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lib/trends_FIR/tsf/Tsf.md
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# TSF: Time Series Forecast
| Property | Value |
| ---------------- | -------------------------------- |
| **Category** | Trend (FIR MA) |
| **Inputs** | Source (close) |
| **Parameters** | `period` (default 14) |
| **Outputs** | Single series (Tsf) |
| **Output range** | Tracks input |
| **Warmup** | `period` bars |
### TL;DR
- TSF projects the least-squares regression line one bar forward, providing a statistically grounded forecast of the next bar's value.
- Parameterized by `period` (default 14).
- Output range: Tracks input.
- Requires `period` bars of warmup before first valid output (IsHot = true).
- Validated against TA-Lib, Skender, and Tulip reference implementations where available.
> "The best prediction of the future is the trend that's already in motion — extended by exactly one step."
TSF projects the least-squares regression line one bar forward, providing a statistically grounded forecast of the next bar's value. Unlike simple moving averages that smooth past data, TSF answers the question: "If the current trend continues, where will price be next?" This makes it inherently leading rather than lagging, though the forecast degrades quickly beyond one step.