RT Journal Article
SR Electronic
T1 Performance Measurements for Machine-Learning Trading Systems
JF The Journal of Trading
FD Institutional Investor Journals
SP 5
OP 16
DO 10.3905/jot.2015.10.4.005
VO 10
IS 4
A1 Dror Parnes
YR 2015
UL https://pm-research.com/content/10/4/5.abstract
AB This study presents several insightful performance measurements for machine-learning trading systems. Machine-learning trading platforms are presumed to operate in a continuous time domain, whereas their learning configurations prompt recurring yet bounded improvements over time. The study provides practical estimation guidelines for the relevant parameters and further illustrates the functionality of the proposed scheme through some conjectural examples. The recommended performance measurements aim to help internal auditors of trading departments and regulatory institutions to better track errors at these automated systems.TOPICS: Big data/machine learning, performance measurement