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High-Frequency Trading Strategy Based on Deep Neural Networks · Study

WorkHigh-Frequency Trading Strategy Based on Deep Neural Networks

Andrés Arévalo2016

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Workgreen2016

High-Frequency Trading Strategy Based on Deep Neural Networks

Andrés Arévalo · Germán Hernández · Javier Sandoval

100 citations·0/0 files stored·Lecture notes in computer science

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Stock Market Forecasting Methods Financial Markets and Investment Strategies Stochastic processes and financial applications

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References

2006Analysis of Financial Time Series 200625 years of time series forecasting 2005Analysis of Financial Time Series 1996Designing a neural network for forecasting financial and economic time series 1999Technical analysis of the financial markets: a comprehensive guide to trading methods and applications 1992Neural Networks in Finance and Investing: Using Artificial Intelligence to Improve Real-World Performance 2008The Econometric Modelling of Financial Time Series

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2018Replicating a Trading Strategy by Means of LSTM for Financial Industry Applications 2020Enhanced Prediction of Intra-day Stock Market Using Metaheuristic Optimization on RNN–LSTM Network 2022A New CNN-Based Model for Financial Time Series: TAIEX and FTSE Stocks Forecasting 2022Stock Price Prediction Using a Frequency Decomposition Based GRU Transformer Neural Network 2019A novel CNN-DDPG based AI-trader: Performance and roles in business operations 2019Deep architectures for long-term stock price prediction with a heuristic-based strategy for trading simulations

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Details

Year2016

Typeother

Published2016-01-01

VenueLecture notes in computer science

ISSN-L0302-9743

Languageen

Citations100

Files0 public / 0

ShelfStock Market Forecasting Methods

Identifiers

doi10.1007/978-3-319-42297-8_40

openalex_workW2490603845

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2017A Double-Layer Neural Network Framework for High-Frequency Forecasting

2022GCNET: Graph-based prediction of stock price movement using graph convolutional network