Alpha#92
Type:
alpha_92• Category:indicators
Description
Alpha#92 - min of ts_rank decays.
Parameters
| Name | Type | Description | Required | Default |
|---|---|---|---|---|
dataExp | string | price data | no | |
high | string | select the column with highest prices | no | |
low | string | select the column with lowest prices | no | |
close | string | select the column with closing prices | no | |
open | string | select the column with opening prices | no | |
volume | string | select the column with volume | no |
Help
Alpha#92
Description
Alpha#92 is an indicator from Alpha 101, a set of formulaic alphas used in investing strategies. This indicator calculates the minimum of time series ranking (ts_rank) decays.
What does this worker do?
This worker calculates the Alpha#92 indicator, which is defined as the minimum of ts_rank decays. The ts_rank function ranks the input data over time, and the decay function applies a decay factor to the ranked values.
How to interpret the results
The Alpha#92 indicator provides a measure of the minimum decay in the ranked values over time. A lower value indicates a higher decay, while a higher value indicates a lower decay.
Parameters
The following parameters are required to calculate the Alpha#92 indicator:
- dataExp:
price data- Type: DataFrame
- Description: Price data used to calculate the indicator
- high:
select the column with highest prices- Type: string
- Description: Column name with highest prices
- low:
select the column with lowest prices- Type: string
- Description: Column name with lowest prices
- close:
select the column with closing prices- Type: string
- Description: Column name with closing prices
- open:
select the column with opening prices- Type: string
- Description: Column name with opening prices
- volume:
select the column with volume- Type: string
- Description: Column name with volume data
Usage
To use this indicator, simply pass in the required parameters. You can refer to the following GIFs for a step-by-step guide:
Reference
For more information on Alpha 101 and the 101 Formulaic Alphas, please refer to the publication by Zura Kakushadze: