In this paper, we tested the effect of the rating system (e.g. S&P) on the price fluctuation of the market by an agent-based model. The information of rating is defined as a discrete version of fundamental value. In addition to the investment strategies that are modeled in earlier studies (noise trader, fundamentalist, trend predictor, and contrarian), we modeled an agent called "rating user ", who uses rating information as an index of fundamental value of an asset. The result indicates that the market becomes unstable if investors make use of the rating rather than fundamental value itself.

The purpose of our work was to examine which index is effective for reducing the overfitting. The purpose of this paper is to report on our work. For the purpose of our work, we constructed an automatic trading model using Genetic programming. We simulated the model using real foreign exchange market data to compare the asset based index and Sharpe Ratio based index. As a result, the case using Sharpe Ratio based index showed higher performances than the case using asset based index.

This study presents a computer simulation model to analyze the transmission of knock-on defaults in a bank credit network. Simulations quantify the impact which the topology of the network, the net worth of banks, and the capital surcharge on big banks impose on the number of knock-on defaults of banks.

We investigate characteristics of firms that lose market value in the post-downgrade period by securities analyst. We found higher pre-downgrade volatility is strongly associated with the negative return in the post-downgrade period. Among high volatility firms, small capitalization stocks and stocks with inferior sentiment are more likely to underperform.