> For the complete documentation index, see [llms.txt](https://traiex.gitbook.io/whitepaper/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://traiex.gitbook.io/whitepaper/ai-services/ai-trading.md).

# AI Trading

Optional BTC and ETH Spot automation through Base and Pro, with capital controls and real-time user supervision.

AI Trading is an optional service for automated BTC and ETH Spot trading without leverage. The user selects a subscription, assigns capital, sets the available parameters, and launches a strategy. The service manages trades within that scope, with real-time visibility and user intervention available throughout operation.

## Base and Pro

Base and Pro share the same strategic foundation for BTC and ETH Spot trading. Base provides the standard implementation; Pro uses greater AI resources and a more advanced implementation of that foundation.

| Strategy | Operating since | Implementation                                            |
| -------- | --------------- | --------------------------------------------------------- |
| Base     | November 2024   | Standard implementation of the shared trading foundation  |
| Pro      | November 2025   | Expanded implementation supported by greater AI resources |

Both strategies use the configuration model, exposure limit, and protective-stop rules below. The subscription determines strategy availability and the capital that can be assigned.

## Allocation and Exposure

The nominal subscription limit covers the combined capital assigned to Base and Pro. Accumulated trading profit can extend the capital used within the allowance described in Subscriptions and Daily Profit Sharing. Each strategy uses no more than 50% of its own assigned capital for aggregate trading exposure across its trades. Manual positions and other account balances are outside the AI subscription limit.

Assigned capital is the pool available to a strategy; deployed capital is the portion placed into the market. The deployment limit leaves part of the allocation uncommitted. Market movements, execution, and costs determine the outcome of the deployed portion.

## Trade Windows and Protective Stops

Typical holding periods range from one to thirty minutes, with most trades held for approximately fifteen minutes. This describes the usual trading window, not a contractual deadline for every position. Market conditions and the position's management state affect its duration.

Protective stops are configured at a maximum intended distance of 1.5% from entry. Rapid movements, gaps, limited liquidity, or service interruptions can cause execution beyond the intended level. The stop is a position-management rule, not a guaranteed maximum loss. Costs also affect the final result.

## Supervision and Intervention

Users can inspect trading activity and capital in real time and adjust positions and settings during operation. Capital remains accessible through account controls; open orders and positions affect the amount available for another operation. Transfers and withdrawals follow the applicable processing and account conditions.

## Stop and Existing Positions

Stop prevents new trades without immediately liquidating existing positions. Open trades remain managed, and the user can inspect, adjust, or close them.

A stopped strategy can therefore retain market exposure. The typical holding window does not create an automatic closure deadline after Stop.

## Operating History

Base has recorded a positive monthly realized trading result in every month since its November 2024 launch. Monthly performance is measured on the last day of the month using actual results from closed trades, accounting for all costs. Deposits and withdrawals are excluded from trading performance, and unrealized changes in open positions are not included in this monthly measure.

Historical performance does not establish the result of every user's participation period or predict future returns. Allocation, costs, open positions, and the timing of participation affect an individual outcome.

## Related reading

* [Subscriptions and Daily Profit Sharing](https://traiex.gitbook.io/whitepaper/ai-services/subscriptions-and-daily-profit-sharing)
* [Risks and Terms](https://traiex.gitbook.io/whitepaper/development-and-reference/risks-and-terms)