Candle z-score (ta.cdl_z)

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Standardize open, high, low, and close separately to measure each price's deviation from its rolling mean.

Indicator catalog · How to use indicators

Run this example

This complete script uses bundled data. It observes the selected output without placing trades.

import numpy as np
from openbacktesting import Backtest, Strategy
from openbacktesting.test import GOOG

data = GOOG.copy()

class Example(Strategy):
    def init(self):
        self.value = self.ta.cdl_z()
        self.latest_value = None

    def next(self):
        channel = self.value.open
        if channel.valid[-1]:
            self.latest_value = float(channel[-1])

result = Backtest(data, Example).run()
print(result["_strategy"].latest_value)

Call and parameters

self.ta.cdl_z(*, length=30, ddof=1, inputs=None, backend=None, required_outputs=None)

Register in init(). Read the returned channel in next() after checking valid[-1].

Parameter	Meaning	Type	Default	Allowed values
length	Calculation window in observations.	int	30	Minimum: 2
ddof	Degrees of freedom subtracted from the variance denominator.	int	1	Minimum: 0

source/named source arguments accept a column name or same-run single-channel handle. Alternatively, inputs maps each input below to a column or handle. backend selects a supported implementation; required_outputs selects channels for readiness diagnostics. See shared arguments and handles.

Inputs and outputs

Required inputs: open_, high, low, close.

Channel	Meaning
open	Open output
high	High output
low	Low output
close	Close output

Reading values safely

Insufficient history or missing inputs can make a channel invalid. Check that channel's valid mask; ready is diagnostic and never suppresses next(). Multi-output results may have different valid channels on the same bar.

Zero can be a valid non-triggered pattern; validity is separate from its score. A score is not an order or a guaranteed direction signal.

Indicator catalog · Custom calculations