Documentation

chandeMomentumOscillator() function

chandeMomentumOscillator() applies the technical momentum indicator developed by Tushar Chande to input data.

The Chande Momentum Oscillator (CMO) indicator does the following:

  1. Determines the median value of the each input table and calculates the difference between the sum of rows with values greater than the median and the sum of rows with values lower than the median.
  2. Divides the result of step 1 by the sum of all data movement over a given time period.
  3. Multiplies the result of step 2 by 100 and returns a value between -100 and +100.

Output tables

For each input table with x rows, chandeMomentumOscillator() outputs a table with x - n rows.

Function type signature
(<-tables: stream[A], n: int, ?columns: [string]) => stream[B] where A: Record, B: Record
  • Copy
  • Fill window

For more information, see Function type signatures.

Parameters

n

(Required) Period or number of points to use in the calculation.

columns

List of columns to operate on. Default is ["_value"].

tables

Input data. Default is piped-forward data (<-).

Examples

Apply the Chande Momentum Oscillator to input data

import "sampledata"

sampledata.int()
    |> chandeMomentumOscillator(n: 2)
  • Copy
  • Fill window

Was this page helpful?

Thank you for your feedback!


The future of Flux

Flux is going into maintenance mode. You can continue using it as you currently are without any changes to your code.

Read more

InfluxDB 3 Core and Enterprise are now in Beta

InfluxDB 3 Core and Enterprise are now available for beta testing, available under MIT or Apache 2 license.

InfluxDB 3 Core is a high-speed, recent-data engine that collects and processes data in real-time, while persisting it to local disk or object storage. InfluxDB 3 Enterprise is a commercial product that builds on Core’s foundation, adding high availability, read replicas, enhanced security, and data compaction for faster queries. A free tier of InfluxDB 3 Enterprise will also be available for at-home, non-commercial use for hobbyists to get the full historical time series database set of capabilities.

For more information, check out: