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https://github.com/mihakralj/QuanTAlib.git
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Miha Kralj
35 lines
1.4 KiB
Plaintext
35 lines
1.4 KiB
Plaintext
// Licensed under the Apache License, Version 2.0
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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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