public async Task<PortfolioPnlCache> GetCurrentAllocatedExposureHistPnl(CarbonClient cc_, bool forcerefresh_ = false)
{
if (m_currentExpBackwards != null && !forcerefresh_)
return m_currentExpBackwards.Value;
var exp = await GetLatestAllocatedExposure(cc_, forcerefresh_);
// if we haven't got exposure
if (exp == null || exp.Item2 == null)
{
m_currentExpBackwards = new TriedObject<PortfolioPnlCache>();
return null;
}
var listOfColumns = new List<string>();
var listOfDailyReturns = new List<DatedDataCollectionGen<double>>();
for (int i = 0; i < exp.Item2.Length; ++i)
{
var exposureName = exp.Item1[i];
var exposure = exp.Item2[i];
if (exposure.IsZero())
continue;
listOfColumns.Add(exposureName);
// get the security master
var secMaster = await SecMasters.Get(exposureName, cc_);
// find equivalent TRS object
var trInstrument = (secMaster == null) ? null : await secMaster.TRInstrument(cc_);
// get TRS object's history
var series = trInstrument == null ? null : await trInstrument.GetTimeSeries(cc_);
if (series == null)
{
Logger.Error(string.Format("Could not find total return series for [{0}]", exposureName), typeof(Portfolio));
continue;
}
var dailyIncrements = series.ToReturns();
if (secMaster.Invert)
dailyIncrements = dailyIncrements.MultiplyBy(-1d);
listOfDailyReturns.Add(dailyIncrements.MultiplyBy(exposure));
}
var con = new ConstructGenGen<DateTime, double>(listOfColumns.ToArray());
for (int i = 0; i < con.ArrayLength; ++i)
con.SetColumnValues(i, listOfDailyReturns[i].Dates, listOfDailyReturns[i].Data);
con.Keys.Sort((a, b) => a.CompareTo(b));
m_currentExpBackwards = new TriedObject<PortfolioPnlCache>(new PortfolioPnlCache(new SysTimeSeries { Data = con }));
return m_currentExpBackwards.Value;
}
private void analyse()
{
if (m_lastApplied == null)
return;
seasAverageNormalized.ClearSeries();
seasProbability.ClearSeries();
var allLevels = m_lastApplied.GetCombined(DataAroundEventField.Filled_Level);
var allDiffs = m_lastApplied.GetCombined(DataAroundEventField.Filled_Daily_Diff);
var subsetLevels = new ConstructGenGen<int, double>(allLevels.ColumnHeadings);
var subsetDiffs = new ConstructGenGen<int, double>(allLevels.ColumnHeadings);
//
// get all the values for the subset that's been defined
//
foreach (var indexPoint in allLevels.Keys)
{
if (indexPoint < m_args.AnalysisStartIndex)
continue;
if (indexPoint > m_args.AnalysisEndIndex)
break;
subsetLevels.SetValues(indexPoint, allLevels.GetValues(indexPoint));
subsetDiffs.SetValues(indexPoint, allDiffs.GetValues(indexPoint));
}
//
// calculate and apply probabilities
//
var probType = ProbabilityCalcType.UpsMinusDownsOverNumber;
var probabilities = new double[subsetDiffs.Keys.Count];
for (int i = 0; i < subsetDiffs.Keys.Count; ++i)
{
var valsForIndexPoint = allDiffs.GetValues(allDiffs.Keys[i]);
probabilities[i] = ProbabilityCalc.CalcProb(valsForIndexPoint, probType);
}
// add probability column chart
seasProbability.AddColumnChart("Probability", subsetLevels.Keys.Select(x => x.ToString()).ToArray(),
probabilities, ProbabilityCalc.GetMaxValue(probType));
seasProbability.AddLegend();
//
// calculate normlized series on subset
//
var normdValues = new ConstructGenGen<int, double>(allLevels.ColumnHeadings);
var keys = subsetLevels.Keys.Select(x => x.ToString()).ToArray();
for(int i=0;i<subsetLevels.ArrayLength;++i)
{
var normd = subsetLevels.GetColumnValues(i).Normalize();
normdValues.SetColumnValues(i, subsetLevels.Keys.ToArray(), normd);
}
//
// calculate average normalized series
//
var averageNorms = new double[normdValues.Keys.Count];
//var dispersionMeasure = new double[normdValues.Keys.Count];
for (int i = 0; i < averageNorms.Length; ++i)
{
var valuesToUse = normdValues.GetValues(normdValues.Keys[i]).Where(x => double.IsNaN(x) == false).ToArray();
averageNorms[i] = valuesToUse.Average();
//dispersionMeasure[i] = Statistics.Stdev(valuesToUse.Select(x=>x-averageNorms[i]).ToArray());
}
//
// normalize the average and display
//
averageNorms = averageNorms.Normalize();
seasAverageNormalized.AddLineChart("Seasonal pattern", keys, averageNorms);
//seasAverageNormalized.AddColumnChart("stdev", keys, dispersionMeasure, dispersionMeasure.Max());
seasAverageNormalized.AddLegend();
}