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Characterizing Complexity and Self-Similarity Based on Fractal and Entropy Analyses for Stock Market Forecast Modelling
16 references·5 citing·42 second hop
Characterizing Complexity and Self-Similarity Based on Fractal and Entropy Analyses for Stock Market Forecast Modelling (2019)Characterizing Complexity and Self-Simila…Literature review: Machine learning techniques applied to financial market prediction (2019)Literature review: Machine le…CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)CNNpred: CNN-based stock mark…Stock price prediction using support vector regression on daily and up to the minute prices (2018)Stock price prediction using …Global stock market investment strategies based on financial network indicators using machine learning techniques (2018)Global stock market investmen…Stock market index prediction using artificial neural network (2016)Stock market index prediction…An adaptive stock index trading decision support system (2016)An adaptive stock index tradi…Predicting stock market index using fusion of machine learning techniques (2014)Predicting stock market index…Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Predicting stock and stock pr…Rényi’s information transfer between financial time series (2012)Rényi’s information transfer …Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Predicting direction of stock…Determination of weights for ultimate cross efficiency using Shannon entropy (2010)Determination of weights for …A multiple-kernel support vector regression approach for stock market price forecasting (2010)A multiple-kernel support vec…Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network (2008)Stock market prediction of S&…Ranking efficiency for emerging markets (2004)Ranking efficiency for emergi…Using neural networks for forecasting volatility of S&P 500 Index futures prices (2003)Using neural networks for for…Fractional Brownian Motions, Fractional Noises and Applications (1968)Fractional Brownian Motions, …Predicting financial distress in high-dimensional imbalanced datasets: a multi-heterogeneous self-paced ensemble learning framework (2025)Predicting financial distress…Forecasting the overnight return direction of stock market index combining global market indices: A multiple-branch deep learning approach (2022)Forecasting the overnight ret…Renyi entropy and mutual information measurement of market expectations and investor fear during the COVID-19 pandemic (2020)Renyi entropy and mutual info…Modeling and Forecasting of Innovative, Scientific and Technical Activity Indicators Under Unstable Economic Situation in the Country: Case of Ukraine (2020)Modeling and Forecasting of I…A NOVEL R/S FRACTAL ANALYSIS AND WAVELET ENTROPY CHARACTERIZATION APPROACH FOR ROBUST FORECASTING BASED ON SELF-SIMILAR TIME SERIES MODELING (2020)A NOVEL R/S FRACTAL ANALYSIS …Financial time series forecasting using support vector machines (2003)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Forecasting stock market movement direction with support vector machine (2004)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)Applications of deep learning in stock market prediction: Recent progress (2021)Generalized autoregressive conditional heteroskedasticity (1986)Sentiment analysis on social media for stock movement prediction (2015)Computational Intelligence and Financial Markets: A Survey and Future Directions (2016)A systematic review of fundamental and technical analysis of stock market predictions (2019)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Evaluating multiple classifiers for stock price direction prediction (2015)The Typical Spectral Shape of an Economic Variable (1966)AN INTRODUCTION TO LONG‐MEMORY TIME SERIES MODELS AND FRACTIONAL DIFFERENCING (1980)THE ESTIMATION AND APPLICATION OF LONG MEMORY TIME SERIES MODELS (1983)Empirical properties of asset returns: stylized facts and statistical issues (2001)Measuring the efficiency of decision making units (1978)Data Envelopment Analysis: Theory, Methodology, and Applications (1994)Data Envelopment Analysis: A Comprehensive Text with Models, Applications, References and DEA-Solver Software (1999)An integrated fuzzy clustering cooperative game data envelopment analysis model with application in hospital efficiency (2018)Supplier sustainability performance evaluation and selection: A framework and methodology (2018)Exploring the Role of Agricultural Services in Production Efficiency in Chinese Agriculture: A Case of the Socialized Agricultural Service System (2022)Application of neural networks to an emerging financial market: forecasting and trading the Taiwan Stock Index (2002)A neural network approach for credit risk evaluation (2007)Using artificial neural network models in stock market index prediction (2011)Modelling carbon emission intensity: Application of artificial neural network (2019)Systematic analysis and review of stock market prediction techniques (2019)The applications of artificial neural networks, support vector machines, and long–short term memory for stock market prediction (2021)The Efficient Market Hypothesis and Its Critics (2003)Fine-tuned support vector regression model for stock predictions (2021)Survey of feature selection and extraction techniques for stock market prediction (2023)Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation (1982)Theory building with big data-driven research – Moving away from the “What” towards the “Why” (2020)Prediction of stock price direction using a hybrid GA-XGBoost algorithm with a three-stage feature engineering process (2021)Machine learning techniques and data for stock market forecasting: A literature review (2022)PORTFOLIO SELECTION* (1952)Optimal Versus Naive Diversification: How Inefficient is the 1/ N Portfolio Strategy? (2007)Deep learning with long short-term memory networks for financial market predictions (2017)Deep Learning for Stock Market Prediction (2020)A Survey of Forex and Stock Price Prediction Using Deep Learning (2021)Integration of genetic fuzzy systems and artificial neural networks for stock price forecasting (2010)Stock index forecasting based on a hybrid model (2011)Carbon price forecasting with a novel hybrid ARIMA and least squares support vector machines methodology (2012)
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References

  • 1968Fractional Brownian Motions, Fractional Noises and Applications7,658 cited
  • 2014Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques1,139 cited
  • 2010Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange880 cited
  • 2019CNNpred: CNN-based stock market prediction using a diverse set of variables643 cited
  • 2014Predicting stock market index using fusion of machine learning techniques608 cited
  • 2019Literature review: Machine learning techniques applied to financial market prediction560 cited
  • 2008Stock market prediction of S&P 500 via combination of improved BCO approach and BP neural network423 cited
  • 2016Stock market index prediction using artificial neural network396 cited
  • 2018Stock price prediction using support vector regression on daily and up to the minute prices330 cited
  • 2010Determination of weights for ultimate cross efficiency using Shannon entropy321 cited
  • 2010A multiple-kernel support vector regression approach for stock market price forecasting255 cited
  • 2004Ranking efficiency for emerging markets209 cited
  • 2003Using neural networks for forecasting volatility of S&P 500 Index futures prices195 cited
  • 2018Global stock market investment strategies based on financial network indicators using machine learning techniques

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173 cited
  • 2012Rényi’s information transfer between financial time series159 cited
  • 2016An adaptive stock index trading decision support system136 cited
  • Cited by

    • 2020Renyi entropy and mutual information measurement of market expectations and investor fear during the COVID-19 pandemic70 cited
    • 2022Forecasting the overnight return direction of stock market index combining global market indices: A multiple-branch deep learning approach44 cited
    • 2020A NOVEL R/S FRACTAL ANALYSIS AND WAVELET ENTROPY CHARACTERIZATION APPROACH FOR ROBUST FORECASTING BASED ON SELF-SIMILAR TIME SERIES MODELING41 cited
    • 2025Predicting financial distress in high-dimensional imbalanced datasets: a multi-heterogeneous self-paced ensemble learning framework30 cited
    • 2020Modeling and Forecasting of Innovative, Scientific and Technical Activity Indicators Under Unstable Economic Situation in the Country: Case of Ukraine17 cited