// Licensed under the Apache License, Version 2.0
// © mihakralj
//@version=6
indicator("Mean Relative Absolute Error", "MRAE", overlay=false)

//@function Calculates Mean Relative Absolute Error
//@param   actual Series of actual values
//@param   predicted Series of predicted/forecast values
//@param   length Rolling window for averaging
//@returns MRAE value (0 = perfect, 1 = 100% error)
mrae(series float actual, series float predicted, simple int length) =>
    float epsilon = 1e-10

    // Compute relative absolute error for current bar
    float absActual = math.abs(nz(actual, 1.0))
    float absError = math.abs(nz(actual, 0.0) - nz(predicted, 0.0))
    float relError = absActual > epsilon ? absError / absActual : 0.0

    // Rolling mean of relative errors
    float result = ta.sma(relError, length)
    result

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

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

// Calculation
mrae_value = mrae(i_actual, i_predicted, i_length)

// Plot
plot(mrae_value, "MRAE", color=color.yellow, linewidth=2)
hline(0, "Perfect", color=color.green, linestyle=hline.style_dotted)
hline(1, "100% Error", color=color.red, linestyle=hline.style_dotted)