An Analysis of Some Effects of Rating Information using an Artificial Market

Shun Katsumi, Hajime Shimao, Noboru Nishiyama

Research output: Contribution to journalArticlepeer-review

Abstract

Standard & Poor' s (S & P) downgraded American government bonds from AAA to AA+ last year. The effects of the downgrade on financial markets have been studied in financial engineering, economics and computational finance, but not in agent-based simulation studies. In this paper, we investigate the effect of the rating system (e.g.: S & P) on asset price fluctuations in the artificial market, which is the agent-based simulation model of the financial market. The rating information is defined as a discrete version of the fundamental value. Four strategies : the noise trader, the fundamentalist, the trend predictor, and the contrarian trader, were assumed in previous studies of the artificial market, plus we assume a new agent called “rating user” which uses the rating value, defined as the discrete value of the fundamental value of an asset. We investigate if the rating user makes the artificial market unstable. First, the simulation results show that kurtosis of an asset price return in the market, without fundamentalists, is higher than without rating users. This suggests the usage of rating information makes the artificial market unstable. The simulation outcomes also suggest volatility continuity of asset price return is stronger in the market without fundamentalists than without rating users. Second, we investigate how two parameters, the update interval and rating length, which control the rating value, makes the market stable. The simulation outcomes show that both standard deviation of asset price return and kurtosis of asset price return becomes smaller as the update interval increases. The standard deviation gets larger and kurtosis of that gets larger with the increasing length of rating. These results imply that the rating information should be updated at short intervals and the length of rating should be moderate to make the artificial market stable. keywords: raing-information, financial market, artificial market, agent-based simulation.

Original languageEnglish (US)
Pages (from-to)384-390
Number of pages7
JournalTransactions of the Japanese Society for Artificial Intelligence
Volume27
Issue number6
DOIs
StatePublished - 2012

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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