Algorithmic Trading

12 papers with code • 0 benchmarks • 1 datasets

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

Most implemented papers

A Wavelet Method for Panel Models with Jump Discontinuities in the Parameters

timmens/sawr 22 Sep 2021

Our method adapts Haar wavelets to the structure of the observed variables in order to detect the change points of the parameters consistently.

Using Reinforcement Learning in the Algorithmic Trading Problem

evgps/a3c_trading 26 Feb 2020

A system for trading the fixed volume of a financial instrument is proposed and experimentally tested; this is based on the asynchronous advantage actor-critic method with the use of several neural network architectures.

An Application of Deep Reinforcement Learning to Algorithmic Trading

ThibautTheate/An-Application-of-Deep-Reinforcement-Learning-to-Algorithmic-Trading 7 Apr 2020

This scientific research paper presents an innovative approach based on deep reinforcement learning (DRL) to solve the algorithmic trading problem of determining the optimal trading position at any point in time during a trading activity in stock markets.

Rise of the Machines? Intraday High-Frequency Trading Patterns of Cryptocurrencies

QuantLet/CCID 9 Sep 2020

This research analyses high-frequency data of the cryptocurrency market in regards to intraday trading patterns related to algorithmic trading and its impact on the European cryptocurrency market.

Taking Over the Stock Market: Adversarial Perturbations Against Algorithmic Traders

nehemya/Algo-Trade-Adversarial-Examples 19 Oct 2020

In this study, we present a realistic scenario in which an attacker influences algorithmic trading systems by using adversarial learning techniques to manipulate the input data stream in real time.

Multi-Graph Tensor Networks

gylx/GTNRL-Trading 25 Oct 2020

The irregular and multi-modal nature of numerous modern data sources poses serious challenges for traditional deep learning algorithms.

Exploration of Algorithmic Trading Strategies for the Bitcoin Market

Crone1/Bitcoin-Algorithmic-Trading-Paper 28 Oct 2021

This work brings an algorithmic trading approach to the Bitcoin market to exploit the variability in its price on a day-to-day basis through the classification of its direction.

Intelligent Trading Systems: A Sentiment-Aware Reinforcement Learning Approach

xicocaio/its-sentarl 14 Nov 2021

The feasibility of making profitable trades on a single asset on stock exchanges based on patterns identification has long attracted researchers.

A Modular Framework for Reinforcement Learning Optimal Execution

fernandodemeer/rl_optimal_execution 11 Aug 2022

In this article, we develop a modular framework for the application of Reinforcement Learning to the problem of Optimal Trade Execution.