Skip to main content

Stable classes of technical trading rules

Buy Article:

$53.17 plus tax (Refund Policy)


Technical analysis includes a huge variety of trading rules. This fact has always been a serious hindrance to the large number of market efficiency studies implemented either to demonstrate the profitability of market-beating systems or to deny their operational feasibility. For evident reasons it is practically impossible and theoretically weak to systematically analyse the entire body of all trading rules. We therefore propose a novel method to form natural classes of trading rules which are found to be robust to changing market scenarios. In particular, groups are formed adopting a similarity measure based on the investing signals of the trading rules. Our clustering methodology adopts a Markov chain bootstrapping technique to generate differentiated scenarios preserving volume and price joint distributional features. An application is developed on a sample of 674 trading rules. Results show that six groups (here identified as trading styles) are sufficient to explain the large portion of the investing signals variance. We also suggest applications of our results to fund performance measurement and the analysis of financial markets.

Document Type: Research Article


Affiliations: Dipartimento Metodi Quantitativi, Universita degli Studi di Brescia, Contrada Santa Chiara, 50 - 25122 Brescia, BS, Italy

Publication date: May 1, 2011

More about this publication?

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more