DistinguishLongShortPositions: Boolean;
DistinguishLongShortPositions: System.Boolean;
The DistinguishLongShortPositions property determines whether the model should distinguish between short and long positions.
Available values:
True. Distinguish between long and short positions.
False. Do not distinguish between long and short positions.
The DistinguishLongShortPositions property is used only in the Delta-normal method, that is, IMsValueAtRiskTransform.MethodType = MsValueAtRiskMethodType.DeltaNormal.
Executing the example requires that the repository contains dictionaries with the identifiers:
DIM_INSTRUMENTS. It contains the list of financial instrucments.
DIM_ORGANIZATIONS. It contains the list of organizations.
These dictionaries are used for variable dimensions described below.
The repository should contain a modeling container with the MS_PRIMARY identifier that contains a model with the M_VAR identifier. The container should include variables with identifiers:
V_STOCKPRICES. Variable of financial tools. It contains the DIM_INSTRUMENTS dimension.
V_PORTFOLIO. Variable of portfolio. It contains the DIM_INSTRUMENTS and DIM_ORGANIZATIONS dimensions.
V_VALUEATRISK. Variable to which the results are unloaded. It contains DIM_ORGANIZATIONS.
Add links to the Dimensions, Cubes, Metabase, Ms, Stat system assemblies.
Sub UserProc;
Var
mb: IMetabase;
pMsDescrKey: Integer;
pModel: IMsModel;
pTrans: IMsFormulaTransform;
pInsStub, pPortStub, pVaRStub: IVariableStub;
pOutVar, pPortVar, pInsVar: IMsFormulaTransformVariable;
pOutSlice, pPortSlice, pInsSlice: IMsFormulaTransformSLice;
pDimIns, pDimOrg: IDimensionModel;
pInstIns, pInstOrg: IDimInstance;
pSel: IDimSelection;
pSelSet: IDimSelectionSet;
pFactory: IDimSelectionSetFactory;
pSelector: IMsFormulaTransformSelector;
pFormula: IMsFOrmula;
pVaR: IMsValueAtRiskTransform;
pTerm: IMsFormulaTermInfo;
pBT: IMsValueAtRiskBacktesting;
coo: IMsFormulaTransformCoord;
calc: IMsMethodCalculation;
res: IMsValueAtRiskBacktestingResult;
i: integer;
Begin
mb := MetabaseClass.Active;
pMsDescrKey := mb.ItemById("MS_PRIMARY").Key;
pModel := mb.ItemByIdNamespace("M_VAR", pMsDescrKey).Edit As IMsModel;
pTrans := pModel.Transform;
// Delete all variables from model
pTrans.Inputs.Clear;
pTrans.Outputs.Clear;
pTrans.Series.Clear;
// Set sample and forecast periods
pModel.Period.IdentificationStartDate := DateTime.ComposeDay(2000, 1, 1);
pModel.Period.IdentificationEndDate := DateTime.ComposeDay(2000, 1, 10);
pModel.Period.ForecastStartDate := DateTime.ComposeDay(2000, 1, 11);
pModel.Period.ForecastEndDate := DateTime.ComposeDay(2000, 1, 20);
// Get variables for VaR model
pInsStub := mb.ItemByIdNamespace("V_STOCKPRICES", pMsDescrKey).Bind As IVariableStub;
pPortStub := mb.ItemByIdNamespace("V_PORTFOLIO", pMsDescrKey).Bind As IVariableStub;
pVaRStub := mb.ItemByIdNamespace("V_VALUEATRISK", pMsDescrKey).Bind As IVariableStub;
// Get dimension of financial tools
pInstIns := mb.ItemById("DIM_INSTRUMENTS").Open(Null) As IDimInstance;
pDimIns := pInstIns.Dimension;
// Get dimension of organizations
pInstOrg := mb.ItemById("DIM_ORGANIZATIONS").Open(Null) As IDimInstance;
pDimOrg := pInstOrg.Dimension;
// Add output variable
pOutVar := pTrans.Outputs.Add(pVaRStub);
// Get input variable slice
pFactory := New DimSelectionSetFactory.Create;
pSelSet := pFactory.CreateDimSelectionSet;
pSel := pSelSet.Add(pInstOrg);
pSel.SelectAll;
pOutSlice := pOutVar.Slices.Add(pSelSet);
// Add the variable of portfolio
pPortVar := pTrans.Inputs.Add(pPortStub);
// Get the slice of portfolio
pSelSet.Clear;
pSel := pSelSet.Add(pInstIns);
pSel.SelectAll;
pSel := pSelSet.Add(pInstOrg);
pSel.SelectAll;
