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Algorithmic Trading

An algorithmic trading system is a software that is used for trading in the stock market.

Papers

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Showing 51–75 of 95 papers

TitleStatusHype
Learn Continuously, Act Discretely: Hybrid Action-Space Reinforcement Learning For Optimal Execution—0
Le trading algorithmique—0
Limit Order Book Simulations: A Review—0
Machine Learning-Driven Virtual Bidding with Electricity Market Efficiency Analysis—0
Mean Field Games with Partial Information for Algorithmic Trading—0
MOT: A Mixture of Actors Reinforcement Learning Method by Optimal Transport for Algorithmic Trading—0
Nine Challenges in Modern Algorithmic Trading and Controls—0
NoxTrader: LSTM-Based Stock Return Momentum Prediction for Quantitative Trading—0
Order-book modelling and market making strategies—0
Order flow and price formation—0
Periodicity in Cryptocurrency Volatility and Liquidity—0
Portfolio Management using Deep Reinforcement Learning—0
Predicting risk/reward ratio in financial markets for asset management using machine learning—0
Random walk model from the point of view of algorithmic trading—0
Solvability of Differential Riccati Equations and Applications to Algorithmic Trading with Signals—0
A bounded operator approach to technical indicators without lag—0
Sizing Strategies for Algorithmic Trading in Volatile Markets: A Study of Backtesting and Risk Mitigation Analysis—0
Stock Market Directional Bias Prediction Using ML Algorithms—0
Model Based Reinforcement Learning with Non-Gaussian Environment Dynamics and its Application to Portfolio Optimization—0
The Adaptive Multi-Factor Model and the Financial Market—0
Trading through Earnings Seasons using Self-Supervised Contrastive Representation Learning—0
Turnover of investment portfolio via covariance matrix of returns—0
Universal Trading for Order Execution with Oracle Policy Distillation—0
Validating Weak-form Market Efficiency in United States Stock Markets with Trend Deterministic Price Data and Machine Learning—0
Sentiment and Knowledge Based Algorithmic Trading with Deep Reinforcement Learning—0
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