Schaff Trend Cycle
get_stc(quotes, cycle_periods=10, fast_periods=23, slow_periods=50)
||Iterable[Quote]||Iterable(such as list or an object having
• Need help with pandas.DataFrame?
||int, default 10||Number of periods (
||int, default 23||Number of periods (
||int, default 50||Number of periods (
Historical quotes requirements
You must have at least
S+C+100 worth of
quotes, whichever is more, to cover the convergence periods. Since this uses a smoothing technique, we recommend you use at least
S+C+250 data points prior to the intended usage date for better precision.
quotes is an
Iterable[Quote] collection of historical price quotes. It should have a consistent frequency (day, hour, minute, etc). See the Guide for more information.
- This method returns a time series of all available indicator values for the
STCResultsis just a list of
- It always returns the same number of elements as there are in the historical quotes.
- It does not return a single incremental indicator value.
- The first
S+Cslow periods will have
Nonevalues since there’s not enough data to calculate.
Convergence warning: The first
S+C+250periods will have decreasing magnitude, convergence-related precision errors that can be as high as ~5% deviation in indicator values for earlier periods.
||float, Optional||Schaff Trend Cycle|
See Utilities and Helpers for more information.
from stock_indicators import indicators # This method is NOT a part of the library. quotes = get_history_from_feed("SPY") # Calculate STC(12,26,9) results = indicators.get_stc(quotes, 10, 23, 50)
About Schaff Trend Cycle
Created by Doug Schaff, Schaff Trend Cycle is a stochastic oscillator view of two converging/diverging exponential moving averages (a.k.a MACD). [Discuss]