public DiscretizedBarrierOption(BarrierOption.Arguments args, StochasticProcess process, TimeGrid grid = null)
{
arguments_ = args;
vanilla_ = new DiscretizedVanillaOption(arguments_, process, grid);
Utils.QL_REQUIRE(args.exercise.dates().Count > 0, () => "specify at least one stopping date");
stoppingTimes_ = new InitializedList <double>(args.exercise.dates().Count);
for (int i = 0; i < stoppingTimes_.Count; ++i)
{
stoppingTimes_[i] = process.time(args.exercise.date(i));
if (grid != null && !grid.empty())
{
// adjust to the given grid
stoppingTimes_[i] = grid.closestTime(stoppingTimes_[i]);
}
}
}
public override void calculate()
{
DayCounter rfdc = process_.riskFreeRate().link.dayCounter();
DayCounter divdc = process_.dividendYield().link.dayCounter();
DayCounter voldc = process_.blackVolatility().link.dayCounter();
Calendar volcal = process_.blackVolatility().link.calendar();
double s0 = process_.stateVariable().link.value();
Utils.QL_REQUIRE(s0 > 0.0, () => "negative or null underlying given");
double v = process_.blackVolatility().link.blackVol(arguments_.exercise.lastDate(), s0);
Date maturityDate = arguments_.exercise.lastDate();
double r = process_.riskFreeRate().link.zeroRate(maturityDate, rfdc, Compounding.Continuous, Frequency.NoFrequency).rate();
double q = process_.dividendYield().link.zeroRate(maturityDate, divdc, Compounding.Continuous, Frequency.NoFrequency).rate();
Date referenceDate = process_.riskFreeRate().link.referenceDate();
// binomial trees with constant coefficient
var flatRiskFree = new Handle <YieldTermStructure>(new FlatForward(referenceDate, r, rfdc));
var flatDividends = new Handle <YieldTermStructure>(new FlatForward(referenceDate, q, divdc));
var flatVol = new Handle <BlackVolTermStructure>(new BlackConstantVol(referenceDate, volcal, v, voldc));
PlainVanillaPayoff payoff = arguments_.payoff as PlainVanillaPayoff;
Utils.QL_REQUIRE(payoff != null, () => "non-plain payoff given");
double maturity = rfdc.yearFraction(referenceDate, maturityDate);
StochasticProcess1D bs =
new GeneralizedBlackScholesProcess(process_.stateVariable(), flatDividends, flatRiskFree, flatVol);
TimeGrid grid = new TimeGrid(maturity, timeSteps_);
T tree = FastActivator <T> .Create().factory(bs, maturity, timeSteps_, payoff.strike());
BlackScholesLattice <T> lattice = new BlackScholesLattice <T>(tree, r, maturity, timeSteps_);
DiscretizedVanillaOption option = new DiscretizedVanillaOption(arguments_, process_, grid);
option.initialize(lattice, maturity);
// Partial derivatives calculated from various points in the
// binomial tree (Odegaard)
// Rollback to third-last step, and get underlying price (s2) &
// option values (p2) at this point
option.rollback(grid[2]);
Vector va2 = new Vector(option.values());
Utils.QL_REQUIRE(va2.size() == 3, () => "Expect 3 nodes in grid at second step");
double p2h = va2[2]; // high-price
double s2 = lattice.underlying(2, 2); // high price
// Rollback to second-last step, and get option value (p1) at
// this point
option.rollback(grid[1]);
Vector va = new Vector(option.values());
Utils.QL_REQUIRE(va.size() == 2, () => "Expect 2 nodes in grid at first step");
double p1 = va[1];
// Finally, rollback to t=0
option.rollback(0.0);
double p0 = option.presentValue();
double s1 = lattice.underlying(1, 1);
// Calculate partial derivatives
double delta0 = (p1 - p0) / (s1 - s0); // dp/ds
double delta1 = (p2h - p1) / (s2 - s1); // dp/ds
// Store results
results_.value = p0;
results_.delta = delta0;
results_.gamma = 2.0 * (delta1 - delta0) / (s2 - s0); //d(delta)/ds
results_.theta = Utils.blackScholesTheta(process_,
results_.value.GetValueOrDefault(),
results_.delta.GetValueOrDefault(),
results_.gamma.GetValueOrDefault());
}