SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Generating Realistic Stock Market Order Streams
9 references·2 citing·50 second hop
Generating Realistic Stock Market Order Streams (2020)Generating Realistic Stock Market Order S…Generative adversarial networks for financial trading strategies fine-tuning and combination (2020)Generative adversarial networ…Stock Market Prediction Based on Generative Adversarial Network (2019)Stock Market Prediction Based…The Double Auction Market Institution: A Survey (2018)The Double Auction Market Ins…NSE Stock Market Prediction Using Deep-Learning Models (2018)NSE Stock Market Prediction U…Deep Learning for Forecasting Stock Returns in the Cross-Section (2018)Deep Learning for Forecasting…Stock Price Prediction via Discovering Multi-Frequency Trading Patterns (2017)Stock Price Prediction via Di…A deep learning framework for financial time series using stacked autoencoders and long-short term memory (2017)A deep learning framework for…Limit Order Books (2016)Limit Order BooksAgent-based Computational Finance (1989)Agent-based Computational Fin…Learning to simulate realistic limit order book markets from data as a World Agent (2022)Learning to simulate realisti…Improving Generalization in Reinforcement Learning–Based Trading by Using a Generative Adversarial Market Model (2021)Improving Generalization in R…Market Making and the Changing Structure of the Securities Industry (1985)Adaptive agents in a persistent shout double auction (1998)Sunspots in the Laboratory (2005)SODA: Strategy-Proof Online Double Auction Scheme for Multimicrogrids Bidding (2017)EFFICIENT CAPITAL MARKETS: A REVIEW OF THEORY AND EMPIRICAL WORK* (1970)Noise Trader Risk in Financial Markets (1990)The Use of Knowledge in Society (1996)The contribution of tourism development to economic growth in the Korean economy (2003)Chapter 23 Heterogeneous Agent Models in Economics and Finance (2006)Negative bubbles and shocks in cryptocurrency markets (2016)Forecasting stock market movement direction with support vector machine (2004)CNNpred: CNN-based stock market prediction using a diverse set of variables (2019)Temporal Relational Ranking for Stock Prediction (2019)Applications of deep learning in stock market prediction: Recent progress (2021)A Bayesian regularized artificial neural network for stock market forecasting (2013)Comparison of ARIMA and Artificial Neural Networks Models for Stock Price Prediction (2014)Predicting stock market index using fusion of machine learning techniques (2014)Listening to Chaotic Whispers (2018)Enhancing Stock Movement Prediction with Adversarial Training (2019)A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions (2021)Surveying stock market forecasting techniques – Part II: Soft computing methods (2008)… and the Cross-Section of Expected Returns (2015)Does Academic Research Destroy Stock Return Predictability? (2015)Mixture of Activation Functions With Extended Min-Max Normalization for Forex Market Prediction (2019)Financial time series forecasting with deep learning : A systematic literature review: 2005–2019 (2020)ST-Trader: A Spatial-Temporal Deep Neural Network for Modeling Stock Market Movement (2021)Forecasting with artificial neural networks: (1998)Time series forecasting using a hybrid ARIMA and neural network model (2003)Stock price prediction using LSTM, RNN and CNN-sliding window model (2017)Stock Market Analysis: A Review and Taxonomy of Prediction Techniques (2019)Optimizing LSTM for time series prediction in Indian stock market (2020)Stock price prediction using deep learning and frequency decomposition (2020)Time Series Analysis: Forecasting and Control (1977)Time Series Analysis: Forecasting and Control (1977)A hybrid ARIMA and support vector machines model in stock price forecasting (2004)A systematic review of stock market prediction using machine learning and statistical techniques (2021)S_I_LSTM: stock price prediction based on multiple data sources and sentiment analysis (2021)Machine learning approaches in stock market prediction: A systematic literature review (2023)The Combination of Forecasts (1969)The Sharpe Ratio (1994)Empirical properties of asset returns: stylized facts and statistical issues (2001)CORRGAN: Sampling Realistic Financial Correlation Matrices Using Generative Adversarial Networks (2020)Generation of Realistic Synthetic Financial Time-series (2022)Generalized autoregressive conditional heteroskedasticity (1986)Herd Behavior and Investment (1988)The Efficient Market Hypothesis and Its Critics (2003)Novel Deep Reinforcement Algorithm With Adaptive Sampling Strategy for Continuous Portfolio Optimization (2021)High-dimensional Hawkes processes for limit order books: modelling, empirical analysis and numerical calibration (2018)Incorporating signals into optimal trading (2019)Deep order flow imbalance: Extracting alpha at multiple horizons from the limit order book (2023)
this work references cited by second hop

References

  • 2017A deep learning framework for financial time series using stacked autoencoders and long-short term memory1,131 cited
  • 1989Agent-based Computational Finance693 cited
  • 2018NSE Stock Market Prediction Using Deep-Learning Models615 cited
  • 2017Stock Price Prediction via Discovering Multi-Frequency Trading Patterns476 cited
  • 2019Stock Market Prediction Based on Generative Adversarial Network313 cited
  • 2018Deep Learning for Forecasting Stock Returns in the Cross-Section124 cited
  • 2018The Double Auction Market Institution: A Survey104 cited
  • 2016Limit Order Books78 cited
  • 2020Generative adversarial networks for financial trading strategies fine-tuning and combination70 cited

Cited by

  • 2021Improving Generalization in Reinforcement Learning–Based Trading by Using a Generative Adversarial Market Model42 cited
  • 2022Learning to simulate realistic limit order book markets from data as a World Agent23 cited

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