Algorithmic Crypto Trading using EMA Strategy

Title

Algorithmic Crypto Trading using EMA Strategy

Creator

Revathi, S.; Meesala, Shobha; Sudha, V.; Priyanka, R.; Manikandakumar, M.; Vigneshwaran, T.

Description

Algorithmic trading has transformed financial markets by enabling data-driven strategies that enhance efficiency and decision-making. This paper presents a web-based crypto currency trading platform that employs the Exponential Moving Average (EMA) strategy for automated trade execution, market trend analysis, and portfolio tracking. The platform integrates key performance metrics, including win rate, average profit per trade, risk-reward ratio, and profit factor to assess trading effectiveness. Notably, EMA-based trading achieves the highest profit factor of 3.5 which outperformed deep learning and manual trading by 9.37% and 133%, respectively. Additionally, EMA exhibits a strong win rate of 60%, compared to 65% for deep learning and 40% for manual trading, while maintaining a balanced risk-reward ratio of 2.2. The system features live data visualization, customizable watchlists, and automated trading workflows, providing traders with actionable insights with minimized human error. Performance evaluation indicates that EMA offers a superior trade-off between profitability and risk management, making it a robust and adaptable solution for navigating cryptocurrency markets. This work bridges the gap between manual trading and advanced algorithmic strategies, delivering a user-friendly and efficient trading framework. 2025 IEEE.

Source

Proceedings of 5th International Conference on Pervasive Computing and Social Networking, ICPCSN 2025;pp.997-1002

Date

01-01-2025

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Algorithmic Trading; Automated Systems; Cryptocurrency; Data Visualization; Exponential Moving Average; Portfolio Analytics

Coverage

Revathi S., Cmr Institute of Technology, Bengaluru, India; Meesala S., Reva University, Bangalore, India; Sudha V., Cambridge Institute of Technology, Bangalore, India; Priyanka R., Cambridge Institute of Technology, Bangalore, India; Manikandakumar M., Christ University, Bangalore, India; Vigneshwaran T., Christ University, Bangalore, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISBN: 979-833153519-3;

Format

online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/ICPCSN65854.2025.11035368

https://www.scopus.com/pages/publications/105010204561?origin=resultslist