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However, unlike that work we provide a formal theoretical justification for the validity of these tests and present some new general theoretical results. These results take advantage of the link between the algorithms of Blake and Kapetanios (2000, 2003a, 2003b) and boosting. We carry out a Monte Carlo study of the properties of the new tests and find that they have very good power performance. A simplified implementation of boosting is found to have desirable properties and small computational cost. An empirical application to the S&amp;P 500 constituents illustrates the usefulness of our new test.<\/jats:p>","DOI":"10.1017\/s0266466609990612","type":"journal-article","created":{"date-parts":[[2010,2,17]],"date-time":"2010-02-17T06:40:05Z","timestamp":1266388805000},"page":"1363-1397","source":"Crossref","is-referenced-by-count":7,"title":["TESTS OF THE MARTINGALE DIFFERENCE HYPOTHESIS USING BOOSTING AND RBF NEURAL NETWORK APPROXIMATIONS"],"prefix":"10.1017","volume":"26","author":[{"given":"George","family":"Kapetanios","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew P.","family":"Blake","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"56","published-online":{"date-parts":[[2010,2,17]]},"reference":[{"key":"S0266466609990612_ref34","unstructured":"Poskitt D.S. 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