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Waiting time distributions in financial markets

机译:金融市场的等待时间分布

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We study waiting time distributions for data representing two completely different financial markets that have dramatically different characteristics. The first are data for the Irish market during the 19th century over the period 1850 to 1854. A total of 10 stocks out of a database of 60 are examined. The second database is for Japanese yen currency fluctuations during the latter part of the 20th century (1989-1992). The Irish stock activity was recorded on a daily basis and activity was characterised by waiting times that varied form one day to a few months. The Japanese yen data was recorded every minute over 24 hour periods and the waiting times varied from a minute to a an hour or so. For both data sets, the waiting time distributions exhibit power law tails. The results for Irish daily data can be easily interpreted using the model of a continuous time random walk first proposed by Montroll and applied recently to some financial data by Mainardi, Scalas and colleagues. Yen data show a quite different behaviour. For large waiting times, the Irish data exhibit a cut off; the Yen data exhibit two humps that could arise as result of major trading centres in the World.
机译:我们研究数据的等待时间分布,这些数据代表具有完全不同特征的两个完全不同的金融市场。首先是19世纪1850至1854年间爱尔兰市场的数据。在60个数据库中,总共检查了10个股票。第二个数据库是20世纪后期(1989-1992年)日元汇率波动的数据库。每天记录爱尔兰的股票活动,活动的特点是等待时间从一天到几个月不等。在24小时内每分钟记录一次日元数据,等待时间从一分钟到一个小时左右不等。对于这两个数据集,等待时间分布都显示出幂律尾部。使用Montroll最初提出的连续时间随机游走模型,可以很容易地解释爱尔兰每日数据的结果,最近该模型被Mainardi,Scalas及其同事应用于一些财务数据。日元数据显示出完全不同的行为。对于较长的等待时间,爱尔兰数据显示出临界值;日元数据显示,由于世界主要贸易中心的影响,可能会出现两个驼峰。

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