Parallel computing strategies in the analysis of the inhibiting effect of price limits on futures prices

被引:2
|
作者
Balakrishnan, Narayanaswamy [1 ]
Gopinatha, Jakadeesan [2 ]
Goswami, Dhrubajyoti [2 ]
Shanker, Latha [3 ]
机构
[1] McMaster Univ, Dept Math & Stat, Hamilton, ON L8S 4K1, Canada
[2] Concordia Univ, Dept Comp Sci & Software Engn, Montreal, PQ H3G 1M8, Canada
[3] Concordia Univ, Dept Finance, John Molson Sch Business, Montreal, PQ H3G 1M8, Canada
来源
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE | 2014年 / 26卷 / 09期
关键词
parallel computing; finance; futures pricing; daily price limits; load balancing; IMPLEMENTATION; FINANCE; MODEL;
D O I
10.1002/cpe.2907
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In futures markets with price limits, trading halts are triggered by limit hits. Limit hits are rarely observed, perhaps because traders avoid bid-ask quotes that cause them. If this explanation is true, futures prices would cluster in a narrow region close to the limits. We test this empirically for currency futures contracts and find results consistent with the explanation. The tests require calculations of all combinations of a computationally intensive time series, which are extremely time consuming on a sequential machine and hence limit the practicality of the analysis. Consequently, we investigate parallel computing strategies in partitioning the datasets and solving them in parallel on a high-end Beowulf cluster. We discuss two different partitioning strategies of the given datasets on the cluster and elaborate the results. Copyright (c) 2012 John Wiley & Sons, Ltd.
引用
收藏
页码:1666 / 1678
页数:13
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