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A formal approach to candlestick pattern classification in financial time series
9 references·2 citing·42 second hop
A formal approach to candlestick pattern classification in financial time series (2019)A formal approach to candlestick pattern …Computational Finance: An Introductory Course with R (2014)Computational Finance: An Int…Profitable candlestick trading strategies—The evidence from a new perspective (2012)Profitable candlestick tradin…Intelligent stock trading system based on improved technical analysis and Echo State Network (2011)Intelligent stock trading sys…Pattern discovery of fuzzy time series for financial prediction (2006)Pattern discovery of fuzzy ti…Expert system for predicting stock market timing using a candlestick chart (1999)Expert system for predicting …Trading on the Edge: Neural, Genetic, and Fuzzy Systems for Chaotic Financial Markets (1994)Trading on the Edge: Neural, …Japanese candlestick charting techniques (1991)Japanese candlestick charting…Stock price pattern recognition-a recurrent neural network approach (1990)Stock price pattern recogniti…Fuzzy Sets, Uncertainty, and Information (1990)Fuzzy Sets, Uncertainty, and …Stock price crash prediction based on multimodal data machine learning models (2024)Stock price crash prediction …Forecasting Stock Market Prices Using Machine Learning and Deep Learning Models: A Systematic Review, Performance Analysis and Discussion of Implications (2023)Forecasting Stock Market Pric…Fractal Market Analysis: Applying Chaos Theory to Investment and Economics (1994)Encyclopedia of information science and technology (2005)A hybrid approach based on neural networks and genetic algorithms for detecting temporal patterns in stock markets (2006)Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends (2019)Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process (2021)Time series forecasting based on echo state network and empirical wavelet transformation (2021)Judgment under Uncertainty: Heuristics and Biases (1974)Judgement under Uncertainty: Heuristics and Biases (1983)Noise Trader Risk in Financial Markets (1990)Wrapper ANFIS-ICA method to do stock market timing and feature selection on the basis of Japanese Candlestick (2015)Fuzzy modeling of stock trading with fuzzy candlesticks (2017)Shortlisting machine learning-based stock trading recommendations using candlestick pattern recognition (2023)Forecasting enrollments with fuzzy time series — Part I (1993)Forecasting enrollments based on fuzzy time series (1996)Support vector machine with adaptive parameters in financial time series forecasting (2003)Fuzzy time-series based on Fibonacci sequence for stock price forecasting (2007)Improvement of Auto-Regressive Integrated Moving Average models using Fuzzy logic and Artificial Neural Networks (ANNs) (2008)Multivariate fuzzy forecasting based on fuzzy time series and automatic clustering techniques (2011)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Evaluating multiple classifiers for stock price direction prediction (2015)Applications of deep learning in stock market prediction: Recent progress (2021)SMP-DL: a novel stock market prediction approach based on deep learning for effective trend forecasting (2023)Deep Learning in Finance: A Survey of Applications and Techniques (2024)Deep learning for financial forecasting: A review of recent trends (2025)Opaque financial reports, R2, and crash risk☆ (2009)When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks (2011)A five-factor asset pricing model (2014)Designing a neural network for forecasting financial and economic time series (1996)Forecasting stock market movement direction with support vector machine (2004)Financial time series forecasting using independent component analysis and support vector regression (2009)An adaptive stock index trading decision support system (2016)Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data (2019)Machine Learning Stock Market Prediction Studies: Review and Research Directions (2020)Financial time series forecasting using support vector machines (2003)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Deep Direct Reinforcement Learning for Financial Signal Representation and Trading (2016)Appropriate choice of aggregation operators in fuzzy decision support systems (2001)How to build aggregation operators from data (2003)Fuzzy inferior ratio method for multiple attribute decision making problems (2014)WHAT DO WE KNOW ABOUT THE PROFITABILITY OF TECHNICAL ANALYSIS? (2007)Technical analysis: An asset allocation perspective on the use of moving averages☆ (2009)Forecasting the Equity Risk Premium: The Role of Technical Indicators (2011)
this work references cited by second hop

References

  • 1990Fuzzy Sets, Uncertainty, and Information439 cited
  • 1994Trading on the Edge: Neural, Genetic, and Fuzzy Systems for Chaotic Financial Markets261 cited
  • 1990Stock price pattern recognition-a recurrent neural network approach255 cited
  • 2006Pattern discovery of fuzzy time series for financial prediction180 cited
  • 1999Expert system for predicting stock market timing using a candlestick chart165 cited
  • 1991Japanese candlestick charting techniques139 cited
  • 2011Intelligent stock trading system based on improved technical analysis and Echo State Network102 cited
  • 2012Profitable candlestick trading strategies—The evidence from a new perspective61 cited
  • 2014Computational Finance: An Introductory Course with R23 cited

Cited by

  • 2023Forecasting Stock Market Prices Using Machine Learning and Deep Learning Models: A Systematic Review, Performance Analysis and Discussion of Implications341 cited
  • 2024Stock price crash prediction based on multimodal data machine learning models24 cited

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