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Supervised actor-critic reinforcement learning with action feedback for algorithmic trading
Reinforcement learning is one of the promising approaches for algorithmic trading in financial markets. However, in certain situations, buy or sell...
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Reinforcement Learning in Algorithmic Trading: An Overview
This article provides a overview of the application of reinforcement learning in algorithmic trading. Reinforcement learning is a type of machine...
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Deep Heterogeneous AutoML Trend Prediction Model for Algorithmic Trading in the USD/COP Colombian FX Market Through Limit Order Book (LOB)
This study presents a novel and competitive approach for algorithmic trading in the Colombian US dollar inter-bank market (SET-FX). At the core of...
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Algorithmic trading with directional changes
Directional changes (DC) is a recent technique that summarises physical time data (e.g. daily closing prices, hourly data) into events, offering...
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Multi-type data fusion framework based on deep reinforcement learning for algorithmic trading
In recent years, research on algorithmic trading based on machine learning has been increasing. One challenge faced is getting an accurate...
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Algorithmic Forex Trading Using Q-learning
The forex market is a difficult market for traders to succeed. The high noise and volatility of the forex market make the traders very hard to open...
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MOT: A Mixture of Actors Reinforcement Learning Method by Optimal Transport for Algorithmic Trading
Algorithmic trading refers to executing buy and sell orders for specific assets based on automatically identified trading opportunities. Strategies...
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Green Hardware Infrastructure for Algorithmic Trading
Every software needs hardware to be run on. Nowadays we encounter urgent need to mitigate the adverse effects of climate change. It prompted a...
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Algorithmic Trading Systems and Strategies: A New Approach Design, Build, and Maintain an Effective Strategy Search Mechanism
Design and develop a complex trading system from idea to operation. Old approaches were based on manually searching for strategy ideas. This book...
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Algorithmic Trading System Using Auto-machine Learning as a Filter Rule
This paper enhances the performance of an algorithmic trading system or strategy, based on technical indicators, by integrating a classification...
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UNSURE - A machine learning approach to cryptocurrency trading
Although cryptocurrency trading can be highly profitable, it carries significant risks due to extreme price fluctuations and high degree of market...
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Quantitative Trading: An Introduction
Quantitative trading, also called algorithmic trading, refers to automated trading activities that buy or sell particular instruments based on...
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Quantitative Trading Strategies Using Python Technical Analysis, Statistical Testing, and Machine Learning
Build and implement trading strategies using Python. This book will introduce you to the fundamental concepts of quantitative trading and shows how...
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Sentiment and Knowledge Based Algorithmic Trading with Deep Reinforcement Learning
Algorithmic trading, due to its inherent nature, is a difficult problem to tackle; there are too many variables involved in the real-world which...
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Transaction-aware inverse reinforcement learning for trading in stock markets
AbstractTraining automated trading agents is a long-standing topic that has been widely discussed in artificial intelligence for the quantitative...
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(Some) algorithmic bias as institutional bias
In this paper I argue that some examples of what we label ‘algorithmic bias’ would be better understood as cases of institutional bias. Even when...
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Predicting earnings per share using feature-engineered extreme gradient boosting models and constructing alpha trading strategies
This study explores the effectiveness of Extreme Gradient Boosting (XGBoost) models in predicting a stock's future Earnings Per Share (EPS). It...
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An Algorithmic Trading Strategy for the Colombian US Dollar Inter-bank Bulk Market SET-FX Based on an Evolutionary TPOT AutoML Predictive Model
In this paper, we introduce a competitive algorithmic trading strategy for the Colombian US dollar inter-bank bulk order-driven market, SET-FX. The...
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Multi-factor stock trading strategy based on DQN with multi-BiGRU and multi-head ProbSparse self-attention
AbstractReinforcement learning is widely used in financial markets to assist investors in develo** trading strategies. However, most existing...
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Introduction to Develo** Trading Systems
To move on to the next chapters, which contain specific information about the architecture and technical solution of my system, we must consider the...