对于日间交易者和量化投资者
Vast Rijpendom's model observes your orders, position size and response to drawdowns, and continuously calibrates the system's risk tolerance accordingly. No fixed profile, but an allocation logic that moves with the market and your behavior.
The overview below shows the signals and quality indicators that are continuously monitored, from processing speed to the spread around each prediction.
每次市场更新的平均处理时间，在过去一千个价格变动中测量。
Bandwidth around the point forecast under current market volatility.
Internal consistency score based on cross-validation over recent market regimes.
当前在模型监控范围内的仪器数量。
View illustrating the processing speed of the platform.这不是当前的交易建议，也不反映实时市场状况。
The system starts with a conservative base setting and then builds a risk profile from your actual decisions: position size, holding time and the way you respond to losses.每一次行为变化都被视为新证据，而不是既定模型的例外。
Dynamic allocation means that the allocation between positions shifts once the model determines that your risk tolerance has changed, for example after a series of losses or increased volatility.最终的控制权仍在您手中：模型提出限制，您确认或更改它们。
下表基于具有历史市场数据的示例场景，将手动分析与 Vast Rijpendom 模型进行了比较。
| 方法 | Error Reduction Rate | Time to Insight |
|---|---|---|
| 手动分析 | Reference value | 每个周期 45–90 分钟 |
| Fixed Maturity AI | 偏差幅度降低高达 20%* | 2分钟以内 |
误差减少率衡量的是与手动估计相比，预测结果与实际结果之间偏差的减少程度。 Time-to-Insight measures the time between new market data becoming available and a detailed recommendation.
* 基于与历史市场数据的模拟比较；不保证未来的结果。使用的数据源：公开市场数据以及您自己的交易历史记录（如果提供）。模型结果未经外部审核。
该集成专为更喜欢通过 API 而不是手动配置屏幕进行工作的技术用户而设计。
通过 REST 端点或 Web 套接字源连接您的代理或数据环境。沙盒环境可直接通过 /v1/sandbox。
定义模型可以运行的框架：最大头寸规模、允许的工具和硬停止限制。
将网络钩子连接到您自己的系统或通过以下方式将信号直接传输到您的订单执行 /v1/webhooks。
Technical questions we receive most often from traders who want to understand the model before deploying it.
交易数据以加密方式存储，仅用于校准您的风险状况。 Data is not shared with third parties for marketing purposes and remains accessible for export at your request.
每条建议都显示了导致该信号的潜在因素，包括波动性、动量和您自己的风险参数的加权贡献。 You not only see the outcome, but also the reasoning behind it.
Processing time is typically between 10 and 25 milliseconds, depending on the complexity of the instrument and the load on the feed at the time.
是的。 Every allocation change stays within the limits you set, and you can pause or roll back the automation at any time.