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time-series-4

Algorithmic Trading

3260 papers • 126 benchmarks • 313 datasets

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

(Image credit: Papersgraph)

Benchmarks

These leaderboards are used to track progress in algorithmic-trading-4

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Dataset

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Libraries

Use these libraries to find algorithmic-trading-4 models and implementations

ai4finance-foundation/fingpt

2 papers 11,309

Datasets

S&P 500 Intraday Data

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No subtasks available.

Most implemented papers

FinGPT: Open-Source Financial Large Language Models

Xiao-Yang Liu, Hongyang Yang, Chris Wang•Thu Jun 08 2023

This paper presents an open-source large language model, FinGPT, for the finance sector, and highlights the importance of an automatic data curation pipeline and the lightweight low-rank adaptation technique in building FinGPT.

326

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Introduction Benchmarks Datasets Subtasks Libraries Papers

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Machine Learning in Asset Management—Part 1: Portfolio Construction—Trading Strategies

Derek Snow•Mon Jul 15 2019

This article focuses on portfolio construction using machine learning, highlighting nine different trading varieties each making use of a reinforcement-, supervised-, or unsupervised-learning framework or a combination of these learning frameworks.

20 0

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Using Reinforcement Learning in the Algorithmic Trading Problem

I. Oseledets, E. Ponomarev, A. Cichocki•Sat Nov 30 2019

Trading on the stock exchange is interpreted into a game with a Markov property consisting of states, actions, and rewards and a system for trading the fixed volume of a financial instrument is proposed and experimentally tested based on the asynchronous advantage actor-critic method with the use of several neural network architectures.

26 0

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An Application of Deep Reinforcement Learning to Algorithmic Trading

Thibaut Théate, D. Ernst•Mon Apr 06 2020

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 is presented.

202 0

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Rise of the machines? Intraday high-frequency trading patterns of cryptocurrencies

W. Härdle, Alla Petukhina, Raphael C. G. Reule•Tue May 12 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 to lead to a new quantitative view on approaching the predictability of economic value in this new digital market.

54 0

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Taking over the Stock Market: Adversarial Perturbations Against Algorithmic Traders

A. Shabtai, Y. Elovici, Elior Nehemya, Yael Mathov•Sun Oct 18 2020

This study presents 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 and presents various mitigation methods.

8 0

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Multi-Graph Tensor Networks

Yao Xu, Kriton Konstantinidis, D. Mandic•Sat Oct 24 2020

A novel Multi-Graph Tensor Network (MGTN) framework is introduced, which exploits both the ability of graphs to handle irregular data sources and the compression properties of tensor networks in a deep learning setting.

8 0

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Deep Reinforcement Learning in Quantitative Algorithmic Trading: A Review

Tidor-Vlad Pricope•Sun May 30 2021

It is concluded that DRL in stock trading has showed huge applicability potential rivalling professional traders under strong assumptions, but the research is still in the very early stages of development.

48 0

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Exploration of Algorithmic Trading Strategies for the Bitcoin Market

Eoin Brophy, N. Crone, Tomas E. Ward•Wed Oct 27 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 to indicate the credible potential that machine learning models have in extracting profit from theBitcoin market.

4 0

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Algorithmic Trading | State-of-the-Art