private static double getOverallStatValue(SwapsSummaryRow v, DateTime date_)
{
var stats = v.Instrument.Stats.RollingStats;
var instrumentValues = stats.GetValues(date_);
if (instrumentValues == null)
{
Logger.Error(
string.Format("could not get stats for date '{0}' on instrument '{1}'", date_.ToString("dd-MMM-yyyy"), v.Inst),
typeof(RatesHelperMethods));
return 0d;
}
var contributions = Singleton<CentralSwitches>.Instance.StatContributions;
double statValue = 0d;
foreach (var contribution in contributions)
{
var handlingType = PossibleStatColumns.First(x => x.Item1 == contribution.Field).Item2;
switch (handlingType)
{
case StatContributionType.Value:
{
statValue += (contribution.Allocation * instrumentValues[(int)contribution.Field]);
}
break;
case StatContributionType.PercentileAbs:
{
statValue += (contribution.Allocation * (Math.Abs(instrumentValues[(int)contribution.Field] - 0.5d) * 2d));
}
break;
case StatContributionType.Carry:
{
var cry = instrumentValues[(int)contribution.Field];
var lvlP = instrumentValues[(int)StatCols.Values_Percentile_1Y];
statValue += (contribution.Allocation *
(Sign(lvlP - 0.5d) * -Sign(cry) * Math.Abs(cry)));
}
break;
}
}
return statValue;
}
public static void RebuildOverallStat(SwapsSummaryRow v)
{
v.CombStat = getOverallStatValue(v, v.Instrument.Stats.RollingStats.Dates.Last());
}
public static DatedDataCollectionGen<double> GetHistoricalStatSeries(SwapsSummaryRow row_)
{
if (row_ == null) return null;
var con = row_.Instrument.Stats.RollingStats;
var values = new double[con.Dates.Count];
for (int i = 0; i < values.Length; ++i)
{
values[i] = getOverallStatValue(row_, con.Dates[i]);
}
return new DatedDataCollectionGen<double>(con.Dates.ToArray(), values);
}
public static Instrument GetRegressionCandidate(SwapsSummaryRow instrument_, RegressionCandidate candidateType_)
{
string curve = instrument_.GetInstrument().CurveName;
// for the futures curves, the regressor is the swap curve
switch (curve)
{
case CurveNames.EDCurve:
curve = CurveNames.USD3M;
break;
case CurveNames.ERCurve:
curve = CurveNames.EUR6M;
break;
case CurveNames.L_Curve:
curve = CurveNames.GBP6M;
break;
}
//if (instrument_.Inst.Contains("USD") || instrument_.Inst.Contains(CurveNames.EDCurve))
// curve = CurveNames.USD3M;
//else if (instrument_.Inst.Contains("EUR") || instrument_.Inst.Contains(CurveNames.ERCurve) )
// curve = CurveNames.EUR6M;
//else if (instrument_.Inst.Contains("GBP") || instrument_.Inst.Contains(CurveNames.L_Curve) )
// curve = CurveNames.GBP6M;
//else if (instrument_.Inst.Contains("JPY"))
// curve = CurveNames.JPY6M;
//else if (instrument_.Inst.Contains("CAD"))
// curve = CurveNames.CAD6M;
//else
// throw new NotSupportedException("Need to implement for unknown curve");
Instrument ret = null;
switch (candidateType_)
{
case RegressionCandidate.Bonds2s:
{
ret = xYyY.Get(curve, 0, 2);
}
break;
case RegressionCandidate.Bonds5s:
{
ret = xYyY.Get(curve, 0, 5);
}
break;
case RegressionCandidate.Bonds10s:
{
ret = xYyY.Get(curve, 0, 10);
}
break;
case RegressionCandidate.Bonds30s:
{
ret = xYyY.Get(curve, 0, 30);
}
break;
case RegressionCandidate.TwosFives:
{
ret = CurveSwap.Get(curve, PointDef.Create(0, 5), PointDef.Create(0, 2));
}
break;
case RegressionCandidate.TwosTens:
{
ret = CurveSwap.Get(curve, PointDef.Create(0, 10), PointDef.Create(0, 2));
}
break;
case RegressionCandidate.FivesTens:
{
