mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-07-28 01:37:43 +00:00
Miha Kralj
24e86d762a
- Updated BBWN, BBWP, CCV, CV, CVI, EWMA, GKV, HLV, HV, Jvolty, JVOLTYN, MASSI, NATR, RSV, RV, RVI, TR, UI, VOV, VR, YZV indicators with documentation links. - Added documentation links for Aberration, Acceleration Bands, Andrews' Pitchfork, Adaptive Price Zone, ATR Bands, Bollinger Bands, Center of Gravity, Donchian Channels, Decay Min-Max Channel, Detrended Synthetic Price, EACP, EBSW, HOMOD, Jurik Volatility Bands, Keltner Channel, MA Envelope, Min-Max Channel, Price Channel, Regression Channels, Standard Deviation Channel, Stoller Average Range Channel, Super Trend Bands, Ultimate Bands, Ultimate Channel, VWAP Bands, and VWAP with Standard Deviation Bands.
35 lines
1.4 KiB
Plaintext
35 lines
1.4 KiB
Plaintext
// The MIT License (MIT)
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// © mihakralj
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//@version=6
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indicator("Quantile Loss (Pinball Loss)", "QuantileLoss", overlay=false)
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//@function Calculates Quantile Loss (Pinball Loss)
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//@param actual Series of actual values
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//@param predicted Series of predicted/forecast values
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//@param length Rolling window for averaging
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//@param quantile Quantile value between 0 and 1 (default 0.5)
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//@returns Mean quantile loss over the window
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quantile_loss(series float actual, series float predicted, simple int length, simple float quantile = 0.5) =>
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// Compute quantile loss for current bar
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float diff = nz(actual, 0.0) - nz(predicted, 0.0)
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float loss = diff >= 0 ? quantile * diff : (quantile - 1.0) * diff
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// Rolling mean of losses
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float result = ta.sma(loss, length)
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result
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// ---------- Main loop ----------
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// Inputs
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i_length = input.int(14, "Length", minval=1)
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i_quantile = input.float(0.5, "Quantile", minval=0.01, maxval=0.99, step=0.05, tooltip="0.5=median (MAE), >0.5=penalize under-prediction, <0.5=penalize over-prediction")
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i_actual = input.source(close, "Actual")
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i_predicted = input.source(open, "Predicted")
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// Calculation
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quantile_value = quantile_loss(i_actual, i_predicted, i_length, i_quantile)
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// Plot
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plot(quantile_value, "Quantile Loss", color=color.yellow, linewidth=2)
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hline(0, "Zero", color=color.gray, linestyle=hline.style_dotted)
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