[arsc-ml 54] ARSC-mlからのお知らせ

[nhosoe ＠ grips.ac.jp]

□名前:細江宣裕
□所属:政策研究大学院大学
□会員:会員
□お知らせの内容:研究会関連
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□内容
　:各位
　お世話になります。
以下の通り第7回ポリシー・モデリング・ワークショップを開催いたします。
今回が2015年度最終回です。
ふるってご参加ください。

http://www3.grips.ac.jp/~nhosoe/pmw/index.html


政策研究大学院大学・細江

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第7回

日時: 2016年2月27日(土)

場所: 政策研究大学院大学 4階 会議室4B

地図: http://www.grips.ac.jp/jp/docs/map.pdf

14:00-15:50

講演者: 高橋孝明 氏 (東京大学)

題目: A tale of two cities: Urban spatial structure and mode of transportation

概要: This paper discusses the interdependence of the spatial structure
of a city and the transport mode used there to obtain two types of
equilibria. One is the “auto city equilibrium” at which
workers,distributed over a city thinly, use an automobile for their
commutes. The other is the “rapid transit city equilibrium” at which
rapid transit services are provided for the commutes of workers,who
are distributed densely. We have derived and characterized the
conditions for each type of equilibrium. Furthermore, the possibility
of multiple equilibria has been studied.

16:10-18:00

講演者: 楡井誠 氏 (一橋大学)

題目: Beauty Contests and Fat Tails in Financial Markets

概要: This study seeks to explain the emergence of fat-tailed
distributions of trading volumes and asset returns in financial
markets. We use a rational expectations form of the herding model. In
the model, traders infer other traders' private signals regarding the
value of an asset by observing their aggregate buying actions. The
rational expectations equilibrium outcome entails an upward sloping
demand curve. This is because the information contained in others'
signals is more encouraging than is reflected in the incremental
price. That is, there are strategic complementarities in informed
traders' buying actions. In this environment, we show that equilibrium
trading volumes and asset returns follow fat-tailed distributions
without making any parametric assumptions on private signals.
Specifically, we demonstrate that the trading volume follows a
power-law distribution when the number of traders is large and the
signal is noisy. Furthermore, we provide simulation results to show
that our model successfully reproduces the observed distributions of
daily stock returns.

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