Next Article in Journal
Global Stability Analysis of Fractional-Order Quaternion-Valued Bidirectional Associative Memory Neural Networks
Next Article in Special Issue
Stability Assessment of Stochastic Differential-Algebraic Systems via Lyapunov Exponents with an Application to Power Systems
Previous Article in Journal
A Class of Quantum Briot–Bouquet Differential Equations with Complex Coefficients
Previous Article in Special Issue
State Vector Identification of Hybrid Model of a Gas Turbine by Real-Time Kalman Filter
Open AccessArticle

Predictive Power of Adaptive Candlestick Patterns in Forex Market. Eurusd Case

Conselleria d’Educació, Cultura i Esport, Avda. de Campanar, 32, ES-46015 València, Spain
Mathematics 2020, 8(5), 802; https://doi.org/10.3390/math8050802
Received: 26 March 2020 / Revised: 27 April 2020 / Accepted: 8 May 2020 / Published: 14 May 2020
The Efficient Market Hypothesis (EMH) states that all available information is immediately reflected in the price of any asset or financial instrument, so that it is impossible to predict its future values, making it follow a pure stochastic process. Among all financial markets, FOREX is usually addressed as one of the most efficient. This paper tests the efficiency of the EURUSD pair taking only into consideration the price itself. A novel categorical classification, based on adaptive criteria, of all possible single candlestick patterns is presented. The predictive power of candlestick patterns is evaluated from a statistical inference approach, where the mean of the average returns of the strategies in out-of-sample historical data is taken as sample statistic. No net positive average returns are found in any case after taking into account transaction costs. More complex candlestick patterns are considered feeding supervised learning systems with the information of past bars. No edge is found even in the case of considering the information of up to 24 preceding candlesticks. View Full-Text
Keywords: FOREX; efficient market hypothesis; adaptive candlestick patterns; decision trees; random forest; adaboost; finance FOREX; efficient market hypothesis; adaptive candlestick patterns; decision trees; random forest; adaboost; finance
Show Figures

Figure 1

MDPI and ACS Style

Orquín-Serrano, I. Predictive Power of Adaptive Candlestick Patterns in Forex Market. Eurusd Case. Mathematics 2020, 8, 802.

AMA Style

Orquín-Serrano I. Predictive Power of Adaptive Candlestick Patterns in Forex Market. Eurusd Case. Mathematics. 2020; 8(5):802.

Chicago/Turabian Style

Orquín-Serrano, Ismael. 2020. "Predictive Power of Adaptive Candlestick Patterns in Forex Market. Eurusd Case" Mathematics 8, no. 5: 802.

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop