dc.contributor.authorZou, Xi
dc.date.accessioned2014-11-26T01:29:54Z
dc.date.available2014-11-26T01:29:54Z
dc.date.copyright2014en_US
dc.date.issued2014
dc.identifier.citationZou, X. (2014, March). Copula-based pairs trading in local markets. Presented at Discover URECA @ NTU poster exhibition and competition, Nanyang Technological University, Singapore.en_US
dc.identifier.urihttp://hdl.handle.net/10220/24241
dc.description.abstractPairs trading is a widely accepted quantitative trading strategy originated from Wall Street. The intrinsic idea of pairs trading is to identify a pair of stocks whose prices move together in their history. Subsequently, long/short positions are constructed when the stock prices are undervalued/overvalued relative to their counterparty. The profitability of this trading strategy depends on the assumption of mean-reverting property, which states that stock prices will eventually return to their equilibrium positions if they deviate from each other. Distance method is the most commonly implemented pairs trading strategy by traders and hedge funds. However, this approach, which can be seen as a standard linear correlation analysis, is only able to fully describe the dependency structure between stocks under the assumption of multivariate normal returns. To overcome this limitation, we propose a new pairs trading strategy using copula modelling technique. Copula allows separate estimation of the marginal distributions of stock returns as well as their joint dependency structure. Thus, the proposed new strategy, which is based on the estimated optimal dependency structure and marginal distributions, can identify relative undervalued or overvalued positions with more accuracy and confidence. Hence, it is deemed to generate more trading opportunities and profits. [2nd Award]en_US
dc.language.isoenen_US
dc.rights© 2014 The Author(s).en_US
dc.subjectCopula
dc.subjectPairs Trading
dc.titleCopula-based pairs trading in local marketsen_US
dc.typeStudent Research Poster
dc.contributor.schoolNanyang Business Schoolen_US
dc.contributor.supervisorWu Yuanen_US
dc.description.degreeStudent Research Posteren_US


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