio HONDA (Hitotsubashi Univ.), with Ming-Yen Cheng
and Jialiang Li
Efficient estimation in semivarying coefficient models for
longitudinal/clustered data
11:50 - 13:30: Lunch
13:30 - 14:00: Shu-Hui YU (National University of Kaohsiung)
Toward optimal averaging in regression models with time series errors
14:00 - 14:40: Xiaofeng SHAO (Univ. Illinois)
Martingale difference correlation and high dimensional feature screening
14:40 - 15:20: Ching-Kang ING (Inst. Stat. Science, Academia Sinica)
Group and variable selection in high-dimensional regressions
15:20 - 15:40: Coffee Break
15:40 - 16:20: Holger DETTE (Ruhr-Univ. Bochum)
Detection of multiple structural breaks in multivariate time series
16:20 - 17:00: Marc HALLIN (ECARES, Université libre de Bruxelles)
Generalized dynamic factor models and volatilities
18:00 -: Buffet-style party
(Cafeteria; Basya-Michi)
March 4
10:00 - 10:30: Yoichi MIYATA (Takasaki city Univ. of Econ.)
The validity of Bayesian information criteria in misspecified models
10:30 - 11:00: Tomoyuki AMANO (Wakayama Univ.), with Masanobu Taniguchi
(Waseda Univ.)
Control variate method for time series
11:00 - 11:30: Hiroaki OGATA (Tokyo Metropolitan Univ.)
Stationary circular time series
11:30 - 12:00: Kiyoshi INOUE (Waseda Univ.)
Precision of estimators for common parameters from several populations
12:00 - 13:30: Lunch
13:30 - 14:00: Kenta KOIZUMI and Hiroshi SHIRAISHI (Keio Univ.)
Statistical estimation for optimal dividend barrier
14:00 - 14:30: Kenichiro TAMAKI (Waseda Univ.)
One-step time series model-building by empirical likelihood
14:30 - 15:00: Shunsuke Sakai and *Junichi Hirukawa (Niigata Univ.)
Rank tests for an ARMA model against other tv-ARMA models
15:00 - 15:20: Coffee Break
15:20 - 15:50: Yasutaka SHIMIZU (Waseda Univ.)
LSE-type estimation for stochastic processes with small Levy noise
15:50 - 16:20: Ryozo MIURA (Hitotsubashi Univ.)
Asymptotic theory of R-estimators from iid to weakly dependent
observations: the case of one sample models and simple linear
regression models with generalized Lehmann’s alternative models
16:20 - 17:00: Herbert HEYER (Univ. Tuebingen)
Information functionals and applications to random walks and statistics
17:00 - 17:10: Takeru SUZUKI (Waseda Univ.)
Closing address
18:00 -: Party (Further
details will be announced later)
---------------------------------------------------------------------------------------------------
日時:2015年1月28日(水) 15:30ー17:00
場所:63号館、1階、数学応用数理会議室
講演題目及び講演者
Title: Robustness
in the context of ordinal response models.
Speaker: Anna Clara Monti, University of Sannio,
Italy
---------------------------------------------------------------------------------------------------
日時:2014年12月22日(月) 13:00-17:30
場所:早稲田大学理工63号館1階 数学応数会議室
共
催 早稲田理工学術院談話会
(1)
13:00 - 14:30
講
演者:Runhuan Feng (University of Illinois at Urbana-Champaign, USA)
講
演題目:Quantitative Risk Management of Variable Annuities Guaranteed
Benefits:
Opportunities and Challenges
(2)
14:30 - 16:00
講
演者:Jose Garrido (Concordia University, Canada)
講
演題目:On the finite-time Gerber-Shiu function and its use as a risk
measure
(3)
16:00 - 17:30
講
演者: 謝 衷潔(XIE, Zhongjie) (北京大学)
講
演題目: Some Interesting Problems in Statistical Testing of Random
Sequences
18:00-
ビュッフェ形式懇親会 於 馬車道
上記、 (1),(2) の講演に関する問い合わせは、 清水泰隆 <shimizu@waseda.jp> まで、
(3)
の講演に関する問い合わせは、鈴木武 <tasuzuki@waseda.jp> まで
お願いします。
---------------------------------------------------------------------------------------------------
日時:2014年11月25日(火) 16:00-17:00
場所:早稲田大学理工63号館1階 数学応数会議室
Title: Recent developments in estimation for CO-GARCH(1,1) models
Speaker: Ilia Negri (Univ. Bergamo, Italy)
Abstract:
COGARCH models are continuous time version of the well known GARCH
models of financial returns.
