RT Journal Article
SR Electronic
T1 Gains and Losses Revisited: Skill Detection and Similarity Assessment
JF The Journal of Financial Data Science
FD Institutional Investor Journals
SP 39
OP 71
DO 10.3905/jfds.2022.1.105
VO 4
IS 4
A1 Sid Browne
YR 2022
UL https://pm-research.com/content/4/4/39.abstract
AB The article develops an analytical framework that enables investors who use gain- and loss-based performance measures to evaluate and compare investment strategies or managers and to do so in a more precise manner that accounts for statistical uncertainty and sampling error. In particular, the article develops tests for detection of timing skill and sizing skill for individual strategies as well as tests to compare similarity across competing strategies or between different periods (e.g., backtest and live). Some of these tests are exact and therefore relevant for small samples or track records. The article illustrates the methodology throughout by applying these results to a suite of systematic strategy indexes.