---
title: K1RL QUASAR — Volatility 75
emoji: ⭐
colorFrom: yellow
colorTo: gray
sdk: docker
pinned: false
license: mit
short_description: 8 quantum AI agents trading Volatility 75 on Deriv 24/7
---

# ⚡ K1RL QUASAR — VOLATILITY 75
### ⭐ THE GOLD RANGER — Precision · Momentum · Continuous Volatility

![Status](https://img.shields.io/badge/STATUS-LIVE%2024%2F7-FFD700?style=for-the-badge) ![Index](https://img.shields.io/badge/INDEX-VOLATILITY%2075-FFD700?style=for-the-badge) ![Symbol](https://img.shields.io/badge/SYMBOL-R__75-lightgrey?style=for-the-badge) ![Voyage](https://img.shields.io/badge/VOYAGE-v10-FFD700?style=for-the-badge) ![Pretrain](https://img.shields.io/badge/PRETRAIN-V75__1S%20v5-gray?style=for-the-badge)

---

## 🧠 What is K1RL QUASAR?

K1RL QUASAR is an **8-agent quantum-enhanced reinforcement learning trading system** that autonomously trades synthetic indices on the Deriv platform — 24 hours a day, 7 days a week, with zero human intervention.

Each agent runs an **Actor-Critic network** enhanced with **Qiskit quantum circuits**, coordinating via **QMIX value decomposition** and a **QuantumVotingSystem** where all 6 trading agents vote on every action before execution.

---

## ⭐ Gold Ranger Profile — Volatility 75

> **The Gold Ranger is the precision momentum trader.** Pretrained on V75_1S weights — the same symbol, the same market structure, the same 75% annualised volatility — but now operating on the standard 1-second tick feed. Agents arrive already calibrated to V75's random-walk character and simply refine their timing to the native cadence.

| Property | Value |
|---|---|
| 🎯 Index | Volatility 75 Index |
| 📡 Deriv Symbol | `R_75` |
| 〰️ Market Type | Continuous random-walk (75% annualised vol) |
| 📈 Tick Cadence | 1 second |
| 🧬 Pretrained From | **V75_1S (voyage v5)** |
| 📦 Voyage | `v10` → saves to `V100/v10/` |
| 🔑 Redis Password | `k1rl_v75_8d2f5a1c9e4b7063` |
| 🔄 Transfer Scale | 1.00× — direct weight transfer (same symbol family) |

---

## 🔑 Why V75_1S is the Right Pretrain

Unlike spaces that load from V75 foundation (v1), **V75 loads pretrained weights from V75_1S (v5)** — its closest sibling.

| Factor | V75_1S → V75 | V75 Foundation (v1) → V75 |
|---|---|---|
| Symbol | ✅ Identical (`R_75` / `1HZ75V`) | ✅ Same symbol |
| Market structure | ✅ Same random-walk character | ✅ Same |
| Training maturity | ✅ Fully trained (v5 voyage) | ⚠️ Older baseline |
| Weight transfer scale | ✅ 1.00× (no freq. correction) | ⚠️ May require re-adaptation |
| Expected convergence | **Fast** — same market, more evolved weights | Moderate |

The agents arrive already understanding V75's volatility rhythm. Fine-tuning on the standard tick feed is the only remaining step.

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## 🏗️ Architecture

```
┌──────────────────────────────────────────────────────────┐
│               K1RL QUASAR — VOLATILITY 75                │
├──────────────┬──────────────┬────────────────────────────┤
│  Features.py │  Rewards.py  │    quasar_main4.py         │
│  V75         │  V75         │    8 Actor-Critic          │
│  Tick Data   │  Reward Sig  │    QMIX + Voting           │
├──────────────┴──────────────┴────────────────────────────┤
│                 Redis (V75: namespace)                    │
├──────────────────────────────────────────────────────────┤
│            HuggingFace Spaces — CPU Basic                │
└──────────────────────────────────────────────────────────┘

Checkpoint Loading:

  Startup → scan V100/v10/ → found? → YES → Resume training
                                   → NO  → Load V100/v5/ (V75_1S)
                                                → Reset steps to 0
                                                → Begin V75 fine-tune
```

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## 🗺️ Fleet Voyage Map

| Voyage | Space | Symbol | Pretrain | Theme |
|---|---|---|---|---|
| v1 | K1RL-Quasar-Volatility-75 | R_75 | 🏛️ Foundation | ⬛ Black |
| v2 | K1RL-Quasar-Crash-500 | CRASH500 | v1 | 🔵 Blue |
| v3 | K1RL-Quasar-Volatility-50-1s | 1HZ50V | v1 | 💚 Green |
| v4 | K1RL-Quasar-Volatility-100-1s | 1HZ100V | v1 | 🔴 Red |
| v5 | K1RL-Quasar-Volatility-75-1s | 1HZ75V | v1 | 💛 Yellow |
| v6 | K1RL-Quasar-Crash-1000 | CRASH1000 | v2 | 🌸 Pink |
| v7 | K1RL-Quasar-Volatility-25 | R_25 | v1 | — |
| v8 | K1RL-Quasar-Volatility-30-1s | 1HZ30V | v1 | — |
| v9 | K1RL-Quasar-STPRNG200 | STPRNG200 | v1 | — |
| **v10** | **K1RL-Quasar-Volatility-75** | **R_75** | **v5 (V75_1S)** | **⭐ Gold** |

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## 📊 Checkpoints

- **Dataset**: [KarlQuant/k1rl-checkpoints](https://huggingface.co/datasets/KarlQuant/k1rl-checkpoints)
- **Path**: `V100/v10/`
- **Strategy**: Resume from v10 → fallback warm-start from **v5 (V75_1S)** → cold start if v5 empty

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*Built with PyTorch · Qiskit · Redis · HuggingFace Spaces*

**K1RL QUASAR Fleet** — *Autonomous Quantum Trading* ⭐