ret = CurveSwap.Get(curve, PointDef.Create(0, 10), PointDef.Create(0, 5));
}
break;
case RegressionCandidate.FivesThirties:
{
ret = CurveSwap.Get(curve, PointDef.Create(0, 30), PointDef.Create(0, 5));
}
break;
case RegressionCandidate.TensThirties:
{
ret = CurveSwap.Get(curve, PointDef.Create(0, 30), PointDef.Create(0, 10));
}
break;
case RegressionCandidate.TwosFivesTens:
{
ret = ButterflySwap.Get(curve, PointDef.Create(0, 2), PointDef.Create(0, 5),
PointDef.Create(0, 10));
}
break;
case RegressionCandidate.FivesSevensTens:
{
ret = ButterflySwap.Get(curve, PointDef.Create(0, 5), PointDef.Create(0, 7),
PointDef.Create(0, 10));
}
break;
case RegressionCandidate.FivesTensThirties:
{
ret = ButterflySwap.Get(curve, PointDef.Create(0, 5), PointDef.Create(0, 10),
PointDef.Create(0, 30));
}
break;
default:
{
throw new NotSupportedException(string.Format("{0} regressionCandidate not yet implemented.", candidateType_));
}
}
return ret;
}
public static void UpdateThisWithCentralOptions(SwapsSummaryRow summaryRow_)
{
try
{
var lin = DoRegression(summaryRow_,
GetRegressionCandidate(summaryRow_, Singleton<CentralSwitches>.Instance.RegressionArgs.Dependent),
Singleton<CentralSwitches>.Instance.RegressionArgs.NumberOfDays, true);
if (lin != null)
{
//summaryRow_.Beta = lin.ParameterEstimates[1].Value;
summaryRow_.SetRegressionREsiduals(new DatedDataCollectionGen<double>(summaryRow_.Instrument.A_Prices.Dates.SliceLast(Singleton<CentralSwitches>.Instance.RegressionArgs.NumberOfDays),
lin.Residuals.ToArray()));
var anova = new NMathStats.LinearRegressionAnova(lin);
summaryRow_.RSquared = anova.RSquared;
}
}
catch (Exception e)
{
Logger.Error(string.Format("Error updating regression stats for {0}", summaryRow_.ToString()),
typeof (RegressionHelper), e);
}
}
public static void ShowRegression(SwapsSummaryRow row_)
{
var regARgs = Singleton<CentralSwitches>.Instance.RegressionArgs;
var regressionCandidate = GetRegressionCandidate(instrument_: row_,
candidateType_: regARgs.Dependent);
var title = string.Format("{0} = beta ({1}) + c", row_.Inst, regressionCandidate.ToString());
ReturnsEval.RegressionsAnalysis analysis = new RegressionsAnalysis(title);
analysis.Dependent = new RegressionsDataSeriesWrapper(row_.Instrument.A_Prices, 0);
analysis.AddIndependentSeries(regressionCandidate.A_Prices, 0, regressionCandidate.ToString());
analysis.AddIntercept = true;
analysis.WindowLength = Singleton<CentralSwitches>.Instance.RegressionArgs.NumberOfDays;
analysis.Evaluate();
ReturnsEvalDisplay.RegressionResultsDisplay rd = new RegressionResultsDisplay();
rd.Bind(analysis);
SI.Controls.LookFeel.ProcessControl(rd);
var form = rd.DisplayInShowForm(title);
form.Icon = SI.Controls.Util.BmpToIcon(RatesSpreadResources.keyImage);
}
public static NMathStats.LinearRegression DoRegression(SwapsSummaryRow summaryRow_, Instrument regressAgainstThis_, int numDays_ = 252, bool withIntercept_=true)
{
var ys = summaryRow_.GetRawStatSeries(StatCols.Values);
if (ys.Length < numDays_)
return null;
ys = ys.GetEndValues(numDays_);
var xs = regressAgainstThis_.A_Prices.Data.Slice(regressAgainstThis_.A_Prices.Length - numDays_, numDays_);
NMathCore.DoubleVector yV = new NMathCore.DoubleVector(ys.Data);
NMathCore.DoubleMatrix matrix = new NMathCore.DoubleMatrix(xs.ToColumn());
var lin = new NMathStats.LinearRegression(obs: yV, A: matrix, addIntercept: withIntercept_);
return lin;
}
