# yvaty.lat

- **Website:** <https://yvaty.lat>
- **Primary alias:** `yvaty.lat`

## Description

CoinAI Quant is an AI-powered cryptocurrency quant trading platform that combines deep learning with quantitative strategies to help users analyze markets and automate trading. Its tools draw on multiple data sources, including on-chain activity, order flow, sentiment, news, and macro-market correlations. The AI engine provides price predictions, strategy signals, market reports, pattern detection, and alerts for unusual events. Users can test strategies with historical data and simulations that account for fees, slippage, and funding rates, then deploy them in live or paper trading. CoinAI Quant also offers automated execution, portfolio rebalancing, stop-loss and take-profit controls, encrypted API key management, and real-time position and risk monitoring. The platform serves beginners, active traders, and professional teams through Free, Pro, and Ultra subscriptions, with features ranging from basic backtesting and market dashboards to advanced AI models, extensive historical data, multi-account management, and institutional risk tools. API access, educational resources, and customer support are also available. Cryptocurrency trading involves substantial risk, and the platform cautions that past performance does not guarantee future results.

## Industries

- 💰 Finance
- 💰 Investing _(under Finance)_
- 🖥 Computers Electronics and Technology
- 🖥 Blockchain and Cryptocurrency _(under Computers Electronics and Technology)_

## Logos & icons

- logo _(primary)_ — PNG, SVG — [download](https://cdn.brandfetch.io/idhcwIfZiT/w/820/h/820/theme/dark/logo.png?c=1bxid64Mup7aczewSAYMX&t=1791458941713)

## Colors

| Name | Hex | Theme |
| --- | --- | --- |
| Dodger Blue | #2962ff | accent |
| Chathams Blue | #125d75 | dark |
| Cornflower Blue | #5b8def | light |

## Fonts

- Inter — asset _(google)_

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_Source: <https://brandfetch.com/yvaty.lat>_
_See [/llms.txt](/llms.txt) for a full list of agent-readable pages, and [/auth.md](/auth.md) for how agents authenticate._