It turns out that COGARCH(1,1) captures the so called stylized facts of
volatility:
is random and has jumps; has heavy-tailed margins; has cluster in the
extremes (volatility clustering).
In this talk Method of Moments and Pseudo Maximum Likelihood estimators
are presented for such COGARCH(1,1) models
and it is shown how the method of Prediction-Based Estimating
Functions, that can be applied to this model
if the higher order structure of the process is clarified, outperforms
the other available estimation methods.
---------------------------------------------------------------------------------------------------
日時:2014年10月22日(水) 14:00-17:00
場所:63号館、1階、数学応用数理会議室
講演題目及び講演者
(i) 14:00 - 15:30<br>
Abnormal
volume effects on the CAPM with heteroskedasticity:
A quantile regression approach
Cathy W.S. Chen (Feng Chia University, Taiwan)
(ii) 15:30 - 17:00
LASSO estimation of threshold autoregressive models
Ngai Hang Chan (Chinese University of Hong Kong, Hong Kong)
17:30 - 馬車道で立食式懇親会
---------------------------------------------------------------------------------------------------
日時:2014年7月23日(水)15:45−17:30
Date: July 23 (Wed), 2014 15:45−17:30
場所:早稲田大学理工63号館1階 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
(1) 15:45−16:30
Spectral envelope analyses for sequence data
Solvang Hiroko Kato, Institute of Marine Research, Norway
(2) 16:30−17:30
Distribution of the sum-of-digits function of random integers: a survey
Hsien-Kuei Hwang, Institute of Statistical Science, A
cademia Sinica, Taiwan,
( Cowork with Louis H. Y. Chen and Vytas Zacharovas).
なお、講演終了後、18:00より馬車道でビュッフェ形式の小宴を予定していますの
で、ご参加ください。
------------------------------------------------------------------------------------------
日時:2014年6月25日(水)15:00−17:00
Date: June 25 (Wed), 2014 15:00 — 17:00
場所:早稲田大学理工63号館1階 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
(1) 15:00−16:00
ソルベンシーマージン比率の代替指標と生保破綻の分析
早稲田大学商学研究科 大塚忠義
(2) 16:00−17:00
The Holistic Balance Sheet Approach and Evaluation of Employer
Covenant for Occupational Pensions in Europe
厚生省年金局 清水 信広
なお、講演終了後、17:30より馬車道でビュッフェ形式の小宴を予定していますの
で、ご参加ください。
------------------------------------------------------------------------------------------
日時:2014年5月28日(水)15:00−17:10
Date: May 28 (Wed), 2014 15:00 — 17:00
場所:早稲田大学理工63号館1階 数学応数会議室
Location: Nishi-Waseda Campus, Building 63-1st Floor Meeting Room
(1) 15:00−15:50
データサイエンスのこれまでとこれから
早稲田大学理工学術院 柴田 里程
(2) 16:00−16:30
Asymptotic Theory of Parameter Estimation by a Function Based on
Interpolation Error
早稲田大学理工学研究科 *須籐 慶大
早稲田大学理工学研究科 劉 言
早稲田大学理工学術院 谷口 正信
(3)16:30−17:10
離散時間確率金利モデルの漸近展開と金利派生商品の価格付け
東京理科大学工学部 塩濱敬之
なお、講演終了後、17:30よりビュッフェ形式の小宴を予定していますので、ご参
加ください。
------------------------------------------------------------------------------------------
2014年4月16日(水)15:00−17:00
場所: 早稲田大学理工63号館1階 数学応数会議室
Location: Nishi-Waseda Campus,
Building 63-1st Floor Meeting Room
(1) 15:00−15:30
QTL解析における影響分析
早稲田大学国際教育センター Dou Xiaoling
(2) 15:30−16:10
Default risk analysis with ruin theory
早稲田大学理工学術院 清水泰隆
(3) 16:20−17:00
公的年金運用の改革−確率的なリスク制約概念の導入とその技術的対応について−
年金積立金管理運用独立行政法人(GPIF) 山下 隆
なお、講演終了後、17:
30よりビュッフェ形式の小宴を予定していますので、ご参加ください。
------------------------------------------------------------------------------------------
Waseda International Symposium on “Stable Process, Semimartingale,
Finance & Pension Mathematics”
2014年3月3日ー5日 (March 3ー5, 2014)
場所:
早稲田大学理工55号館S棟2階 Meeting Room 3
Location: Nishi-Waseda Campus,
Building 55S-2th Floor Meeting Room 3
Organizers: Masanobu Taniguchi (Waseda Univ.), Dou Xiaoling (ISM) and
Kenta Hamada (Waseda Univ.)
