mirror of
https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
92709ef2ed
- Implemented Stochastic Oscillator (%K and %D) in Stoch.cs with streaming and batch processing capabilities. - Added validation tests for the Stochastic Oscillator in Stoch.Validation.Tests.cs, ensuring consistency with Skender.Stock.Indicators. - Created documentation for the Stochastic Oscillator in Stoch.md, detailing its mathematical formula, architecture, parameters, and common pitfalls. - Updated project file to include necessary numeric libraries for highest and lowest calculations.
96 lines
2.9 KiB
Markdown
96 lines
2.9 KiB
Markdown
# BBB: Bollinger %B
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> "Price oscillates, but %B tells you where it lives inside the band."
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Bollinger %B quantifies where the current price sits within Bollinger Bands. A value of `0` is at the lower band, `1` is at the upper band, and `0.5` is centered at the middle band. The value can overshoot outside `[0, 1]` when price pierces the bands.
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## Calculation
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1. Compute the SMA and standard deviation over the lookback period.
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2. Construct upper/lower bands using the standard deviation multiplier.
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3. Normalize the price position within the bands.
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Formula:
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```
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Basis = SMA(source, period)
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StdDev = sqrt(E[x^2] - E[x]^2)
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Upper = Basis + multiplier * StdDev
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Lower = Basis - multiplier * StdDev
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BBB = (Price - Lower) / (Upper - Lower)
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```
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If the band width is zero, BBB returns `0.5` (neutral).
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## Interpretation
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- `BBB = 1.0` → price at upper band (overbought risk)
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- `BBB = 0.0` → price at lower band (oversold risk)
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- `BBB > 1.0` → price above upper band (breakout)
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- `BBB < 0.0` → price below lower band (breakdown)
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## Parameters
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| Name | Type | Default | Range | Description |
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| :--- | :--- | :------ | :---- | :---------- |
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| `period` | `int` | `20` | `>0` | Lookback period for SMA and StdDev. |
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| `multiplier` | `double` | `2.0` | `>0` | Standard deviation multiplier for band width. |
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## API
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```mermaid
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classDiagram
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class Bbb {
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+Name : string
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+WarmupPeriod : int
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+IsHot : bool
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+Update(TValue input, bool isNew) TValue
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+Update(TSeries source) TSeries
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+Prime(ReadOnlySpan~double~ source, TimeSpan? step) void
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+Reset() void
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+Batch(TSeries source, int period, double multiplier) TSeries
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+Batch(ReadOnlySpan~double~ source, Span~double~ output, int period, double multiplier) void
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+Calculate(TSeries source, int period, double multiplier) (TSeries Results, Bbb Indicator)
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}
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```
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## Usage Example
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```csharp
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using QuanTAlib;
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// Initialize
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var bbb = new Bbb(period: 20, multiplier: 2.0);
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foreach (var bar in bars)
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{
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var value = bbb.Update(bar.Close);
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if (bbb.IsHot)
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{
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Console.WriteLine($"{bar.Time}: %B={value.Value:F3}");
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}
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}
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```
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## Performance Profile
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| Metric | Score | Notes |
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| :--- | :--- | :--- |
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| **Throughput** | 9 | O(1) rolling sums and variance. |
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| **Allocations** | 0 | Zero allocations in hot path. |
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| **Complexity** | O(1) | Constant time per update. |
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| **Accuracy** | 10 | Matches Pine reference and standard formula. |
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| **Timeliness** | 7 | Period-length lag similar to SMA. |
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| **Overshoot** | 8 | Can exceed [0, 1] on strong moves. |
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| **Smoothness** | 6 | Moderate smoothing via SMA and StdDev. |
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## Validation
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No direct TA-Lib/Tulip/Skender equivalent exists for Bollinger %B. Validation is performed against the PineScript reference and internal consistency checks (batch vs streaming vs span).
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## Sources
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- John Bollinger, *Bollinger on Bollinger Bands*
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- [PineScript reference](bbb.pine)
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