// Licensed under the Apache License, Version 2.0
// © mihakralj
//@version=6
indicator("Quantile Loss (Pinball Loss)", "QuantileLoss", overlay=false)

//@function Calculates Quantile Loss (Pinball Loss)
//@param   actual Series of actual values
//@param   predicted Series of predicted/forecast values
//@param   length Rolling window for averaging
//@param   quantile Quantile value between 0 and 1 (default 0.5)
//@returns Mean quantile loss over the window
quantile_loss(series float actual, series float predicted, simple int length, simple float quantile = 0.5) =>
    // Compute quantile loss for current bar
    float diff = nz(actual, 0.0) - nz(predicted, 0.0)
    float loss = diff >= 0 ? quantile * diff : (quantile - 1.0) * diff

    // Rolling mean of losses
    float result = ta.sma(loss, length)
    result

// ---------- Main loop ----------

// Inputs
i_length = input.int(14, "Length", minval=1)
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")
i_actual = input.source(close, "Actual")
i_predicted = input.source(open, "Predicted")

// Calculation
quantile_value = quantile_loss(i_actual, i_predicted, i_length, i_quantile)

// Plot
plot(quantile_value, "Quantile Loss", color=color.yellow, linewidth=2)
hline(0, "Zero", color=color.gray, linestyle=hline.style_dotted)