Waseda University, (map http://www.sci.waseda.ac.jp/eng/access/)
Supported by Kiban (A) (23244011) (M.Taniguchi)
& Government Pension Investment Fund (GPIF), Japan
Program
(* speaker )
March 3, 2014
13:00 - 14:40 : Chaired by X. Dou
13:00 - 13:30
(1) Generalized Periodogram and Its Statistical
Inference for Time Series
Yan Liu (Waseda Univ.)
13:30 - 14:10
(2) Dimension reduction for locally stationary time
series factor models
Junichi Hirukawa (Niigata Univ.)
14:10 - 14:50
(3) Estimation of autocopula with estimating
function approach
Hiroaki Ogata (Waseda Univ.)
Coffee Break
15:10 - 17:20 : Chaired by J.
Hirukawa
15:10 - 15:50
(4) Semiparametric statistics with
infinite-dimensional martingales: Bridges between a stochastic maximal
inequality and Cox’s regression
model
Yoichi Nishiyama (Inst. Statist. Math., Tokyo)
15:50 - 16:30
(5) Parameter change problem for diffusion processes
Ilia Negri (Univ. Bergamo)
16:30 - 17:20
(6) Inference for change point problems for
fractional diffusion processes
B.L.S. Prakasa Rao (Univ. Hyderabad Campus)
March 4, 2014
9:30 - 10:50 : Chaired by T. Mikosch
9:30 - 10:10
(7) Empirical likelihood ratio for symmetric
alpha-stable processes
Fumiya Akashi*, Yan Liu and Masanobu Taniguchi
(Waseda Univ.)
10:10 - 10:50
(8) EM algorithms for estimating the Bernstein
copula
Xiaoling Dou* (Inst. Stat. Math.), Satoshi Kuriki,
Gwo Dong Lin and Donald Richards
Coffee Break
11:00 - 12:30 : Chaired by I. Negri
11:00 - 11:40
(9) LAD-based estimation of locally stable
Ornstein-Uhlenbeck processes
H. Masuda (Kyushu Univ.)
11:40 - 12:30
(10) Nonparametric independence screening and
structural identification for ultra-high dimen- sional longitudinal
data
Ming-Yen Cheng, Toshio Honda* (Hitotsubashi Univ.),
Jialiang Li and Heng Peng
Lunch
13:40 - 15:20 : Chaired by C.
Kluppelberg
13:40 - 14:30
(11) Distributions of the maximum likelihood and
minimum contrast estimators associated with the fractional
Ornstein-Uhlenbeck process
Katsuto Tanaka (Gakusyuin Univ.)
14:30 - 15:20
(12) Extremogram and Ex-Periodogram for heavy-tailed
time series
Thomas Mikosch* (Univ. Copenhagen), Richard A. Davis
(Columbia Univ.) and Yuwei Zhao
Coffee Break
15:40 - 17:20 : Chaired by M.Taniguchi
15:40 - 16:30
(13) Continuous-time GARCH models Claudia
Kluppelberg (Munich Univ. Technology)
16:30 - 17:20
(14) Asymptotic Theory for the Sample Covariance
Matrix of a Heavy-Tailed Multivariate Time Series
Richard A. Davis (Columbia Univ.)
