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postgraduate thesis: The statistical properties and effectiveness of filter trading rule

TitleThe statistical properties and effectiveness of filter trading rule
Authors
Issue Date2013
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Xin, L. [辛聆]. (2013). The statistical properties and effectiveness of filter trading rule. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5016249
AbstractFilter trading rule is a technical trading strategy that was very popular amongst practitioners and has been used a lot for testing market efficiency. It has been shown that the filter trading rule is mathematically equivalent to the CUSUM quality control test as both are based on change point detection theory via sequential probability ratio tests (SPRT). To study the operating characteristics of the filter trading rule, many results from the CUSUM literature can be applied. However, some interesting operating characteristics of a technical trading rule such as expected profit per day may not be relevant when put into a quality control setting. In this thesis, we derive formulae for computing these operating characteristics. It is well known that just like any other technical trading rule, the filter trading rule is not effective when the asset price follows a random walk. In this thesis, we studied the statistical properties and effectiveness of the filter trading rule under different asset price models including Markov regime switching model and conditional heteroskedasticity model. The properties of the filter trading rule considered include the waiting time for the first signal in filter trading, the duration of a long or a short cycle in filter trading, the profit return derived from a long or a short cycle and the unit time return of long term filter trading. Built on the above results, we consider the problem of optimizing the performance of a filter trading rule by choosing a suitable filter size. For filter trading rule under the conditional heteroskedasticity model, the change point detection methods lead to a new technical trading rule called generalized filter trading rule in this thesis. The generalized filter trading rule is shown to have a better performance over the ordinary filter trading rule when it is applied to the trading of the Hang Seng Index futures contract. Finally, we have applied the filter trading rule to intraday trading on high frequency Hang Seng Index futures data.
DegreeDoctor of Philosophy
SubjectStocks - Prices - Statistical methods
Investments - Statistical methods
Dept/ProgramStatistics and Actuarial Science
Persistent Identifierhttp://hdl.handle.net/10722/196092

 

DC FieldValueLanguage
dc.contributor.authorXin, Ling-
dc.contributor.author辛聆-
dc.date.accessioned2014-03-28T07:05:57Z-
dc.date.available2014-03-28T07:05:57Z-
dc.date.issued2013-
dc.identifier.citationXin, L. [辛聆]. (2013). The statistical properties and effectiveness of filter trading rule. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5016249-
dc.identifier.urihttp://hdl.handle.net/10722/196092-
dc.description.abstractFilter trading rule is a technical trading strategy that was very popular amongst practitioners and has been used a lot for testing market efficiency. It has been shown that the filter trading rule is mathematically equivalent to the CUSUM quality control test as both are based on change point detection theory via sequential probability ratio tests (SPRT). To study the operating characteristics of the filter trading rule, many results from the CUSUM literature can be applied. However, some interesting operating characteristics of a technical trading rule such as expected profit per day may not be relevant when put into a quality control setting. In this thesis, we derive formulae for computing these operating characteristics. It is well known that just like any other technical trading rule, the filter trading rule is not effective when the asset price follows a random walk. In this thesis, we studied the statistical properties and effectiveness of the filter trading rule under different asset price models including Markov regime switching model and conditional heteroskedasticity model. The properties of the filter trading rule considered include the waiting time for the first signal in filter trading, the duration of a long or a short cycle in filter trading, the profit return derived from a long or a short cycle and the unit time return of long term filter trading. Built on the above results, we consider the problem of optimizing the performance of a filter trading rule by choosing a suitable filter size. For filter trading rule under the conditional heteroskedasticity model, the change point detection methods lead to a new technical trading rule called generalized filter trading rule in this thesis. The generalized filter trading rule is shown to have a better performance over the ordinary filter trading rule when it is applied to the trading of the Hang Seng Index futures contract. Finally, we have applied the filter trading rule to intraday trading on high frequency Hang Seng Index futures data.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subject.lcshStocks - Prices - Statistical methods-
dc.subject.lcshInvestments - Statistical methods-
dc.titleThe statistical properties and effectiveness of filter trading rule-
dc.typePG_Thesis-
dc.identifier.hkulb5016249-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesislevelDoctoral-
dc.description.thesisdisciplineStatistics and Actuarial Science-
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.5353/th_b5016249-
dc.date.hkucongregation2013-

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