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Tytuł artykułu
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Języki publikacji
Abstrakty
Various trading strategies have been proposed that use estimates of the Hurst coefficient, which is an indicator of long-range dependence, for the calculation of buy and sell signals. This paper introduces frequency-domain tests for long-range dependence which do, in contrast to conventional procedures, not assume that the number of used periodogram ordinates grow with the length of the time series. These tests are applied to series of gold price returns and stock index returns in a rolling analysis. The results suggest that there is no long-range dependence, indicating that trading strategies based on fractal dynamics have no sound statistical basis. (original abstract)
Rocznik
Tom
Numer
Strony
93--106
Opis fizyczny
Twórcy
autor
- University of Vienna, Austria
autor
- University of Vienna, Austria
Bibliografia
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- [16] R Core Team, (2017), R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria. URL https://www. R-project.org/.
- [17] Reisen V., Abraham B., Lopes S., (2001), Estimation of parameters in ARFIMA processes: a simulation study, Communications in Statistics - Simulation and Computation 30, 787-803.
- [18] Reschenhofer E., (1997), Generalization of the Kolmogorov-Smirnov test, Computational Statistics & Data Analysis 24, 433-441.
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Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000171561581