Evaluation and ranking of market forecasters

Bailey, DH; Borwein, JM; Salehipour, A; López de Prado, M

Evaluation and ranking of market forecasters

Bailey, DH Borwein, JM Salehipour, A López de Prado, M

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Publisher:: Joim
Publication Type:: Journal Article
Citation:: Journal of Investment Management, 2018, 16 (2), pp. 47 - 64
Issue Date:: 2018-05-01

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Field	Value	Language
dc.contributor.author	Bailey, DH	en_US
dc.contributor.author	Borwein, JM	en_US
dc.contributor.author	Salehipour, A	en_US
dc.contributor.author	López de Prado, M	en_US
dc.date.issued	2018-05-01	en_US
dc.identifier.citation	Journal of Investment Management, 2018, 16 (2), pp. 47 - 64	en_US
dc.identifier.issn	1545-9144	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133429
dc.description.abstract	Many investors rely on market experts and forecasters when making investment decisions, such as when to buy or sell securities. Ranking and grading market forecasters provides investors with metrics on which they may choose forecasters with the best record of accuracy for their particular market exposure. This study develops a novel ranking methodology to rank the market forecaster. In particular, we distinguish forecasts by their specificity, rather than considering all predictions and forecasts equally important, and we also analyze the impact of the number of forecasts made by a particular forecaster.We have applied our methodology on a dataset including 6627 forecasts made by 68 forecasters.	en_US
dc.publisher	Joim	en_US
dc.relation.ispartof	Journal of Investment Management	en_US
dc.title	Evaluation and ranking of market forecasters	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	16	en_US
utslib.for	1502 Banking, Finance and Investment	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
utslib.copyright.status	closed_access
pubs.consider-herdc	false	en_US
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	16	en_US

Abstract:

Many investors rely on market experts and forecasters when making investment decisions, such as when to buy or sell securities. Ranking and grading market forecasters provides investors with metrics on which they may choose forecasters with the best record of accuracy for their particular market exposure. This study develops a novel ranking methodology to rank the market forecaster. In particular, we distinguish forecasts by their specificity, rather than considering all predictions and forecasts equally important, and we also analyze the impact of the number of forecasts made by a particular forecaster.We have applied our methodology on a dataset including 6627 forecasts made by 68 forecasters.

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http://hdl.handle.net/10453/133429