Files
go-opt-pricer/models.go

117 lines
3.7 KiB
Go

package main
import (
"math"
"math/rand"
"time"
)
// Option struct that holds all the details of an option
type Option struct {
OptType int64
Strike float64
ExpiryDate time.Time
// Market data
ValueDate time.Time
Spot float64
Rfr float64
Vol float64
Sims int64
// Results
FV float64
Delta float64
Vega float64
Rho float64
Gamma float64
Theta float64
Levels []float64
}
// Single simulation of Geometric Brownian Motion
func gbmSimulation(spot float64, rfr float64, vol float64, tte float64, randNum float64) float64 {
var drift, stoch float64
drift = (rfr - math.Pow(vol, 2)/2) * tte
stoch = vol * math.Pow(tte, 0.5) * randNum
return spot * math.Exp(drift+stoch)
}
// PriceMonteCarlo is the exported method to run the simulations and value
// a vanilla option using Monte Carlo methods
func (opt *Option) PriceMonteCarlo() {
var i int64
var level float64
opt.Levels = make([]float64, opt.Sims)
tte := opt.ExpiryDate.Sub(opt.ValueDate).Hours() / (24 * 365)
rand.Seed(time.Now().UTC().UnixNano())
for i = 0; i < opt.Sims; i++ {
randNum := rand.NormFloat64()
// Base
opt.Levels[i] = gbmSimulation(opt.Spot, opt.Rfr, opt.Vol, tte, randNum)
opt.FV += math.Max((opt.Levels[i]-opt.Strike)*float64(opt.OptType), 0)
// Delta
level = gbmSimulation(opt.Spot+0.0001, opt.Rfr, opt.Vol, tte, randNum)
opt.Delta += math.Max((level-opt.Strike)*float64(opt.OptType), 0)
// Gamma -- TODO: Doesn't look right
level = gbmSimulation(opt.Spot+0.0001, opt.Rfr, opt.Vol, tte, randNum)
opt.Gamma += math.Max((level-opt.Strike)*float64(opt.OptType), 0)
level = gbmSimulation(opt.Spot-0.0001, opt.Rfr, opt.Vol, tte, randNum)
opt.Gamma += math.Max((level-opt.Strike)*float64(opt.OptType), 0)
level = gbmSimulation(opt.Spot, opt.Rfr, opt.Vol, tte, randNum)
opt.Gamma -= 2 * math.Max((level-opt.Strike)*float64(opt.OptType), 0)
// Vega
level = gbmSimulation(opt.Spot, opt.Rfr, opt.Vol+0.0001, tte, randNum)
opt.Vega += math.Max((level-opt.Strike)*float64(opt.OptType), 0)
// Theta
level = gbmSimulation(opt.Spot, opt.Rfr, opt.Vol, tte-1./365, randNum)
opt.Theta += math.Max((level-opt.Strike)*float64(opt.OptType), 0)
// Rho
level = gbmSimulation(opt.Spot, opt.Rfr+0.01, opt.Vol, tte, randNum)
opt.Rho += math.Max((level-opt.Strike)*float64(opt.OptType), 0)
}
df := math.Exp(-opt.Rfr * tte)
opt.FV = opt.FV / float64(opt.Sims) * df
opt.Delta = (opt.Delta/float64(opt.Sims)*df - opt.FV) / 0.0001
opt.Gamma = opt.Gamma / float64(opt.Sims) * df / 1e-8
opt.Vega = (opt.Vega/float64(opt.Sims)*df - opt.FV) / 0.01
opt.Theta = (opt.Theta/float64(opt.Sims)*math.Exp(-opt.Rfr*(tte-1./365)) -
opt.FV) / (1. / 365)
opt.Rho = (opt.Rho/float64(opt.Sims)*math.Exp(-(opt.Rfr+0.01)*tte) - opt.FV)
}
func (opt *Option) PriceClosedForm() {
var d1, d2, tte float64
tte = opt.ExpiryDate.Sub(opt.ValueDate).Hours() / (24 * 365)
d1 = (math.Log(opt.Spot/opt.Strike) + tte*(opt.Rfr+math.Pow(opt.Vol, 2)/2)) /
(opt.Vol * math.Pow(tte, 0.5))
d2 = d1 - (opt.Vol * math.Pow(tte, 0.5))
opt.FV = opt.Spot*NormCDF(d1*float64(opt.OptType))*float64(opt.OptType) -
opt.Strike*math.Exp(-opt.Rfr*tte)*
NormCDF(d2*float64(opt.OptType))*float64(opt.OptType)
opt.Delta = NormCDF(d1)
if opt.OptType == -1 {
opt.Delta -= 1
}
opt.Gamma = 1 / (opt.Spot * opt.Vol * math.Sqrt(tte)) * NormCDF(d1)
opt.Vega = opt.Spot / 100 * math.Pow(tte, 0.5) * NormPDF(d1)
opt.Rho = float64(opt.OptType) * tte * opt.Strike * math.Exp(-opt.Rfr*tte) *
NormCDF(float64(opt.OptType)*d2) / 100
opt.Theta = -float64(opt.OptType)*(opt.Rfr*opt.Strike*math.Exp(-opt.Rfr*tte)*
NormCDF(float64(opt.OptType)*d2)) - (opt.Vol/2*math.Sqrt(tte))*
opt.Spot*NormPDF(float64(opt.OptType)*d1)
}