DUCKQUANT / THE QUANT & AI DIRECTORY
2,336 resources, ranked by in-directory PageRank
This paper presents a high-frequency strategy based on Deep Neural Networks (DNNs). The DNN was trained on current time (hour and minute), and $$…
Forecasting financial time-series has long been among the most challenging problems in financial market analysis. In order to recognize the correct circumstance
Publication: Classification-based Financial Markets Prediction using Deep Neural Networks. Published Mar 29, 2016.
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Publication: Deep Learning in Asset Pricing. Published Mar 11, 2019.
Publication: Enhancing Time Series Momentum Strategies Using Deep Neural Networks. Published Apr 9, 2019.
Publication: Cooperative Multi-Agent Reinforcement Learning Framework for Scalping Trading. Published Mar 31, 2019.
Developing accurate financial analysis tools can be useful both for speculative trading, as well as for analyzing the behavior of markets and promptly respondin
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Publication: Practical Deep Reinforcement Learning Approach for Stock Trading. Published Nov 19, 2018.
Publication: Financial Trading as a Game: A Deep Reinforcement Learning Approach. Published Jul 8, 2018.
This paper proposes automating swing trading using deep reinforcement learning. The deep deterministic policy gradient-based neural network model trains to choose an action to…
Publication: A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem. Published Jun 30, 2017.
Publication: VLSTM: Very Long Short-Term Memory Networks for High-Frequency Trading. Published Sep 5, 2018.
In this work, a high-frequency trading strategy using Deep Neural Networks (DNNs) is presented. The input information consists of: (i). Current time (hour and…
In recent years, with the breakthrough of big data and deep learning technology in various fields, many scholars have begun to study the stock…
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Publication: Stock Prices Prediction using Deep Learning Models. Published Sep 25, 2019.
We develop a large-scale deep learning model to predict price movements from limit order book (LOB) data of cash equities. The architecture utilizes convolution
Publication: Financial Time Series Forecasting with Deep Learning : A Systematic Literature Review: 2005-2019. Published Nov 29, 2019.
Publication: Evaluating the Performance of Machine Learning Algorithms in Financial Market Forecasting: A Comprehensive Survey. Published Jun 18, 2019.
Deep Learning and Big Data analytics are two focal points of data science. Deep Learning models have achieved remarkable results in speech recognition and
Publication: Improving Decision Analytics with Deep Learning: The Case of Financial Disclosures. Published Aug 9, 2015.
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Publication: AAMDRL: Augmented Asset Management with Deep Reinforcement Learning. Published Sep 30, 2020.
A reinforcement learning model based on reward correction for quantitative stock selection, Chen, Haibo, Zhang, Chenyu, Li, Yunke
This research applies a deep reinforcement learning technique, Deep Q-network (DQN), to a stock market pairs trading strategy for profit. There is a need…
When applying artificial intelligence technology to quantitative trading, high noise and unpredictability of market environment are the first practical problems
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Publication: An Application of Deep Reinforcement Learning to Algorithmic Trading. Published Apr 7, 2020.
Publication: Capturing Financial markets to apply Deep Reinforcement Learning. Published Jul 9, 2019.
EconStor is a publication server for scholarly economic literature, provided as a non-commercial public service by the ZBW.
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This Meetup group is concerned with data-driven and AI-first finance in general and algorithmic trading in particular. Its events cover the latest developments in…
Alexa, Siri, Cortana, Google Assistant - Vision: Amazon Rekognition, Google Cloud Vision - Natural Language: IBM Watson, Microsoft LUIS - Recommendation: Amazon Personalize -…