Buffet Style Dinner
18:30 - Basyamichi (63 building 1st floor)
March 5, 2014
10:00 - 12:10 : Chaired by R. Davis
10:00 - 10:40
(15) Asymptotics of Realized Volatility with
Non-Gaussian ARCH(∞) Microstructure Noise
Hiroyuki TANIAI*, T. Usami, N. Suto and M. Taniguchi
(Waseda Univ.)
10:40 - 11:20
(16) Review of Statistical Portfolio Theory
Hiroshi Shiraishi (Jikei Medical Univ.)
11:20 - 12: 10
(17) Bayesian estimation of smoothly mixing
time-varying parameter GARCH models
Cathy W. S. Chen* (Feng Chia Univ), Richard Gerlach
and Edward M. H. Lin
------------------------------------------------------------------------------------------
High Dimensional Statistical Analysis
and Related Topics
2014年1月6日ー7日 (January 6-7, 2014)
場所:
早稲田大学理工63号館1階 数学応数会議室
Location: Waseda
University Building 63-1 Meeting Room
(Supported by (A) 23244011( M.Taniguchi, Waseda Univ. )
理工研プロジェクト研究共催 ( Supported by GPIF )
早稲田理工学術院談話会共催
Program
January 6, 2014
13:30 - 14:15 : Discussion on “ High Dimensional Statistical Analysis “
Chaired by Masanobu Taniguchi (
Waseda Univ. )
14:15 - 15:00
Efficient influence function of coefficient functions in
quantile regression
By Hiroyuki Taniai ( Waseda Univ. )
15:00 - 15:30 Coffee Break
15:30 - 16:15
Locally stationary time series factor models
By Junichi Hirukawa ( Niigata Univ. )
16:15 -17:00
Generalized Least Squares Model Averaging,
Qingfeng Liu ( Otaru University of Commerce ) , Ryo
Okui ( Kyoto Univ. )
and Arihiro Yoshimura ( Kyoto Univ. )
17:30 -
Buffet Style Dinner
January 7, 2014
10:30 - 11:00
Robust spectral estimation in time series analysis
By Yan Liu ( Waseda Univ. )
11:00- 11:30
Nonparametric LAN approach for frequency domain GMM-type hypothesis
testing
By Fumiya Akashi ( Waseda Univ. )
11:30 - 12:15 : General Discussion
12:15 - 13:45 : Lunch
13:45 - 14:45
Testing second order dynamics for autoregressive processes in presence
of time-varying variance.
By Hamdi Raissi ( Univ. Europeenne de
Bretagne, France )
14:45 - 15:00: Coffee Break
15:00- 16:00
Nonparametric estimation of probability density functions for
irregularly observed spatial data
By Zudi Lu ( University of Southampton, U.K. )
16:00- 17:00
The dynamic structure of high-dimensional factor models
By Marco Lippi ( Universit a di Roma "La Sapienza" and
EIEF )
------------------------------------------------------------------------------------------
日時: 2013年10月1日(火) 15:00−17:00
(Oct. 1st, 3:00pm to
5:00pm)
場所:
早稲田大学理工63号館1階 数学応数会議室
(Location: Waseda University, Nishi-Waseda Campus, Room 63-1-Meeting
Room)
講演(1): 15:00--16:00
連続時間モデルに対するポートフォリオ推定問題
( Portfolio Estimation for Continuous Time Models)
白石 博
慈恵医科大学(
Shiraishi, H., Jikei Medical Univ.)
講演(2): 16:00--17:00
Optimal
prediction-based estimating function for COGARCH(1,1) models
Ilia Negri
Department of
Engineering、University of Bergamo (Italy)
(3) Small Buffet Party: 17:30 - 19:30
------------------------------------------------------------------------------------------
2013
年9月3日(September 3,2013)(火) 16:00−17:00
場所:
早稲田大学理工63号館1階 数学応数会議室
(1)
16:00-17:00
講
演題目 : "Likelihood Adaptive Modified Penalties"
講
演者 : Yang Feng, Columbia University, USA.
