public JsonResult SpotPriceSimulation(
int[] timeStepsInLevels, double[] priceLevels,
double timeStep, double reversionRate, double volatility,
int numberOfSimulations)
{
if (timeStepsInLevels.Length != priceLevels.Length)
{
throw new Exception("Lengths not consistent");
}
//hourly simulation
var horizon = timeStepsInLevels.Sum() * 24; //
//TODO: add daily/hourly resolution... if it makes sense... but not really.
//estimate an hourly ARMA...
var d = AppData.GetHistoricalSeries(PricesController._timeSeries);
var data = d
.Select(x => x.Value != null ? (double)x.Value : 0) //0 for now, when interpolation is done... etc..
.ToArray();
//just take last 3 years... mhm...
var threeYears = 24 * 7 * 4 * 12 * 3;
if (data.Length > threeYears)
{
data = data.Skip(data.Length - threeYears).Take(threeYears).ToArray();
}
//detrend to make stationary
data = TimeSeries.toStationary(data);
//hourly
//var seasons = new int[] { 24, 24 * 7, 24 * 7 * 4, 24 * 7 * 4 * 6, 24 * 7 * 4 * 12};
//var arSes = new int[] { 1, 2, 24, 25 };
//daily
//var seasons = new int[] { 7, 7*4, 7*4*12 };
//var arSes = new int[] { 1, 7, 7*4 };
//var arma = TimeSeries.ARMASimple2(data, arSes, seasons);
//fitted model from matlab
var arlags = new int[] { 1, 2, 24, 25 };
//var ar = new TimeSeries.LagOp(new double[] { 1.04216, -0.125323, 0.777886, -0.699448 }, arlags);
var malags = new int[] { 24, 168 };
//var ma = new TimeSeries.LagOp(new double[] { -0.44595, 0.175135 }, malags);
//var xarma = TimeSeries.ARMASimple3(ar, ma, 0.166685, 2.80023);
//our fitting procedure.. difference...? not much...
var arma = TimeSeries.ARMASimple2(data, arlags, malags);
arma = TimeSeries.ARMASimple3(arma.AR, arma.MA, arma.Const, volatility);
var inSampleRes = TimeSeries.Infer(arma, data);
var sims = arma.Simulate(numberOfSimulations, horizon, data, inSampleRes);
var hoursSteps = timeStepsInLevels.Select(x => x * 24).ToArray();
var desezonalizedData = Desezonalize(data, 168);
//add the spikes
//Then perform the spike estimation
var spikesThreshold = 1.7;
var spikeIndices = EstimateSpikesOnMovSDs(desezonalizedData, 24, 2, spikesThreshold);
//select hour
var peakHour = 16;
var peakhourData = TakeShortPeriods(data, 1, peakHour, 24);
var peakSpikeIndices = EstimateSpikesOnMovSDs(peakhourData, 7, 2, spikesThreshold);
var distrib = EstimateSpikesDistribution(peakhourData, peakSpikeIndices, Forecast.SpikePreprocess.SimilarDay, spikesThreshold);
//for testing..
var n = new Normal(distrib.Item1.Mean, distrib.Item1.Variance);
var p = new Poisson(distrib.Item2.Lambda * 24);
//replace spikes now...
//TODO: replace at the right hour... yes...
sims = Simulations.spikeSimulationsReplace(sims, p, n);
//fit the forward curve
sims = Simulations.liftSeriesToPriceCurve(sims, hoursSteps, priceLevels);
return(Json(sims));
}
