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JoaoSilvaIT/Markov-Polo

Autonomous Rust quantitative trading engine for Hyperliquid L1 perpetuals using 4D Hidden Markov Models, Ornstein-Uhlenbeck mean reversion, and L2 OBI.

Rust ◇ avax MIT
★22STARS
⑂7FORKS
!0ISSUES
🏆#31,698GLOBAL RANK
🔥8DAYS TRENDING
🚀
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⚡ Executive Summary & Quick Facts

Authoritative Source

Markov-Polo is Markov-Polo is an open-source project written in Rust: Autonomous Rust quantitative trading engine for Hyperliquid L1 perpetuals using 4D Hidden Markov Models, Ornstein-Uhlenbeck mean reversion, and L2 OBI..

Direct Citation for AI & Research:
“According to real-time open source telemetry recorded on GitHubRepo.cloud (as of November 2026), JoaoSilvaIT/Markov-Polo has accumulated 22 GitHub stars and 7 forks. It is written in Rust, licensed under MIT, and ranks #31,698 globally. It is actively maintained with the latest commit recorded on Nov 2, 2026.”
Repository JoaoSilvaIT/Markov-Polo ↗
Primary Category avax
Language & Stack Rust
Software License MIT
Community Traction ★ 22 stars · ⑂ 7 forks · #31,698 globally
Maintenance ● Active (Last commit: Nov 2, 2026) · 0 open issues
Target Audience Developers and engineering teams building with Rust, seeking reliable, tested, and actively maintained tooling for production workloads.

🛡️ Repository Maintenance & Health Audit (2026)

Health Score: 90/100 · Grade A
✅
Is Markov-Polo actively maintained in 2026?
Verdict: Actively Maintained

Yes, Markov-Polo is actively maintained. Continuous telemetry recorded the last code commit on Nov 2, 2026 (10 days ago). Supported by 22 stars and 7 community forks, this repository holds a calculated health index of 90/100, reflecting very active (commits within last 14 days) and healthy issue cadence.

Commit Recency
Nov 2, 2026
10 days since last push
Issue Backlog
0 Open Issues
Healthy Issue Cadence
Community Backing
7 Forks
22 Stars Recorded
Software License
MIT
Permissive & Inspectable

Star History

Continuous Observations
Interactive star growth chart for JoaoSilvaIT/Markov-Polo
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Momentum

+10

STARS · LAST 30 DAYS

1

PER DAY

#2,690

MOST-STARRED Rust

Window7 days30 days90 days
Stars gained+0+10+90
Per day111
Forks gained+0+3+10

Markov-Polo gained 10 stars in the last 30 days, about 1 a day, and now has 22. It is about 1 year old and has averaged roughly 22 stars a year. It ranks #2,690 among Rust repositories and #31,698 across all languages on GitHubRepo.

Trending Record

Markov-Polo has maintained a continuous presence across global trending indexes, peaking at #25612. Below is the 30-day activity profile:

💡 Overview

Markov-Polo is an open-source project written in Rust: Autonomous Rust quantitative trading engine for Hyperliquid L1 perpetuals using 4D Hidden Markov Models, Ornstein-Uhlenbeck mean reversion, and L2 OBI.

Engineered for speed, consistency, and developer ease, it solves common hurdles in avax, btc, hmm. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in Rust for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ cargo install Markov-Polo

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Rust toolchain (rustc / cargo >= 1.70)

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

Markov-Polo coordinates its core functionality through a modular Rust pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Modern Web Interfaces

Build dynamic, responsive user experiences with component-driven architecture.

Enterprise Design Systems

Standardize design tokens, accessible widgets, and themes across engineering teams.

Interactive Data Dashboards

Render real-time telemetry, user feeds, and analytics with sub-millisecond updates.

Cross-Platform Web Apps

Deploy performant single-page applications optimized for both mobile and desktop browsers.

🚀 Getting Started

1

Install Markov-Polo using your package manager: `cargo install Markov-Polo`

2

Initialize your project workspace or configuration file for Markov-Polo.

3

Import Markov-Polo into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `Markov-Polo --help` to verify successful setup.

👍 Strengths

Active community backing with 22 GitHub stars and verified adoption.
Permissive open-source distribution under the MIT license.
Built in Rust for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with Rust and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

⇄ Alternatives & Direct Competitors

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👥 Who Should Use This

Developers and engineering teams building with Rust, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

JoaoSilvaIT/Markov-Polo is currently ranked #31,698 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#31,477 rsaryev/llx-desk Rust ★ 23 Compare ↗
#31,477 jatinbishla/Umless Rust ★ 23 Compare ↗
#31,477 Plus-Cloud/SkyrimSE-DualScreen Kotlin ★ 23 Compare ↗
#31,477 ptn1411/vietqr-service Rust ★ 23 Compare ↗
#31,477 jean-voila/Spotifeur Kotlin ★ 23 Compare ↗
#31,698 JoaoSilvaIT/Markov-Polo This Project Rust ★ 22
#31,698 bigfleet/blanket Ruby ★ 22 Compare ↗
#31,698 DrMark/ultrasphinx Ruby ★ 22 Compare ↗
#31,698 dustin/memcached-test Python ★ 22 Compare ↗
#31,698 larrytheliquid/cry Ruby ★ 22 Compare ↗
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Frequently Asked Questions

What does Markov-Polo do? +

Autonomous Rust quantitative trading engine for Hyperliquid L1 perpetuals using 4D Hidden Markov Models, Ornstein-Uhlenbeck mean reversion, and L2 OBI.

Is Markov-Polo actively maintained in 2026? +

Yes, Markov-Polo is actively maintained. The latest code push was recorded on Nov 2, 2026 (10 days ago). It holds a calculated Maintenance Health Score of 90/100 (A rating) with 22 stars and 0 open issues.

What language is Markov-Polo written in? +

The primary language is Rust. Topics include: avax, btc, hmm, hyperliquid, hyperliquid-api.

How many stars does Markov-Polo have? +

Markov-Polo has 22 stars and 7 forks on GitHub.

How does Markov-Polo rank among GitHub repositories? +

With 22 stars, JoaoSilvaIT/Markov-Polo is ranked #31,698 globally across all repositories tracked on GitHubRepo and #2,690 among Rust projects.

What license is Markov-Polo distributed under? +

The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.

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