Lean
$LEAN_TAG$

An Autoregressive Intergrated Moving Average (ARIMA) is a time series model which can be used to describe a set of data. In particular,with Xₜ representing the series, the model assumes the data are of form (after differencing _diffOrder times): More...
Public Member Functions  
AutoRegressiveIntegratedMovingAverage (string name, int arOrder, int diffOrder, int maOrder, int period, bool intercept=true)  
Fits an ARIMA(arOrder,diffOrder,maOrder) model of form (after differencing it _diffOrder times): More...  
AutoRegressiveIntegratedMovingAverage (int arOrder, int diffOrder, int maOrder, int period, bool intercept)  
Fits an ARIMA(arOrder,diffOrder,maOrder) model of form (after differencing it _diffOrder times): More...  
override void  Reset () 
Resets this indicator to its initial state More...  
Public Attributes  
double[]  ArParameters 
Fitted AR parameters (φ terms). More...  
double[]  MaParameters 
Fitted MA parameters (θ terms). More...  
double  Intercept 
Fitted intercept (c term). More...  
override bool  IsReady => _rollingData.IsReady 
Gets a flag indicating when this indicator is ready and fully initialized More...  
Protected Member Functions  
override decimal  ComputeNextValue (IndicatorDataPoint input) 
Forecasts the series of the fitted model one point ahead. More...  
Protected Member Functions inherited from QuantConnect.Indicators.TimeSeriesIndicator  
TimeSeriesIndicator (string name)  
A constructor for a basic Time Series indicator. More...  
Properties  
override int  WarmUpPeriod [get] 
Required period, in data points, for the indicator to be ready and fully initialized. More...  
double  ArResidualError [get] 
The variance of the residuals (Var(ε)) from the first step of TwoStepFit. More...  
double  MaResidualError [get] 
The variance of the residuals (Var(ε)) from the second step of TwoStepFit. More...  
Properties inherited from QuantConnect.Indicators.TimeSeriesIndicator  
abstract int  WarmUpPeriod [get] 
Required period, in data points, for the indicator to be ready and fully initialized. More...  
Properties inherited from QuantConnect.Indicators.IIndicatorWarmUpPeriodProvider  
int  WarmUpPeriod [get] 
Required period, in data points, for the indicator to be ready and fully initialized. More...  
Additional Inherited Members  
Static Public Member Functions inherited from QuantConnect.Indicators.TimeSeriesIndicator  
static double[]  DifferenceSeries (int d, double[] series, out double[] diffHeads) 
Differences a time series d times. More...  
static double[]  InverseDifferencedSeries (double[] series, double[] diffHeads) 
Undoes the differencing of a time series which has been differenced using DifferenceSeries. https://github.com/statsmodels/statsmodels/blob/04f00006a7aeb1c93d6894caa420698400da6c33/statsmodels/tsa/tsatools.py#L758 More...  
static double[][]  LaggedSeries (int p, double[] series, bool includeT=false) 
Returns an array of lagged series for each of {1,...,p} lags. More...  
static List< double >  CumulativeSum (List< double > series, bool reverse=false) 
Returns a series where each spot is taken by the cumulative sum of all points up to and including the value at that spot in the original series. More...  
Protected Attributes inherited from QuantConnect.Indicators.TimeSeriesIndicator  
double[]  _diffHeads 
"Integration" constants More...  
An Autoregressive Intergrated Moving Average (ARIMA) is a time series model which can be used to describe a set of data. In particular,with Xₜ representing the series, the model assumes the data are of form (after differencing _diffOrder times):
Xₜ = c + εₜ + ΣᵢφᵢXₜ₋ᵢ + Σᵢθᵢεₜ₋ᵢ
where the first sum has an upper limit of _arOrder and the second _maOrder.
Definition at line 34 of file AutoRegressiveIntegratedMovingAverage.cs.
QuantConnect.Indicators.AutoRegressiveIntegratedMovingAverage.AutoRegressiveIntegratedMovingAverage  (  string  name, 
int  arOrder,  
int  diffOrder,  
int  maOrder,  
int  period,  
bool  intercept = true 

