Asymptotic Inference for Performance Fees and the Predictability of Asset Returns
In this paper we provide analytical, simulation, and empirical evidence on a test of equal economic value from competing predictive models of asset returns. We define economic value using the concept of a performance fee - the amount an investor would be willing to pay to have access to an alternative predictive model that is used to make investment decisions. We establish that this fee can be asymptotically normal under modest assumptions. Monte Carlo evidence shows that our test can be accurately sized in reasonably large samples. We apply the proposed test to predictions of the US equity premium.
|Date of creation:||2012|
|Date of revision:||01 Jul 2016|
|Contact details of provider:|| Postal: P.O. Box 442, St. Louis, MO 63166|
Web page: http://www.stlouisfed.org/
More information through EDIRC
|Order Information:|| Email: |
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Norman Swanson & Valentina Corradi, 2006.
"Nonparametric Bootstrap Procedures for Predictive Inference Based on Recursive Estimation Schemes,"
Departmental Working Papers
200618, Rutgers University, Department of Economics.
- Valentina Corradi & Norman R. Swanson, 2007. "Nonparametric Bootstrap Procedures For Predictive Inference Based On Recursive Estimation Schemes," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(1), pages 67-109, 02.
- Allan Timmermann & Andrew Patton, 2004.
"Properties of Optimal Forecasts under Asymmetric Loss and Nonlinearity,"
wp04-05, Warwick Business School, Finance Group.
- Patton, Andrew J. & Timmermann, Allan, 2007. "Properties of optimal forecasts under asymmetric loss and nonlinearity," Journal of Econometrics, Elsevier, vol. 140(2), pages 884-918, October.
When requesting a correction, please mention this item's handle: RePEc:fip:fedlwp:2012-049. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Anna Xiao)
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.