public double Calculate()
{
// fetch portfolios by using the provider
Portfolios = PortfolioProvider.Portfolios;
// call market data provider and gathering product parameters
ProductParameters = ProductParametersProvider.ProductsParameters;
// look over all portfolios and getting the positions
IEnumerable <KeyValuePair <Product, long> > allTransactions =
Portfolios.SelectMany(x => x.Transactions)
.GroupBy(y => y.Product)
.Select(z => new KeyValuePair <Product, long>(z.Key, z.Sum(x => x.Position)));
Positions = allTransactions.ToDictionary(t => t.Key, t => t.Value);
// foreach product do the montecarlo simulation with the target product parameter
// and multiply it by the position value and calculate the lost value
var lostsValuesByProduct = new Dictionary <string, IEnumerable <double> >();
foreach (var pos in Positions)
{
long position = pos.Value;
ProductParameters parameters = ProductParameters.First(x => x.Product.Equals(pos.Key));
var normalDistribution = new NormalEnumerable();
var input = new MonteCarloInput
{
Parameters = parameters,
Position = position,
};
IEnumerable <double> results = normalDistribution.Take(TotalSimulations)
.Select(alea => StatisticsUtilities.CalculateLoss(input, alea))
.ToList();
lostsValuesByProduct.Add(pos.Key.Name, results);
}
// aggregate the lost value for all products
IList <double> totals = new List <double>();
Func <IList <double>, string, IList <double> > sumList =
(current, key) => Helpers.SumList(current, lostsValuesByProduct[key].ToList());
totals = lostsValuesByProduct.Keys.Aggregate(totals, sumList);
// put prices and positions at the portfolio level
// choose the var at 99% for 1 day
return(StatisticsUtilities.CalculateVar(totals, 0.99));
}
