About Us

The Core Philosophy:
Engineering Edge

Most trading ideas fail not due to a lack of intuition, but due to a lack of rigorous validation. hirus.systems was founded to bridge the gap between discretionary trading concepts and quantitative execution.

The Algorithmic Architecture

Our engine is built for speed and precision, utilizing the industry-standard Python ecosystem.

Ultrafast Vectorized Engine

Eliminating the latency of legacy event-driven systems. By utilizing vectorbt, we process entire datasets as matrices, achieving backtest speeds that outperform standard iterations by 100x.

High-Fidelity Time-Series Data

Integration with Twelve Data API provides access to verified, high-resolution historical data. This ensures precise identification of structural shifts (BOS) and Liquidity Zones across multiple timeframes, making backtest results consistent with real-world market behavior.

Algorithmic Synthesis Engine

A proprietary translation layer powered by Google Vertex AI. It performs high-precision mapping of natural language trading hypotheses into optimized code structures. This core serves as the bridge between abstract logic and the vectorbt mathematical framework.

Distributed Computation Engine

Designed for Scalable Parallel Execution, our engine calculates thousands of parameter combinations simultaneously. By utilizing high-performance cloud instances, we enable deep strategy optimization at a scale impossible for standard local environments.

User Features

AI-Driven Strategy Synthesis

We are democratizing institutional-grade quantitative tools. By removing the "technical tax" usually paid by professional traders who understand markets but not complex programming, we collapse the distance between a hypothesis and a validated PnL to zero.

"Intuition meets execution. Describe your logic, and let the architecture handle the complexity."

By fine-tuning LLMs on specific quantitative libraries, hirus.systems allows users to describe market conditions in plain language, which the system then converts into a production-ready backtest.

This focus on the user's intent ensures that the focus remains on alpha discovery, not troubleshooting code or managing data infrastructure.

Roadmap: Scaling the Alpha

PHASE 01
Completed

Core Infrastructure

Implementation of Multi-Test & Optimization Engines and High-Resolution Data integration via Twelve Data.

PHASE 02
Completed

Statistical Validation

Launch of Advanced Portfolio Correlation Analysis and automated SMC structural detection (BOS/Liquidity).

PHASE 03
Current

Intelligence & Asset Scaling

Integration of predictive Machine Learning models for signal filtering. Expansion of technical indicator library and global asset coverage (Forex, Crypto, Indices).

PHASE 04
Future

Production & Execution

Development of a secure Live Execution Bridge via broker APIs and a real-time risk-management dashboard.

Research & Transparency

Building in Public

Follow the technical evolution of our algorithms and my ongoing research into market mechanics across our social ecosystem.

Contact: founder@hirus.systems