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synth-data

Query volatility forecasts from Synthdata.co for crypto, commodities, and stocks. Compare assets and run Monte Carlo simulations.

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安装方式

直接复制以下提示词,发送给你的 AI 助手即可完成安装。

请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 synth-data 技能。 若已安装,则直接安装 synth-data 技能。

Overview

Skill Key
emsin44/synth-data
Author
emsin44
Source Repo
openclaw/skills
Version
-
Source Path
skills/emsin44/synth-data
Latest Commit SHA
6fc9645cce5f2008b1f7144cb80d95065a0656b7

Extracted Content

SKILL.md excerpt

# Synthdata Volatility Skill

Query and analyze volatility forecasts from Synthdata.co for crypto, commodities, and stock indices.

## Setup

Set your API key:
```bash
export SYNTHDATA_API_KEY=your_key_here
```

## Quick Start

```bash
# Single asset
python3 scripts/synth.py BTC

# Multiple assets comparison
python3 scripts/synth.py BTC ETH SOL --compare

# All assets overview
python3 scripts/synth.py --all

# Monte Carlo simulation (24h max)
python3 scripts/synth.py BTC --simulate --hours 12
```

## Available Assets

| Ticker | Name | Category |
|--------|------|----------|
| BTC | Bitcoin | Crypto |
| ETH | Ethereum | Crypto |
| SOL | Solana | Crypto |
| XAU | Gold | Commodity |
| SPYX | S&P 500 | Index |
| NVDAX | NVIDIA | Stock |
| GOOGLX | Google | Stock |
| TSLAX | Tesla | Stock |
| AAPLX | Apple | Stock |

## Output Example

```
==================================================
  BTC — Bitcoin
==================================================
  Price:           $77,966
  24h Change:      🔴 -0.95%
  Current Vol:     58.4% 🟠 [Elevated]
  Avg Realized:    53.3%
  Forecast Vol:    52.2%
```

## Volatility Levels

| Level | Range | Emoji |
|-------|-------|-------|
| Low | < 20% | 🟢 |
| Moderate | 20-40% | 🟡 |
| Elevated | 40-60% | 🟠 |
| High | 60-80% | 🔴 |
| Extreme | > 80% | 🔴 |

## Use Cases

### 1. Market Overview
```bash
python3 scripts/synth.py --all
```
Get a ranked table of all assets by volatility.

### 2. Trading Signals
- **High forecast → Current low**: Expect volatility spike
- **Low forecast → Current high**: Volatility may decrease
- Use for position sizing and options trading

### 3. Monte Carlo Projections
```bash
python3 scripts/synth.py BTC --simulate --hours 24 --paths 1000
```
Generate probabilistic price ranges using forecast volatility (24h max - Synthdata forecast window).

### 4. Scheduled Reports
Create a cron job for daily Slack/Telegram forecasts (see examples/use-cases.md).

### 5. Risk Alerts
Monitor for assets crossing volat...

README excerpt

# Synthdata Volatility Skill

Query and analyze volatility forecasts from [Synthdata.co](https://synthdata.co) for crypto, commodities, and stock indices.

## Features

- 📊 Real-time volatility data for 9 assets (BTC, ETH, SOL, XAU, stocks)
- 🎯 Forward-looking volatility forecasts
- 📈 Monte Carlo price simulations
- 📉 Comparison tables with visual charts
- 🔔 Alert-ready thresholds

## Requirements

- Python 3.8+
- Synthdata API key (sign up at synthdata.co)

## Quick Start

```bash
export SYNTHDATA_API_KEY=your_key_here
python3 scripts/synth.py BTC
```

## Commands

```bash
# Single asset detail
python3 scripts/synth.py BTC

# Compare multiple assets
python3 scripts/synth.py BTC ETH SOL --compare

# All assets overview
python3 scripts/synth.py --all

# Monte Carlo simulation
python3 scripts/synth.py BTC --simulate --hours 24 --chart

# JSON output for integration
python3 scripts/synth.py BTC --json
```

## Example Output

```
==================================================
  BTC — Bitcoin
==================================================
  Price:           $77,966
  24h Change:      🔴 -0.95%
  Current Vol:     58.4% 🟠 [Elevated]
  Avg Realized:    53.3%
  Forecast Vol:    52.2%
```

## Use Cases

- **Trading**: Use forecast volatility to size positions and set stops
- **Options**: High forecast vol = consider buying options
- **Alerts**: Get notified when volatility spikes
- **Research**: Compare volatility across asset classes
- **Automation**: Daily reports to Slack/Telegram

See `examples/use-cases.md` for detailed integration patterns.

## License

MIT

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