A dynamic trading rule based on filtered flag pattern recognition for stock market price forecasting
R Arévalo, J García, F Guijarro, A Peris - Expert Systems with Applications, 2017 - Elsevier
In this paper we propose and validate a trading rule based on flag pattern recognition,
incorporating important innovations with respect to the previous research. Firstly, we …
incorporating important innovations with respect to the previous research. Firstly, we …
Effective fuzzy system for qualifying the characteristics of stocks by random trading
Trading strategies can be divided into two categories, ie, those with momentum
characteristic and those that appear contrarian. The characteristics of trading strategies have …
characteristic and those that appear contrarian. The characteristics of trading strategies have …
Hybrid fuzzy neural network to predict price direction in the German DAX-30 index
Intraday trading rules require accurate information about the future short term market
evolution. For that reason, next-day market trend prediction has attracted the attention of …
evolution. For that reason, next-day market trend prediction has attracted the attention of …
Two-stage stock portfolio optimization based on AI-powered price prediction and mean-CVaR models
CH Wang, Y Zeng, J Yuan - Expert Systems with Applications, 2024 - Elsevier
With the advancement of prediction methods in the field of artificial intelligence, accurate
price predictions can effectively support financial portfolio selection. This paper proposes an …
price predictions can effectively support financial portfolio selection. This paper proposes an …
Forecasting fluctuations in the financial index using a recurrent neural network based on price features
YF Lin, TM Huang, WH Chung… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
Profits can be made from a trading strategy where long or short positions are placed in
advance, based on the ability to forecast a future stock price or index, such as the closing or …
advance, based on the ability to forecast a future stock price or index, such as the closing or …
A deep learning integrated framework for predicting stock index price and fluctuation via singular spectrum analysis and particle swarm optimization
CH Wang, J Yuan, Y Zeng, S Lin - Applied Intelligence, 2024 - Springer
Due to the complexity and volatility of stock market trading, there are still some issues in the
existing prediction methods, including the processing of data noise, inexplicable selection of …
existing prediction methods, including the processing of data noise, inexplicable selection of …
An effective approach for obtaining a group trading strategy portfolio using grouping genetic algorithm
To determine an appropriate trading time for buying or selling stocks is always a difficult
task. The common way to deal with it is using trading strategies formed by technical or …
task. The common way to deal with it is using trading strategies formed by technical or …
A novel approach of option portfolio construction using the Kelly criterion
Money management is one of the most important issues in financial trading. Many skills of
money managements are based on the Kelly criterion, which is a theoretical optimization of …
money managements are based on the Kelly criterion, which is a theoretical optimization of …
Subsequence dynamic time warping for charting: Bullish and bearish class predictions for NYSE stocks
PE Tsinaslanidis - Expert Systems with Applications, 2018 - Elsevier
Advanced pattern recognition algorithms have been historically designed in order to mitigate
the problem of subjectivity that characterises technical analysis (also known as 'charting') …
the problem of subjectivity that characterises technical analysis (also known as 'charting') …
An effective approach for the diverse group stock portfolio optimization using grouping genetic algorithm
Finding useful portfolios that could be a portfolio of trading strategy or a stock portfolio from
financial datasets is always an attractive research topic due to the nature of financial …
financial datasets is always an attractive research topic due to the nature of financial …