Discussion of “The supraview of return predictive signals”

Discussion of “The supraview of return predictive signals” Rev Account Stud (2013) 18:731–733 DOI 10.1007/s11142-013-9237-8 Discussion of ‘‘The supraview of return predictive signals’’ Peter Algert Published online: 31 July 2013 Springer Science+Business Media New York 2013 JEL Classification G12  G14 Green, Hand and Zhang have collected the most extensive database to date on return predictive signals (RPS) research results. They assert a number of findings, but three are most relevant. The first is that RPS discovery is continuing at an undiminished pace. This is good news for both practitioners and academics interested in the field. The second is the discussion of academic ‘‘n-factor’’ models for risk control and what the standard should be for determining the significance of future RPS. The third is the general finding that stock returns are either ‘‘pervasively inefficient’’ or that many more priced factors exist than had previously been understood. This note discusses the first two briefly and then focuses on the findings on the returns to RPS strategies. The authors document that the number of new RPS discovered each year has not diminished over time, nor has their in-sample Sharpe ratio. To use a resources analogy, the ocean either has a lot of fish in it, or technology is more http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Accounting Studies Springer Journals

Discussion of “The supraview of return predictive signals”

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Publisher
Springer US
Copyright
Copyright © 2013 by Springer Science+Business Media New York
Subject
Economics / Management Science; Accounting/Auditing; Finance/Investment/Banking; Public Finance & Economics
ISSN
1380-6653
eISSN
1573-7136
D.O.I.
10.1007/s11142-013-9237-8
Publisher site
See Article on Publisher Site

Abstract

Rev Account Stud (2013) 18:731–733 DOI 10.1007/s11142-013-9237-8 Discussion of ‘‘The supraview of return predictive signals’’ Peter Algert Published online: 31 July 2013 Springer Science+Business Media New York 2013 JEL Classification G12  G14 Green, Hand and Zhang have collected the most extensive database to date on return predictive signals (RPS) research results. They assert a number of findings, but three are most relevant. The first is that RPS discovery is continuing at an undiminished pace. This is good news for both practitioners and academics interested in the field. The second is the discussion of academic ‘‘n-factor’’ models for risk control and what the standard should be for determining the significance of future RPS. The third is the general finding that stock returns are either ‘‘pervasively inefficient’’ or that many more priced factors exist than had previously been understood. This note discusses the first two briefly and then focuses on the findings on the returns to RPS strategies. The authors document that the number of new RPS discovered each year has not diminished over time, nor has their in-sample Sharpe ratio. To use a resources analogy, the ocean either has a lot of fish in it, or technology is more

Journal

Review of Accounting StudiesSpringer Journals

Published: Jul 31, 2013

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