|授業科目名||Artificial Intelligent Economics|
|履修条件||Requirements to join in this lecture are not specified.|
|科目の目的・到達目標||We use a platform called "U-Mart system" in order to study Artificial Intelligent Market. This AI market simulator in essence is actually the same as the existing index futures trading at Osaka Stock Exchange (OSE). I t is noted that the idea of U-Mart preceded the actual one. This simulator at is origin equipped with a hybrid transaction of human and algorithmic agents. The latter can imitate a so-called high frequency transaction (HFT) by the acceleration experiment. So U-Mart is a progressive simulator to imitate the reality.
First of all, we should state our U-Mar project. Originally in 1998 U-Mart Project started as V-Mart(Virtual Mart). Now it however becomes re-nominated U-Mart. The U-Mart Project has published an English textbook (Shiozawa et. al. 2008) as one of Springer Series on Agent Based Social Systems in Spring 2008. The development of the U-Mart system during these 10 years rather was mainly engineers-driven. Now the U-Mart system is internationally recognized as a good platform for AI markets. Our project has now marked Version 4 which could be compatible with spot and futures market as well as batch and double auction.
Our U-Mart Lectures consists of two parts: one is this class. The other is the class for experiment, or training program. Both lectures normally are integrated into a single Aims and Scope of U-Mart lectures. So you are recommended to join into both classes of Artificial Intelligent Economics and Artificial Intelligent Market Experiment.
|授業の概要||The U-Mart System is an artificial intelligent market system to implement a virtual futures market with reference to the actual stock price index arbitrarily chosen, by the use of agent-based simulation techniques. This system, mutatis mutandis, contains a spot market trading as a special case. It is also noteworthy to point out two outstanding features of the U-Mart system. First of all, any agent, either machine or human, does not presume a certain personal rational demand function in advance. Secondly, this system adopts a hybrid approach in a sense that a human agent can always join in the machine agent gaming setting. The latter is a technological feature, a new network innovation of artificial intelligent market system. The former is featured by an alternative approach to the neoclassical method.|
|授業計画||This class will refer to the theories of the market mechanism or auction of the financial market. In particular, U-Mart simulator imitates the fundamental profile of Tokyo Stock Exchange (TSE) as well as Osaka Stock Exchange(OSE). Now TSE and OSE are integrated into Japan Exchange Group. We will learn two methods of dealing: Itayose (Batch Auction) and Zaraba (Continuous Double Auction ). the institutional settings in TSE is also exposited. Moreover, you will learn the agent based simulation in general on which the U-Mart simulator is based.
1. Introductory Guidance of AI market
2. (Prof. Yoshihiro Nakajima, Osaka City University) Introduction to the U-Mart System
3. (Prof. Yusuke Koyama, Shibaura Institute of Technology) Institution of Futures Market
4. (Prof. Kazuhisa Taniguchi, Kinki University) Market and pricing
5. (Prof. Naoki Mori, Osaka Prefectural University) Elementary Introduction of JAVA programming
6. (Prof. Yoshihiro Nakajima) Random Walk and Time Series Analysis of Prices
7. A Short Tour to Tokyo Stock Exchange
8. A Short Tour to AI Laboratory of Tokyo Institute of Technology
9. (Prof. Hajime Kita, Kyoto University) Review on the Standard Agent Set of the U-Mart System
10. (Prof. Yoshihiro Nakajima )Phase Transition and Power Law Distribution
11. (Prof. Hiroshi Deguchi,Tokyo Institute of Technology) A New Application of Gaming Simulation
12. (Prof. Takashi Yamada, Yamaguchi University) The Analysis of Price Time Series
13. (Prof. Naoki Mori, Osaka Prefectural University) JAVA Programming of U-Mart Machine Agent
14. (Prof. Takao Terano, Tokyo Institute of Technology) A New Application of Agent Base Simulation
15. Summing up
|評価方法||Two ways for grade the credit:
1. Do a paper on the given subjects.
2. Days attended
|テキスト・参考文献等||Y. Shiozawa, Y. Nakajima, H. Matsui, Y. Koyama, K. Taniguchi, and F. Hashimoto, Artificial Market Experiments with the U-Mart System, Springer ABSS Series Vol. 4, 2008, Springer-Verlag;
Kita, Hajime, Taniguchi, Kazuhisa, Nakajima, Yoshihiro (Eds.) Realistic Simulation of Financial Markets: Analyzing Market Behaviors by the Third Mode of Science, Springer Evolutionary Economics and Social Complexity Science, Vol. 4, forthcoming, 2017
|授業外の学習活動||You will be allocated the original materials each opportunities. After each lecture, you are obliged to check the materials. It is also recommended to read the textbooks for U-Mart.|