Isao Yagi

Regulations' effectiveness for market turbulence by large erroneous orders using multi agent simulation

We built an artificial market model and investigated the impact of large erroneous orders on price formations. Comparing the case of consented large erroneous orders in the short term with that of continuous small erroneous orders in the long term, if amounts of orders are the same, we found that the orders induced almost the same price fall range. We also analyzed effects of price variation limits for erroneous orders and found that price variation limits that employ a limitation term shorter than the time erroneous orders exist effectively prevent large price fluctuations. We also investigated effects of up-tick rules adopting the trigger method that the Japan Financial Services Agency adopted on November 2013.

Effects of Price Regulations and Dark Pools on Financial Market Stability: An Investigation by Multiagent Simulations

We built an artificial market model and investigated the impact of large erroneous orders on financial market price formations. Comparing the case of consented large erroneous orders in the short term with that of continuous small erroneous orders in the long term, if amounts of orders are the same, we found that the orders induced almost the same price fall range. We also analysed effects of price variation limits for erroneous orders and found that price variation limits that employ a limitation term shorter than the time erroneous orders exist effectively prevent large price fluctuations. We also investigated effects of up-tick rules, adopting the trigger method that the Japan Financial Services Agency adopted in November 2013.

A study on the reversal mechanism for large stock price declines using artificial markets

Deterioration in the fundamentals of firms due to scandals or disasters causes declines in their stock prices. We empirically know that stock prices rebound after they largely fall. In this paper, this trend is called the reversal phenomenon. There has been some preceding research on this issue; however, little has been explained about market mechanisms such as the market pricing mechanism responsible for the reversal in large declines in stock prices. We reproduced the reversal phenomenon in an artificial market with a degree of variation in expected prices, and not with the overreaction hypothesis, and found that a call market, which is a non-continuous double auction, imposes a condition where the market becomes non-efficient.

A Study on the Effectiveness of Short-Selling Regulation in View of Regulation Period Using Artificial Markets

Since the subprime mortgage crisis in the United Sates, stock markets around the world have crashed, revealing their instability. To stem the decline in stock prices, short-selling regulations have been implemented in many markets. However, their effectiveness remains unclear. In this paper, we discussed the effectiveness of short-selling regulation which was invoked temporarily after the market satisfies a regulation condition using an artificial market. First, we proposed an artificial market in which short-selling was regulated after the market satisfied the regulation condition. Next, we observed price variations in the markets in which the durations of short-selling regulation were different and discussed the bubble mechanism of them. Then, we observed the correlation between market stability and regulation periods and it was found that the longer the regulation period was, the more instable markets were. Therefore, we have found short-selling regulation had the property that it not only stemed the decline in the prices but also increased the prices excessively and market instability increased with increasing regulation period. Finally, we determined performances of each agent type in the market in which the regulation was invoked.

A Study on the Market Impact of Short-Selling Regulation Using Artificial Markets

Since the subprime mortgage crisis in the United Sates, stock markets around the world have crashed, revealing their instability. To stem the decline in stock prices, short-selling regulations have been implemented in many markets. However, their effectiveness remains unclear. In this paper, we discuss the effectiveness of short-selling regulation using artificial markets. An artificial market is an agent-based model of financial markets. We constructed an artificial market that allows short-selling and an artificial market with short-selling regulation and have observed the stock prices in both of these markets. We found that the market in which short-selling was allowed was more stable than the market with short-selling regulation, and a bubble emerged in the regulated market. We evaluated the values of assets of agents who used three trading strategies, specifically, these agents were fundamentalists, chartists, and noise traders. The fundamentalists had the best performance among the three types of agents. Finally, we observe the price variations when the market price affects the theoretical price.

Applying Data Mining Techniques to Assess Steel Plant Operation Conditions

The improvement in the operation of melting the scrap metal in electric arc furnace, to make various types of steel products, requires complex expertise. This work discusses data mining approach to this problem. We flattened the time series data of the whole operation into the form which is suitable for conventional data mining methods. This paper describes the methodology for transformation of the time series data and discusses the possible applicability of different classification methods in this domain.