なお、講演終了後、ビュッフェ形式の小宴を予定していますので、ご参加ください。
---------------------------------------------------------------------------------------
2013年7月30日 (July
30, 2013)(火)15:30−16:30
場所:
早稲田大学理工63号館1階 数学応数会議室
講演題目 : "ANALYSIS
OF ALGORITHMS, RANDOM STRUCTURES, ASYMPTOTICS & APPLICATIONS"
講演者 : Institute of Statistical
Science, Academia Sinica,
Hsien-Kuei Hwang
---------------------------------------------------------------------------------------
2013年7月31日 (July
31, 2013)(水)15:00−17:00
場所:
早稲田大学理工63号館1階 数学応数会議室
(1)
15:00−16:00
Consideration on a serial
correlation
早稲田大学 小方 浩明 ( Ogata, H., Waseda Univ.)
(2)16:00−17:00
Performance of time-varying volatility estimation methods for
portfolio management
GPIF 山下 隆 ( Yamashita, T.,
GPIF)
---------------------------------------------------------------------------------------
2013年6月18日 (June
18, 2013)(火)15:30−17:00
場所:
早稲田大学理工55号館S棟 第3会議室
題目:高次元データにおける統計的推測について
講演者: 矢田和善 筑波大学数理物質系
なお、講演終了後、ビュッフェ形式の小宴を予定していますので、ご参加ください。
---------------------------------------------------------------------------------------
2013年5月21日(May
21, 2013)(火)14:30−17:00
場所:
早稲田大学理工63号館数学・応数会議室( 63-1-Meeting Room )
(1) 14:30−15:15
Empirical likelihood approach for
discriminant analysis
of stable linear processes
早稲田大学理工学研究科 明石 郁哉
(Fumiya Akashi, Waseda Univ.)
(2) 15:15−16:00
Asymptotic moments of
symmetric self-normalized sums
早稲田大学理工学研究科 劉 言
(Yan Liu, Waseda Univ.)
(3) 16:00−17:00
Efficient inference for regression
quantiles via Z-estimation
早稲田大学国際教養学部 谷合 弘行
(Hiroyuki Taniai, Waseda Univ.)
---------------------------------------------------------------------------------------
2013年4月23日(April
23, 2013)(火)15:00−17:00
場所:
早稲田大学理工63号館数学・応数会議室( 63-1-Meeting Room )
(1) 15:00−16:00
Non-regular estimation for time series
早稲田大学 谷口 正信
(2) 16:00−17:00
二変量順序統計量の相関構造とその応用
統計数理研究所 Dou Xiaoling
---------------------------------------------------------------------------------------
2013年3月28日(March
28, 2013)(木)14:00−17:00
場所:
早稲田大学理工63号館数学・応数会議室( 63-1-Meeting Room )
(1) 14:00 - 15:30
CUB models: properties, applications and robustness issues.
Anna Clara Monti ( University of Sannio, Italy).
(2) 15:30 - 17:00
Adjusted profile empirical likelihood.
Thomas J. DiCiccio ( Cornell University, USA ).
---------------------------------------------------------------------------------------
2013年1月29日(Jan.
29, 2013)(火)15:00−17:00
場所:
早稲田大学理工63号館数学・応数会議室( 63-1-Meeting Room )
講演内容:
(1)
15:00−16:00
Alex Petkovic ( Waseda University )
Title : On the local likelihood estimator
(2) 16:00−17:00
広島大学 柳原宏和 ( Yanagihara, H. Hiroshima Univ.)
Title : Theoretical and numerical considerations of properties of the
variable selection in normal multivariate linear regression models by
an information criterion minimization method
---------------------------------------------------------------------------------------
2012年11月28日(Nov.
28, 2012)(水,Wed)15:00−17:00
場所:
早稲田大学理工63号館数学・応数会議室( 63-1-Meeting Room )
講演内容:
(1)
15:00−16:00 :
Recent developments of insurance ruin theory: Gerber-Shiu
Analysis
大阪大学 清水 泰隆 ( Shimizu, Y., Osaka Univ.)
(2)
16:00−17:00 :
Quantile regression estimator for GARCH models
Sangyeol Lee, (Seoul National University)
---------------------------------------------------------------------------------------
2012年10月30日(Oct. 30,
2012)(火)15:00−17:00
場所: 早稲田大学理工63号館数学・応数会議室(
63-1-Meeting Room )
講演内容:
(1) 15:00−16:00 :
Analysis of CL and estimating function estimators for financial
time series models
和歌山大学 天野 友之 ( Amano, T., Wakayama Univ.)
