Algorithmic Trading

17 papers with code • 0 benchmarks • 1 datasets

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


Use these libraries to find Algorithmic Trading models and implementations

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.

FinGPT: Open-Source Financial Large Language Models

ai4finance-foundation/fingpt 9 Jun 2023

While proprietary models like BloombergGPT have taken advantage of their unique data accumulation, such privileged access calls for an open-source alternative to democratize Internet-scale financial data.

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.

Deep Reinforcement Learning in Quantitative Algorithmic Trading: A Review

ludel/AutoTrading 31 May 2021

Algorithmic stock trading has become a staple in today's financial market, the majority of trades being now fully automated.

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.