- OpenBacktesting
- Indicator catalog
- Hilbert trend mode (ta.ht_trendmode)
Hilbert trend mode (ta.ht_trendmode)¶
Distinguish trend and cycle market regimes using a state value.
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.ht_trendmode(self.close)
self.latest_value = None
def next(self):
channel = self.value
if channel.valid[-1]:
self.latest_value = float(channel[-1])
result = Backtest(data, Example).run()
print(result["_strategy"].latest_value)
Call and parameters¶
Register in init(). Read the returned channel in next() after checking valid[-1].
| Parameter | Meaning | Type | Default | Allowed values |
|---|---|---|---|---|
| — | No formula parameters. | — | — | — |
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: close.
| Channel | Meaning |
|---|---|
ht_trendmode |
Hilbert trend mode value |
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.