Forecasting metals returns : a Bayesian decision theoretic approach / by David Halperin
- Bib ID:
- 5232716
- Format:
- Book
- Author:
- Halperin, David
- Online Version:
- Electronic version
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- Description:
-
- [Nedlands, W.A.] : University of Western Australia, Economics, 2010
- 30 p. : ill., charts ; 21 cm.
- Series:
- Discussion paper (University of Western Australia. Business School. Economics) ; 10.24.
- Summary:
-
Turning points in commodity returns are important for decisions of policy makers, commodity producers and consumers reliant on medium term outcomes. However, forecasting of turning points has been a neglected feature of forecasting, especially in commodity markets. This paper forecasts turning points in metals price returns using Bayesian Decision Theory. The method produces a probabilistic statement about the belief of a turning point occurring in the next period which, combined with a decision rule based on a loss function generates optimal turning point forecasts. This method produces positive results in forecasting turning points in metals returns, with the simple linear models investigated producing more accurate turning point forecasts than naive models across a number of different evaluation methods for the general case and for the specific example of a producing firm.
- Notes:
-
- Includes bibliographical refrerences (p. 27)
- Also available in an electronic version via the Internet. Address as at 30/05/2011: http://ideas.repec.org/p/uwa/wpaper/10-24.html.
- Subject:
- Other authors/contributors:
- University of Western Australia. Business School. Economics
- Copyright:
-
In Copyright
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Copyright status was determined using the following information:
- Material type:
- Literary Dramatic Musical
- Published status:
- Published
- Publication date:
- 2010
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