Signal And Scoring
Definition: Creates a predictive time series for a target asset based on selection of the top scoring inputs.
ensemble(asset, method, daysLookBack, useTopScoreCount)
- asset: the symbol to forecast
- method: scoring method to use
- daysLookBack: the number of previous days to be used in scoring the input rows (default 30)
- useTopScoreCount: the number or percentage of top-ranked rows to retain in the ensemble of rows (default 20 percent)
Return: Single trendline time series derived from inputs
Description: Input to the action is a list of candidate time series. Its size must be at least as great as useTopScoreCount, if useTopScoreCount is a number rather than a percentage.
tl = inputs -> ensemble(asset=BTC, "pl", daysLookBack=3, useTopScoreCount=5)
Definition: This function implements the scoring methods used in Create Trendline, though it does not function in exactly the way that function uses them.
score_signal(target, method, closeonneutral, zerosize)
target: time series for the symbol to forecast
method: scoring method to use
closeonneutral: whether to close positions when the signal enters the neutral zone
zerosize: defines the bounds of the neutral zone (default 0.0)
Return: Time series of accumulated scores
Description: Input to the action is a trendline indicating long or short positions for trading.
btc_asset = BTC.close
scores = tl -> score_signal(btc_asset, "pl")