The fractal nature of financial data has been investigated through literature. The aim of this paper is to use the information given by the detection of the fractal measure of data in order to provide support for trading decisions when dealing with technical analysis signals that can be used to trigger buy/sell orders. Trendlines are considered as a case study.
The Hurst’s exponent in technical analysis signals / Rotundo, Giulia. - STAMPA. - (2006), pp. 121-125. (Intervento presentato al convegno The Third Nikkei Econophysics Research Workshop and Symposium tenutosi a Tokyo).
The Hurst’s exponent in technical analysis signals
Giulia Rotundo
Investigation
2006
Abstract
The fractal nature of financial data has been investigated through literature. The aim of this paper is to use the information given by the detection of the fractal measure of data in order to provide support for trading decisions when dealing with technical analysis signals that can be used to trigger buy/sell orders. Trendlines are considered as a case study.File allegati a questo prodotto
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