) 
Fits an ARIMA(arOrder,diffOrder,maOrder) model of form (after differencing it _diffOrder times):
Xₜ = c + εₜ + ΣᵢφᵢXₜ₋ᵢ + Σᵢθᵢεₜ₋ᵢ
where the first sum has an upper limit of _arOrder and the second _maOrder. This particular constructor fits the model by means of TwoStepFit for a specified name.
name  The name of the indicator 
arOrder  AR order (p) – defines the number of past values to consider in the AR component of the model. 
diffOrder  Difference order (d) – defines how many times to difference the model before fitting parameters. 
maOrder  MA order – defines the number of past values to consider in the MA component of the model. 
period  Size of the rolling series to fit onto 
intercept  Whether ot not to include the intercept term 
Definition at line 105 of file AutoRegressiveIntegratedMovingAverage.cs.
QuantConnect.Indicators.AutoRegressiveIntegratedMovingAverage.AutoRegressiveIntegratedMovingAverage  (  int  arOrder, 
int  diffOrder,  
int  maOrder,  
int  period,  
bool  intercept  
) 
Fits an ARIMA(arOrder,diffOrder,maOrder) model of form (after differencing it _diffOrder times):
Xₜ = c + εₜ + ΣᵢφᵢXₜ₋ᵢ + Σᵢθᵢεₜ₋ᵢ
where the first sum has an upper limit of _arOrder and the second _maOrder. This particular constructor fits the model by means of TwoStepFit using ordinary least squares.
arOrder  AR order (p) – defines the number of past values to consider in the AR component of the model. 
diffOrder  Difference order (d) – defines how many times to difference the model before fitting parameters. 
maOrder  MA order (q) – defines the number of past values to consider in the MA component of the model. 
period  Size of the rolling series to fit onto 
intercept  Whether to include an intercept term (c) 
Definition at line 152 of file AutoRegressiveIntegratedMovingAverage.cs.
override void QuantConnect.Indicators.AutoRegressiveIntegratedMovingAverage.Reset  (  ) 
Resets this indicator to its initial state
Definition at line 167 of file AutoRegressiveIntegratedMovingAverage.cs.

protected 
Forecasts the series of the fitted model one point ahead.
input  The input given to the indicator 
Definition at line 178 of file AutoRegressiveIntegratedMovingAverage.cs.
double [] QuantConnect.Indicators.AutoRegressiveIntegratedMovingAverage.ArParameters 
Fitted AR parameters (φ terms).
Definition at line 59 of file AutoRegressiveIntegratedMovingAverage.cs.
double [] QuantConnect.Indicators.AutoRegressiveIntegratedMovingAverage.MaParameters 
Fitted MA parameters (θ terms).
Definition at line 64 of file AutoRegressiveIntegratedMovingAverage.cs.
double QuantConnect.Indicators.AutoRegressiveIntegratedMovingAverage.Intercept 
Fitted intercept (c term).
Definition at line 69 of file AutoRegressiveIntegratedMovingAverage.cs.
override bool QuantConnect.Indicators.AutoRegressiveIntegratedMovingAverage.IsReady => _rollingData.IsReady 
Gets a flag indicating when this indicator is ready and fully initialized
Definition at line 74 of file AutoRegressiveIntegratedMovingAverage.cs.

get 
Required period, in data points, for the indicator to be ready and fully initialized.
Definition at line 79 of file AutoRegressiveIntegratedMovingAverage.cs.

get 
The variance of the residuals (Var(ε)) from the first step of TwoStepFit.
Definition at line 84 of file AutoRegressiveIntegratedMovingAverage.cs.

get 
The variance of the residuals (Var(ε)) from the second step of TwoStepFit.
Definition at line 89 of file AutoRegressiveIntegratedMovingAverage.cs.