SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Using Volume Weighted Support Vector Machines with walk forward testing and feature selection for the purpose of creating stock trading strategy
7 references·16 citing·53 second hop
Using Volume Weighted Support Vector Machines with walk forward testing and feature selection for the purpose of creating stock trading strategy (2014)Using Volume Weighted Support Vector Mach…A hybrid stock selection model using genetic algorithms and support vector regression (2011)A hybrid stock selection mode…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…A method for automatic stock trading combining technical analysis and nearest neighbor classification (2010)A method for automatic stock …Using support vector machine with a hybrid feature selection method to the stock trend prediction (2009)Using support vector machine …Intelligent technical analysis based equivolume charting for stock trading using neural networks (2006)Intelligent technical analysi…Modified support vector machines in financial time series forecasting (2002)Modified support vector machi…Time series forecasting using backpropagation neural networks (1991)Time series forecasting using…The Use of Predictive Analytics in Finance (2022)The Use of Predictive Analyti…Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach (2022)Multi-level impacts of climat…Event prediction within directional change framework using a CNN-LSTM model (2022)Event prediction within direc…Asian stock markets closing index forecast based on secondary decomposition, multi-factor analysis and attention-based LSTM model (2022)Asian stock markets closing i…Stock trading rule discovery with double deep Q-network (2021)Stock trading rule discovery …Stock Market Prediction with Gaussian Naïve Bayes Machine Learning Algorithm (2021)Stock Market Prediction with …Feature selection and deep neural networks for stock price direction forecasting using technical analysis indicators (2021)Feature selection and deep ne…A stock selection algorithm hybridizing grey wolf optimizer and support vector regression (2021)A stock selection algorithm h…A review of machine learning experiments in equity investment decision-making: why most published research findings do not live up to their promise in real life (2021)A review of machine learning …Prediction-Based Portfolio Optimization Models Using Deep Neural Networks (2020)Prediction-Based Portfolio Op…Ensemble of machine learning algorithms for cryptocurrency investment with different data resampling methods (2020)Ensemble of machine learning …Comparing the effectiveness of deep feedforward neural networks and shallow architectures for predicting stock price indices (2019)Comparing the effectiveness o…An Empirical Study of Machine Learning Algorithms for Stock Daily Trading Strategy (2019)An Empirical Study of Machine…Integrating principle component analysis and weighted support vector machine for stock trading signals prediction (2018)Integrating principle compone…Stock market trend prediction using dynamical Bayesian factor graph (2015)Stock market trend prediction…Quantifying StockTwits semantic terms’ trading behavior in financial markets: An effective application of decision tree algorithms (2015)Quantifying StockTwits semant…Application of support vector machines in financial time series forecasting (2001)Financial time series forecasting using support vector machines (2003)Forecasting stock market movement direction with support vector machine (2004)Portfolio formation with preselection using deep learning from long-term financial data (2019)Stock Market Forecasting Using Computational Intelligence: A Survey (2020)A survey on machine learning models for financial time series forecasting (2022)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)Deep learning networks for stock market analysis and prediction: Methodology, data representations, and case studies (2017)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Applications of deep learning in stock market prediction: Recent progress (2021)Efficient Capital Markets: A Review of Theory and Empirical Work (1970)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Support vector machine with adaptive parameters in financial time series forecasting (2003)Classification of intraday S&P500 returns with a Random Forest (2018)Technical analysis strategy optimization using a machine learning approach in stock market indices (2021)Stock market prediction system with modular neural networks (1990)A Nonparametric Approach to Pricing and Hedging Derivative Securities Via Learning Networks (1994)Introduction to financial forecasting (1996)SVR with hybrid chaotic genetic algorithms for tourism demand forecasting (2010)Online portfolio selection (2014)Time series forecasting for nonlinear and non-stationary processes: a review and comparative study (2015)Techniques of Financial Analysis. (1963)A new two-stage hybrid approach of credit risk in banking industry (2008)Pairs selection and outranking: An application to the S&P 100 index (2008)Pairs trading and outranking: The multi-step-ahead forecasting case (2010)A Random Walk Down Wall Street (1973)Simple Technical Trading Rules and the Stochastic Properties of Stock Returns (1992)Price Momentum and Trading Volume (2000)CAST: Using neural networks to improve trading systems based on technical analysis by means of the RSI financial indicator (2011)An intelligent short term stock trading fuzzy system for assisting investors in portfolio management (2015)CNN-LSTM Neural Network Model for Quantitative Strategy Analysis in Stock Markets (2017)Efficient Analytic Approximation of American Option Values (1987)Stock price prediction using DEEP learning algorithm and its comparison with machine learning algorithms (2019)A novel graph convolutional feature based convolutional neural network for stock trend prediction (2020)Prediction of cryptocurrency returns using machine learning (2020)PORTFOLIO SELECTION* (1952)Mean-Absolute Deviation Portfolio Optimization Model and Its Applications to Tokyo Stock Market (1991)Deep learning with long short-term memory networks for financial market predictions (2017)Interpretable stock price forecasting model using genetic algorithm-machine learning regressions and best feature subset selection (2022)Deep Learning for Financial Time Series Prediction: A State-of-the-Art Review of Standalone and Hybrid Models (2023)Harnessing a Hybrid CNN-LSTM Model for Portfolio Performance: A Case Study on Stock Selection and Optimization (2023)Time series forecasting using a hybrid ARIMA and neural network model (2003)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Financial time series forecasting model based on CEEMDAN and LSTM (2018)A novel hybrid model for stock price forecasting integrating Encoder Forest and Informer (2023)Carbon price forecasting based on secondary decomposition and feature screening (2023)Multi-step-ahead stock price prediction using recurrent fuzzy neural network and variational mode decomposition (2023)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)A Capital Asset Pricing Model with Time-Varying Covariances (1988)Dynamic Conditional Correlation (2002)A framework to improve churn prediction performance in retail banking (2024)Advanced AI and big data techniques in E-finance: a comprehensive survey (2025)Emerging technologies in finance: challenges for a sustainable finance (2025)
this work references cited by second hop

