AlgoWave-A Rule Based Code Generator for Automatic Trading System

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Authors: Prof. M. S. Burange
Cited by: 0
References: 4

Abstract

Algorithmic trading, also known as automated trading, has transformed financial markets by enabling computers to automatically analyze market conditions and execute trades independently. Traditional methods typically require advanced programming expertise, which excludes many retail traders and novices without such technical skills. The AlgoWave platform addresses this gap through an intuitive web interface that allows users to create and deploy trading strategies without writing any code. Via an accessible dashboard featuring dropdown menus and input forms, traders can define strategies using candlestick patterns, entry/exit signals, and preferred timeframes. AlgoWave automatically converts these specifications into complete, executable scripts compatible with international platforms like MetaTrader5 or domestic Indian markets via Python APIs. This approach makes advanced automation available to non-programmers who previously lacked access to such capabilities. This paper presents AlgoWave's complete system design from user interface to backend code synthesis and secure deployment workflows—supported by empirical performance evaluations demonstrating both reliability and efficiency. Testing confirms over 80% reduction in strategy deployment time versus traditional manual coding, with consistent accuracy during simulations across highly volatile market conditions.

Fields of Study & Subjects

Stock Market Forecasting Methods Financial Markets and Investment Strategies FinTech Crowdfunding Digital Finance

Publication details

Journal / source
International Journal for Research in Applied Science and Engineering Technology
Volume
14
Issue
2
Pages
1103–1109
Publication date
23 February 2026
Language
EN