mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-16 09:38:05 +00:00
docs: update category index files and fix indicator implementations (#58)
This commit is contained in:
+5
-29
@@ -1,36 +1,12 @@
|
||||
# Forecasts
|
||||
|
||||
> "Prediction is very difficult, especially about the future." Niels Bohr
|
||||
> "Prediction is very difficult, especially about the future." Niels Bohr
|
||||
|
||||
Forecasting and predictive models. Unlike reactive indicators that smooth past data, forecasts attempt to project future values. Extrapolation is inherently uncertain. Use with appropriate skepticism and position sizing.
|
||||
|
||||
## Indicator Status
|
||||
## Indicators
|
||||
|
||||
| Indicator | Full Name | Status | Description |
|
||||
| :--- | :--- | :---: | :--- |
|
||||
| [AFIRMA](lib/forecasts/afirma/Afirma.md) | Adaptive FIR Moving Average | | Windowed sinc coefficients. Optimal frequency response. Can extrapolate. |
|
||||
| CFO | Chande Forecast Oscillator | =Ë | Percentage difference between price and linear regression forecast. |
|
||||
| MLP | Multilayer Perceptron | =Ë | Neural network regressor. Nonlinear pattern learning. |
|
||||
| TSF | Time Series Forecast | =Ë | Linear regression projected forward. Standard extrapolation. |
|
||||
|
||||
**Status Key:** Implemented | =Ë Planned
|
||||
|
||||
## Selection Guide
|
||||
|
||||
| Use Case | Recommended | Why |
|
||||
| Indicator | Full Name | Description |
|
||||
| :--- | :--- | :--- |
|
||||
| Smooth extrapolation | AFIRMA | FIR with extrapolation coefficients. Configurable lookahead. |
|
||||
| Linear trend projection | TSF | Simple, interpretable. Works when trend is linear. |
|
||||
| Forecast deviation | CFO | Shows when price diverges from linear forecast. |
|
||||
| Nonlinear patterns | MLP | Neural network learns complex relationships. Requires training. |
|
||||
|
||||
## Forecasting Principles
|
||||
|
||||
| Aspect | Reality | Implication |
|
||||
| :--- | :--- | :--- |
|
||||
| Extrapolation risk | Markets are non-stationary | Short horizons more reliable |
|
||||
| Model uncertainty | All models are wrong | Use ensemble or confidence intervals |
|
||||
| Regime changes | Past patterns may not repeat | Monitor forecast errors |
|
||||
| Overfitting | Complex models fit noise | Prefer simple models when possible |
|
||||
|
||||
Forecasting is not prediction. It is disciplined extrapolation of patterns that may or may not persist.
|
||||
| [AFIRMA](lib/forecasts/afirma/Afirma.md) | Adaptive FIR Moving Average | Windowed sinc coefficients. Optimal frequency response. Can extrapolate. |
|
||||
| MLP | Multilayer Perceptron | Neural network regressor. Nonlinear pattern learning. |
|
||||
|
||||
Reference in New Issue
Block a user