References

  • 2010Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange880 cited
  • 2002Modified support vector machines in financial time series forecasting372 cited
  • 2009Using support vector machine with a hybrid feature selection method to the stock trend prediction302 cited
  • 2011A hybrid stock selection model using genetic algorithms and support vector regression243 cited
  • 2010A method for automatic stock trading combining technical analysis and nearest neighbor classification172 cited
  • 1991Time series forecasting using backpropagation neural networks171 cited
  • 2006Intelligent technical analysis based equivolume charting for stock trading using neural networks125 cited

Cited by

  • 2020Prediction-Based Portfolio Optimization Models Using Deep Neural Networks104 cited
  • 2022The Use of Predictive Analytics in Finance95 cited
  • 2022Asian stock markets closing index forecast based on secondary decomposition, multi-factor analysis and attention-based LSTM model84 cited
  • 2018Integrating principle component analysis and weighted support vector machine for stock trading signals prediction80 cited
  • 2021Feature selection and deep neural networks for stock price direction forecasting using technical analysis indicators80 cited
  • 2019Comparing the effectiveness of deep feedforward neural networks and shallow architectures for predicting stock price indices

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

77 cited
  • 2020Ensemble of machine learning algorithms for cryptocurrency investment with different data resampling methods77 cited
  • 2021A stock selection algorithm hybridizing grey wolf optimizer and support vector regression71 cited
  • 2022Event prediction within directional change framework using a CNN-LSTM model71 cited
  • 2021A review of machine learning experiments in equity investment decision-making: why most published research findings do not live up to their promise in real life66 cited
  • 2019An Empirical Study of Machine Learning Algorithms for Stock Daily Trading Strategy66 cited
  • 2021Stock Market Prediction with Gaussian Naïve Bayes Machine Learning Algorithm63 cited
  • 2022Multi-level impacts of climate change and supply disruption events on a potato supply chain: An agent-based modeling approach56 cited
  • 2015Stock market trend prediction using dynamical Bayesian factor graph54 cited
  • 2015Quantifying StockTwits semantic terms’ trading behavior in financial markets: An effective application of decision tree algorithms50 cited
  • 2021Stock trading rule discovery with double deep Q-network48 cited