Sliding Slope

Calculates the linear slope on a given row, looking backwards for a user-defined window of periods.

Pass in a partition_col, an order_col, and a lookback window size.

NOTE: Your data should be a properly formatted timeseries dataset before applying this transformation. In other words, each period should only appear once, and periods considered zero should be imputed with 0 already. NOTE: Slope calculations are notoriously sensitive to large outliers, especially with smaller windows.

Example use case: On daily stock data, calculate SLOPE by TICKER, with a 14-period lookback window.

Parameters

Name	Type	Description	Is Optional
partition_col	column	Grouping column to calculate the slope within.
order_col	column	Column to order rows by when calculating the agg window. Slope automatically sorts ascending.
value_col	column	Column to calulate slope for.
window	int	Number of periods to use as a lookback period, to calculate slope.

Example

ds = rasgo.get.dataset(fqtn="RASGOCOMMUNITY.PUBLIC.ZEPL_DAILY_STOCK_FEATURES")

ds2 = ds.sliding_slope(partition_col = 'TICKER', 
              order_col = 'DATE', 
              value_col = 'CLOSE', 
              window = 14)

Source Code

RasgoTransforms/sliding_slope.sql at main · rasgointelligence/RasgoTransformsGitHub