(2)16:00−17:00 :
An estimation techniqe for Jamp-diffusion process using MLE based
jump detection scheme
GPIF 山下 隆 ( Yamashita, T., Government Pension Investment Fund)
---------------------------------------------------------------------------------------
2012年9月25日(September 25, 2012)(火)14:00−17:00
場所: 早稲田大学理工63号館数学・応数会議室( 63-1-Meeting Room )
講演内容:
(1) 14:00−15:00 :
Grapgical Representation of Multiple Regression Analysis.
早稲田大学 石村 友二郎 ( Ishimura, Y., Waseda Univ.)
(2)15:00−16:00 :
いろいろなポートフォリオ推定理論について。
( Various Estimation Theory for Portfolios)
慈恵医科大学 白石 博 ( Shiraishi, H., Jikei Medical Univ.)
(1) 16:00−17:00 :
周辺尤度に対するラプラス近似の漸近誤差とその周辺。
( Asymptotic Error Evaluation of Laplace Approximation for Marginal
Likelihood and Its Related Fields )
高崎経済大学 宮田 庸一( Miyata, Y., Takasaki City Univ. Economicsi)
---------------------------------------------------------------------------------------
日時:2012年4月24日(April 24, 2012)(火)15:00−17:00
場所: 早稲田大学理工63号館数学・応数会議室( 63-1-Meeting Room )
講演内容:
(1) 15:00−16:00 :
Theory & Applications for Statistical Science.
早稲田大学 谷口 正信 ( Taniguchi, M., Waseda Univ.)
(2)16:00−17:00 :
最近の欧州公的年金ポートフォリオ策定手法の紹介 ( Introduction to Recent Methods for
European Government Pension Portfolios)
GPIF 山下 隆 ( Yamashita, T., Government Pension Investment Fund)
---------------------------------------------------------------------------------------
日時:2012年1月24
日 (January 24, 2012)(火)13:00−17:00
場所:早稲田大学理工63
号館1階 数学・応数会議室 (63-1-Meeting Room Dept. Math & Appl. Math.)
講演内容(Program)
(2)13 :
00−14 : 00 :
Various Problems in Financial Time Series Analysis
早稲田大学 長幡 英明 ( Nagahata, H., Waseda Univ.)
早稲田大学 宇佐美 友梨 ( Usami, U., Waseda Univ.)
早稲田大学 鈴木 卓哉 ( Suzuki, T., Waseda Univ.)
早稲田大学 横山 明日希 ( Yokoyama, A.,Waseda Univ.)
早稲田大学 谷口 正信 ( Taniguchi, M., Waseda Univ.)
(2)14 :
00−15 : 00 :
The Detection of Stress Using the Voice Analysis
早稲田大学 石村 友次郎 ( Ishimura, T., Waseda Univ.)
(3)
15:00−16:00 :
Productivity of Service Providers: Microeconometric measurement
in
the case of hair salons
経済産業研究所 小西 葉子 ( Konishi, Y., RIETI)
(3)
16:00−17:00 :
“Soft” Benefit Promises of Occupational Pensions and
Intergenerational Fairness
農業者年金基金 清水 信広 ( Shimizu, N., NFPF )
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日時:2011年12月6日(December 6,
2011)(火)
13 : 30−16 : 30
場所:早稲田大学理工63号館1階 数学・応数会議室
(63-1-Meeting Room Dept. Math & Appl. Math.)
講演内容(Program)
(2)13 : 00−14 : 00 :
Statistical properties for long-horizon investors's portfolio
linking with macroeconomic indices performance
Takashi Yamashita ( Government Pension Investment Fund (GPIF) )
(2)14 : 00−15 : 30 :
A simple model for vast panels of volatilities
David Veredas (Univ. Libre de Bruxelles)
(3) 15:30−17:00 :
Pseudo-Gaussian and Rank-Based Optimal Tests for Random
Individual Effects in Large n Small T Panels
Marc Hallin (Univ. Libre de Bruxelles)
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日時:2011年10月25日(October 25, 2011)(火)15:00−17:00
場所:早稲田大学理工 55S
号館406A( Room 55S-406A)
講演内容(Program)
(1) 15:00−16:00 :
Modeling financial data with multivariate stable distributions.
早稲田大学 小方 浩明 ( Ogata, H., Waseda Univ.)br>
(2)16:00−17:00 :
年金制度の自動安定化メカニズムと世代間の公正(Automatic Stabilization Mechanism and
Intergenerational Equity in Pension System)
農業者年金基金 清水信広( Shimizu, N., National Farmers Pension Fund)
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日時:2011年 9月27日 (Sep 27, 2011)(火)
13 : 30−16 : 30
場所:早稲田大学理工63号館1階 数学・応数会議室 (63-1-Meeting Room Dept. Math &
Appl. Math.)
講演内容
(Program)
(2)13 : 30−14 : 30 :
Asymptotic Efficiency in Dynamic Panel Data Models When Both N
and T are Large
京都大学経済研究所 岩倉 相雄 ( Iwakura, H., Kyoto Univ.)
(2)14 : 30−15 : 30 :
クレーム総額の時系列モデルについて(Time Series Models for Total Claim Amount)
新潟大学自然科学系 蛭川 潤一( Hirukawa, J. Niigata Univ.)
(3) 15:30−16:30
臨床研究で使われる統計解析手法の紹介 (Introduction of statistical methods for
clinical reserch)
第一三共株式会社研究開発本部・データサイエンス部・統計解析グループ:塩境 一仁( Shiosakai, K.,
Daiichi-Sankyo Pharmaceutical Company)
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日時:2011年7月26
日(July 26, 2011)(火)
15:00−16:50
場所:早稲田大学理工
55S
号館406A( Room 55S-406A)
講演内容(Program)
(1)
15:00−15:50 :
GPIF基本ポートフォリオの策定方法 (Formulation Method for GPIF fundamental
portfolios)
山下 隆 (T. Yamashita) ( GPIF )
(2)16:00−16:
50 :
Linear regression with deterministic regressors and unit root in
the variance
Alex Petkovic (Waseda University)
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日時:2011年6月21日(June 21,
2011)(火)
15:00−17:00
場所:早稲田大学理工 55S
号館406A( Room 55S-406A)
講演内容:
(1) 15:00−16:00 :
Semiparametric estimation for diffusion processes:
pseudo-likelihood method and Bays method
統計数理研究所 西山 陽一 ( Nishiyama, Y., Inst. Statist. Math.)
(2)16:10−17:00 :
掛金の経済価値を制御する方法(Economic Values of Contribution Cashflows and
Measures to Bring
the EVs under Control)
農業者年金基金 清水 信広 ( Shimizu, N., National Farmer Pension Fund)
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日時:2011年5月24日(May 24, 2011)(火)
15:00−17:00
場所:早稲田大学理工 55S
号館406A( Room 55S-406A)
講演内容:
(1) 15:00−15:40 :
Statistical Portfolio Estimation Under the Utility Function
Depending on Exogenous Variables and Its Applications
早稲田大学 濱田 健太 ( Hamada, K. (D1), Waseda Univ.)
(2)16:00−16:40 :
運用関係指標(資産運用収益率、賃金上昇率など)の統計的性質( Statistical Properties of Indices
on Working Assets )
GPIF 山下 隆 ( Yamashita, T., Government Pension Investment Fund)
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日時:2011年4月26日(April 26, 2011)(火)13:30−17:00
場所:早稲田大学理工 55S
号館406A( Room 55S-406A)
講演内容:
(1) 13:30−14:15 :
Statistical Estimation of Optimal Portfolios for Dependent
Returns.
早稲田大学 谷口 正信 ( Taniguchi, M., Waseda Univ.)
(2)14:15−15:00 :
Bootstrap Estimation of Optimal Portfolios
慈恵医科大学 白石 博 ( Shiraishi, H., Jikei Medical Univ.)
(2)15:30−16:00 :
最近の公的年金投資の諸問題( Recent Problems for Government Pension Investment)
GPIF 山下 隆 ( Yamashita, T., Government Pension Investment Fund)
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