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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.

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SUMMARYWe 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.We also investigated whether dark pools that never provide any order books stabilize markets or not using the model including one lit market, which provides all order books to investors, and one dark pool. We found that markets become more stable as the dark pool is increasingly used. We also found that using the dark pool more reduces the market impacts. However, if other investors' usage rates of dark pools become too large, investors must use the dark pool more than other investors to avoid market impacts. When a tick size of a lit market is larger, dark pools are more useful to avoid market impacts. These results suggest that dark pools stabilize markets when the usage rate is under some threshold and negatively affect the market when the usage rate is over that threshold. Our simulation results suggest the threshold might be much larger than the usage rate in present real financial markets.This study is the first to discuss whether or not several concrete and actually adoptable regulations, including those that have never been employed (e.g. price variation limits with various parameters), could prevent large fluctuations of market prices, including those beyond our experience, using artificial market simulations, and to discuss quantitatively how spreading of dark pools beyond our experience could affect market price formations using the artificial market simulations. In short, this study is the first study to comprehensively discuss how regulations and financial systems beyond our experience could affect price formations using the artificial market simulations.

We built an artificial market model and compared effects of price variation limits, short selling regulations and up-tick rules. In the case without the regulations, the price fell to below a fundamental value when an economic crush occurred. On the other hand, in the case with the regulations, this overshooting did not occur. However, the short selling regulation and the up-tick rule caused the trading prices to be higher than the fundamental value. We also surveyed an adequate limitation price range and an adequate limitation time span for the price variation limit and found a parameters’ condition of the price variation limit to prevent the over-shorts. We also showed the limitation price range should be bigger than a volatility calculated by the limitation time span.