The extension of trading hours to provide more trading opportunities and improve price efficiency has increasingly been discussed. However, currently, there is limited trading activity during the stock market's extended extended-hours trading session. Thus, we shou ld examine whether the extension of trading hours is still effective for creating more trading opportunity and price efficiency even if there are few market participants during the extended session. For this study, we build an agent agent-based market model base d on that of Brock and Hommes (1998) and analyze the effect of extending trading hours. We find that although extending trading hours could increase daily trading volume, it could distort price formation and trade opportunity if market participants are lim ited during the extended extended-hours session. Specifically, the extension could result in more concentrated trading in the opening session, wider divergence between market prices and the fundamental value of stocks, and higher return volatility (especially at th e open).

株式市場において，注文を公開せずに注文を付き合わせる，ダーク・プールという取引市場が普及してきている．ダーク・プールは市場の安定化につながると言われている一方，ダーク・プールは価格決定を行わない市場であるため，市場全体の価格発見機能が低下し，市場全体の効率性が失われるという批判もある．本研究では１つのリット市場(注文情報が公開されている通常の市場) と１つのダーク・プールが存在する人工市場モデル(マルチ・エージェント・シミュレーション) を用いて，ダーク・プールの普及が市場を非効率にするのかどうかシミュレーションを行い分析した．その結果，ダーク・プールはビット・アスク・バウンスを低減させ市場を効率化することが分かった．さらに，ある程度までのダーク・プールの普及はリット市場へ出される成行注文(マーケット・インパクトがある注文) が減少し，流動性を供給する注文が相対的に多くなることによって，市場を効率化することが分かった．一方で，普及のしすぎはファンダメンタル価格への収斂も妨げ市場は非効率になることも分かった．普及しすぎの水準は，ダーク・プールの取引量が，リット市場の取引量より大きいときである可能性を指摘した．さらに，日本株式市場における実データとの比較を行い，シミュレーション結果と整合的な結果が得られることを示した．

The Japan regulators have decided to redraft their risk management guidelines for Investment Trusts in Japan. There are some methods of market risk measurement for Investment Trusts that is addressed under Basel Banking rules as well as is adopting some of the core principles of UCITS (Undertaking for Collective Investments in Transferable Securities). The purpose of this research is to discuss mainly to understand the meaning of recent rule changes and to review the development of VaR (Value at Risk) as a risk measurement tool in financial industry.

We constructed a basic order order-book model which is based on the Maslov model and includes some empirical results such as distributions of order volume. Although this basic model successfully reproduces power law distributions of price changes, the market price greatly oscillates and the Hurst exponent, which indicates randomness of price fluctuation, of this model is much smaller than that of real data. In order to resolve this problem, we revised the basic order order-book model by adding the effect that the selection probability of order types (i.e. market order, limit orde r and cancel) depends on the bid bid-ask spread. Our revised model still reproduces power law distributions of price changes and the Hurst exponent is improved.

Recent financial crises have shown the importance of determining the directionality of the in uence between financial assets in order to identify the origin of market unstabilities. Here, we analyze the correlation between Japan's Nikkei stock average index (Nikkei 225) and other financial markets by introducing a volatility-constrained correlation metrics. The asymmetric feature of the metrics reveals which asset is more in uential than the other. As a result, this method allows us to unveil the directionality of correlation effect, which could not be observed from the standard correlation analysis. Furthemore, we present a theoretical model that reproduces the results observed in empirical analysis.

In this study, we studied large-scale price movements in the exchange market caused by investors' collective behaviors, and focused on the phenomenon created by local investors af- fecting each other and producing large-scale price uctuations as a group, which we denote as swarm behaviors. We think one of the factors of large-scale price movement is connected with certain swarm behaviors of investors. First, we present a basic stochastic order-book model in the continuous double auction mechanism. Next, we incorporate a follower type of investors' swarm behavior in the basic stochastic order-book model. Our study shows a characteristic called \fat tail" is seen in the data obtained from our model that incorporates the investors' swarm behaviors. The result demonstrated that one of the reasons the trend following of price occurs is that orders temporarily swarm on the order book in accordance with past price trends.

In this study, we proposed a new method for extracting factors and related stocks which affect individual stocks. We combined t wo text text-mining methods which are CPR method for news articles and TF-IDF for summary of financial statements statements. We showed how stocks are connected through factors in each terms.

I attended 5th World Congress on Social Simulation Simulation, held at Sao Paulo on November 4th to 7th and talk ed about our re cent results on the analysis of the impact of shadow banking on systemic risk. On this occasion, I present a report on the miscellaneous research topics at the conference, our research topic details, and the discussion on the issues of the current agent simulation technique techniques.