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Predicting Stock Price Trend Using MACD Optimized by Historical Volatility
12 references·2 citing·53 second hopsampled
Predicting Stock Price Trend Using MACD Optimized by Historical Volatility (2018)Predicting Stock Price Trend Using MACD O…Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets (2018)Stock Market Prediction on Hi…Wavelet Neural Network Prediction Method of Stock Price Trend Based on Rough Set Attribute Reduction (2017)Wavelet Neural Network Predic…Minute-ahead stock price forecasting based on singular spectrum analysis and support vector regression (2017)Minute-ahead stock price fore…Forecasting price movements using technical indicators: Investigating the impact of varying input window length (2017)Forecasting price movements u…Maximum and minimum stock price forecasting of Brazilian power distribution companies based on artificial neural networks (2015)Maximum and minimum stock pri…Intraday stock price forecasting based on variational mode decomposition (2015)Intraday stock price forecast…Value and Momentum Everywhere (2013)Value and Momentum EverywhereForecasting stock index price based on M-factors fuzzy time series and particle swarm optimization (2013)Forecasting stock index price…An adaptive network-based fuzzy inference system (ANFIS) for the forecasting: The case of close price indices (2013)An adaptive network-based fuz…Time Series Momentum (2011)Time Series MomentumForecasting stock indices with back propagation neural network (2011)Forecasting stock indices wit…A combination of hidden Markov model and fuzzy model for stock market forecasting (2009)A combination of hidden Marko…Predicting NEPSE index price using deep learning models (2022)Predicting NEPSE index price …Improving MACD Technical Analysis by Optimizing Parameters and Modifying Trading Rules: Evidence from the Japanese Nikkei 225 Futures Market (2021)Improving MACD Technical Anal…Fuzzy sets (1965)Fuzzy sets (1996)An Adaptive Network-Based Fuzzy Inference System (ANFIS) for the prediction of stock market return: The case of the Istanbul Stock Exchange (2010)Developing an approach to evaluate stocks by forecasting effective features with data mining methods (2014)Product sustainability assessment for product life cycle (2018)Modelling near-real-time order arrival demand in e-commerce context: a machine learning predictive methodology (2020)Forecasting enrollments with fuzzy time series — Part I (1993)Improved v -Support vector regression model based on variable selection and brain storm optimization for stock price forecasting (2016)FQTSFM: A fuzzy-quantum time series forecasting model (2021)Particle swarm optimization and intuitionistic fuzzy set-based novel method for fuzzy time series forecasting (2021)Genetic algorithms approach to feature discretization in artificial neural networks for the prediction of stock price index (2000)Application of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index (2002)Time series forecasting using a hybrid ARIMA and neural network model (2003)Forecasting daily stock market return using dimensionality reduction (2016)Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach (2018)Forecasting stock prices with a feature fusion LSTM-CNN model using different representations of the same data (2019)Financial Forecasting Using Support Vector Machines (2001)Stock market forecasting using hidden Markov model: a new approach (2005)A fusion model of HMM, ANN and GA for stock market forecasting (2006)A hybrid fuzzy intelligent agent-based system for stock price prediction (2012)Incorporating Markov decision process on genetic algorithms to formulate trading strategies for stock markets (2016)Scientometric review and analysis of recent approaches to stock market forecasting: Two decades survey (2022)The Cross-Section of Expected Stock Returns (1992)Common risk factors in the returns on stocks and bonds (1993)On Persistence in Mutual Fund Performance (1997)… and the Cross-Section of Expected Returns (2015)Does Academic Research Destroy Stock Return Predictability? (2015)The Behavior of Stock-Market Prices (1965)Mutual Fund Performance (1966)Financial time series forecasting using support vector machines (2003)A novel data-driven stock price trend prediction system (2017)Combining wavelet decomposition with machine learning to forecast gold returns (2019)Deep Learning-based Integrated Framework for stock price movement prediction (2022)Economic prediction using neural networks: the case of IBM daily stock returns (1988)Stock market prediction system with modular neural networks (1990)Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction (2014)The two-stage machine learning ensemble models for stock price prediction by combining mode decomposition, extreme learning machine and improved harmony search algorithm (2020)Using Deep Learning for price prediction by exploiting stationary limit order book features (2020)Application of Artificial Intelligence in Stock Market Forecasting: A Critique, Review, and Research Agenda (2021)Forecasting stock market movement direction with support vector machine (2004)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Modeling financial time-series with generative adversarial networks (2019)Stock Market Forecasting Using Deep Learning and Technical Analysis: A Systematic Review (2020)Forecasting Stock Market Prices Using Machine Learning and Deep Learning Models: A Systematic Review, Performance Analysis and Discussion of Implications (2023)Judgment under Uncertainty: Heuristics and Biases (1974)Judgment under Uncertainty: Heuristics and Biases (1975)Forecasting the Equity Risk Premium: The Role of Technical Indicators (2014)Investor Sentiment Aligned: A Powerful Predictor of Stock Returns (2014)Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control. (1978)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Hybrid Variational Mode Decomposition and evolutionary robust kernel extreme learning machine for stock price and movement prediction on daily basis (2018)Advantages of direct input-to-output connections in neural networks: The Elman network for stock index forecasting (2020)
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References

  • 2013Value and Momentum Everywhere2,225 cited
  • 2011Time Series Momentum1,470 cited
  • 2011Forecasting stock indices with back propagation neural network487 cited
  • 2018Stock Market Prediction on High-Frequency Data Using Generative Adversarial Nets262 cited
  • 2017Forecasting price movements using technical indicators: Investigating the impact of varying input window length190 cited
  • 2015Maximum and minimum stock price forecasting of Brazilian power distribution companies based on artificial neural networks165 cited
  • 2009A combination of hidden Markov model and fuzzy model for stock market forecasting115 cited
  • 2017Wavelet Neural Network Prediction Method of Stock Price Trend Based on Rough Set Attribute Reduction109 cited
  • 2013An adaptive network-based fuzzy inference system (ANFIS) for the forecasting: The case of close price indices103 cited
  • 2013Forecasting stock index price based on M-factors fuzzy time series and particle swarm optimization101 cited
  • 2015Intraday stock price forecasting based on variational mode decomposition98 cited
  • 2017Minute-ahead stock price forecasting based on singular spectrum analysis and support vector regression92 cited

Cited by

  • 2022Predicting NEPSE index price using deep learning models37 cited
  • 2021Improving MACD Technical Analysis by Optimizing Parameters and Modifying Trading Rules: Evidence from the Japanese Nikkei 225 Futures Market

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29 cited