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Machine Learning for Forecasting Mid-Price Movements Using Limit Order Book Data
16 references·0 citing·35 second hop
Machine Learning for Forecasting Mid-Price Movements Using Limit Order Book Data (2019)Machine Learning for Forecasting Mid-Pric…Temporal Attention-Augmented Bilinear Network for Financial Time-Series Data Analysis (2018)Temporal Attention-Augmented …Using deep learning to detect price change indications in financial markets (2017)Using deep learning to detect…Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks (2017)Forecasting Stock Prices from…Modelling high-frequency limit order book dynamics with support vector machines (2015)Modelling high-frequency limi…Using machine learning algorithms for housing price prediction: The case of Fairfax County, Virginia housing data (2014)Using machine learning algori…Financial time series forecasting using independent component analysis and support vector regression (2009)Financial time series forecas…Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm (2008)Forecasting crude oil price w…Forecasting stock market movement direction with support vector machine (2004)Forecasting stock market move…Support vector machine with adaptive parameters in financial time series forecasting (2003)Support vector machine with a…Financial time series forecasting using support vector machines (2003)Financial time series forecas…Statistical properties of stock order books: empirical results and models (2002)Statistical properties of sto…Multiresolution forecasting for futures trading using wavelet decompositions (2001)Multiresolution forecasting f…Application of support vector machines in financial time series forecasting (2001)Application of support vector…An Empirical Analysis of Data Requirements for Financial Forecasting with Neural Networks (2001)An Empirical Analysis of Data…Designing a neural network for forecasting financial and economic time series (1996)Designing a neural network fo…Forecasting futures trading volume using neural networks (1995)Forecasting futures trading v…Time Series Analysis Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control (1977)Time series prediction: Forecasting the future and understanding the past (1994)Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold (2013)Machine learning in energy economics and finance: A review (2019)A new forecasting model with wrapper-based feature selection approach using multi-objective optimization technique for chaotic crude oil time series (2020)Forecasting with artificial neural networks: (1998)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)Predicting stock and stock price index movement using Trend Deterministic Data Preparation and machine learning techniques (2014)Stock market's price movement prediction with LSTM neural networks (2017)A neural network model for bankruptcy prediction (1990)Predicting the Price of Bitcoin Using Machine Learning (2018)Forecasting: theory and practice (2022)The Cross-Section of Expected Stock Returns (1992)A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)Comparing Predictive Accuracy (1994)Stock price prediction using support vector regression on daily and up to the minute prices (2018)Optimizing LSTM for time series prediction in Indian stock market (2020)Machine learning techniques and data for stock market forecasting: A literature review (2022)A Coefficient of Agreement for Nominal Scales (1960)Drift Independent Volatility Estimation Based on High, Low, Open, and Close Prices (2000)DeepLOB: Deep Convolutional Neural Networks for Limit Order Books (2019)Stock Market Prediction Based on Generative Adversarial Network (2019)An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse (1995)Introduction to Econophysics (1999)Empirical properties of asset returns: stylized facts and statistical issues (2001)Statistical theory of the continuous double auction (2003)Fluctuations and response in financial markets: the subtle nature of ‘random’ price changes (2004)Econophysics review: I. Empirical facts (2011)Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey (2009)Support vector regression with chaos-based firefly algorithm for stock market price forecasting (2012)Financial time series forecasting with multi-modality graph neural network (2021)Monitoring housing rental prices based on social media:An integrated approach of machine-learning algorithms and hedonic modeling to inform equitable housing policies (2019)A HOUSE PRICE VALUATION BASED ON THE RANDOM FOREST APPROACH: THE MASS APPRAISAL OF RESIDENTIAL PROPERTY IN SOUTH KOREA (2020)Predicting property prices with machine learning algorithms (2020)
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References

  • 2003Financial time series forecasting using support vector machines1,734 cited
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  • 2004Forecasting stock market movement direction with support vector machine1,119 cited
  • 1996Designing a neural network for forecasting financial and economic time series1,092 cited
  • 2003Support vector machine with adaptive parameters in financial time series forecasting1,008 cited
  • 2008Forecasting crude oil price with an EMD-based neural network ensemble learning paradigm705 cited
  • 2009Financial time series forecasting using independent component analysis and support vector regression538 cited
  • 2014Using machine learning algorithms for housing price prediction: The case of Fairfax County, Virginia housing data400 cited
  • 2017Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks394 cited
  • 2002Statistical properties of stock order books: empirical results and models358 cited
  • 2001An Empirical Analysis of Data Requirements for Financial Forecasting with Neural Networks238 cited
  • 2018Temporal Attention-Augmented Bilinear Network for Financial Time-Series Data Analysis238 cited
  • 2017Using deep learning to detect price change indications in financial markets157 cited
  • 2015Modelling high-frequency limit order book dynamics with support vector machines

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145 cited
  • 2001Multiresolution forecasting for futures trading using wavelet decompositions137 cited
  • 1995Forecasting futures trading volume using neural networks135 cited
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