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政大機構典藏 > 社會科學學院 > 經濟學系 > 會議論文 > Item 140.119/23057

Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/23057

Title:	Are Efficient Markets Really Efficient?: Can Financial Econometric Tests Convince Machine-Learning People?
Authors:	陳樹衡;T.-W. Kuo Chen,Shu-Heng
Date:	2004
Issue Date:	2009-01-09 11:26:22 (UTC+8)
Abstract:	Using Quinlan’s Cubist, this paper examines whether there is a consistent, interpretation of the efficient market hypothesis between financial econometrics and machine learning. In particular, we ask whether machine learning can be useful only in the case when the market is not efficient. Based on the forecasting performance of Cubist in our artificial returns, some evidences seems to support this consistent interpretation. However, there are a few cases whereby Cubist can beat the random walk even though the series is independent. As a result, we do not consider that the evidence is strong enough to convince one to give up his reliance on machine learning even though the efficient market hypothesis is sustained.
Relation:	Computational Intelligence in Economics and Finance Advanced Information Processing 2004, pp 288-296
Data Type:	conference
Appears in Collections:	[經濟學系] 會議論文

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