pPortSlice := pPortVar.Slices.Add(pSelSet);
// Add variable of financial tools
pInsVar := pTrans.Inputs.Add(pInsStub);
// Get the slice of financial tools
pSelSet.Clear;
pSel := pSelSet.Add(pInstIns);
pSel.SelectAll;
pInsSlice := pInsVar.Slices.Add(pSelSet);
// Set model calculation method
pSelector := pTrans.CreateSelector;
pSelector.Slice := pOutSlice;
pSelector.Level := DimCalendarLevel.Day;
pFormula := pTrans.Transform(pSelector);
pFormula.Kind := MsFormulaKind.ValueAtRisk;
pModel.Kind := MsModelKind.ValueAtRisk;
pFormula.Level := DimCalendarLevel.Day;
pVaR := pFormula.Method As IMsValueAtRiskTransform;
// Set dimensions of tools and organizations
pVaR.InstrumentsDimension := pDimIns;
pVaR.OrganizationsDimension := pDimOrg;
// Set "portfolio"
pTerm := pTrans.CreateTermInfo;
pTerm.Slice := pPortSlice;
pVaR.Portfolio := pTerm;
// Set financial tools
pTerm := pTrans.CreateTermInfo;
pTerm.Slice := pInsSlice;
pVaR.StockPrices := pTerm;
// Set output variable
pTerm := pTrans.CreateTermInfo;
pTerm.Slice := pOutSlice;
pVaR.ValueAtRisk := pTerm;
// Specify VaR calculation method
pVaR.MethodType := MsValueAtRiskMethodType.DeltaNormal;
// Specify confidence limit significance
pVaR.ConfidenceLevel := 0.05;
// Set missing data treatment method
pVaR.UseFillGaps := True;
pVaR.MissingData.Method := MissingDataMethod.SampleAverage;
// Use logarithmic yield and zero mean hypothesis
pVaR.LogarithmicProfit := True;
pVaR.ZeroMean := True;
// Set forecasting horizon
pVaR.ForecastingHorizon := 1;
// Set up parameters of the Delta-normal method:
// Distinguish between short and long positions
pVaR.DistinguishLongShortPositions := True;
// Set value of EMWA lambda
pVaR.LambdaEMWA := 0.95;
// Use the random walk hypothesis
pVaR.RandomWalk := True;
// Set backtesting VaR
pBT := pVaR.Backtesting;
pBT.Enabled := True;
pBT.Observations := 10;
// Set calculation parameters
coo := ptrans.CreateCoord(pTrans.Outputs.Item(0));
calc := pTrans.CreateCalculation;
calc.Period.IdentificationStartDate := pModel.Period.IdentificationStartDate;
calc.Period.IdentificationEndDate:=pModel.Period.IdentificationEndDate;
calc.Period.ForecastStartDate := pModel.Period.ForecastStartDate;
calc.Period.ForecastEndDate := pModel.Period.ForecastEndDate;
// Calculate model
pVaR.Execute(calc, coo);
// display results
For i := 0 To pInstOrg.Elements.Count - 1 Do
res := pBT.Result(i);
Debug.WriteLine("=====Organization: " + pInstOrg.Elements.Name(i) + "=======");
If res <> Null Then
Debug.WriteLine("Confidence level = " + res.ActualConfidenceLevel.ToString);
Debug.WriteLine("Average uncovered risk = " + res.AverageUncoveredRisk.ToString);
Debug.WriteLine("Average unused risk = " + res.AverageUnusedRisk.ToString);
Debug.WriteLine("Binary loss function = " + res.BinaryLossFunction.ToString);
Debug.WriteLine("Multiple to obtain coverage = " + res.CoveringFactor.ToString);
Debug.WriteLine("Quadratic loss function = " + res.QuadraticLossFunction.ToString);
Select Case res.TrafficLight
Case MsValueAtRiskTrafficLight.Green: Debug.WriteLine("Traffic light = is green");
Case MsValueAtRiskTrafficLight.Yellow: Debug.WriteLine("Traffic light = is yellow");
Case MsValueAtRiskTrafficLight.Red: Debug.WriteLine("Traffic light = is red");
End Select;
Debug.WriteLine("Correlation between VaR and actual losses = " + res.VaRLossCorrelation.ToString);
Else
Debug.WriteLine("Result for organization " + i.ToString + " is empty!");
End If;
End For;
(pModel As IMetabaseObject).Save;
End Sub UserProc;
After executing the example, the Value-At-Risk model is created. Parameters of model calculation are set by the Delta-normal method. Model calculation results are displayed in the console window.
See also: