public static double beta_black_normal_vol(double beta, double F, double K, double T, double sigma)
{
var optType = OptionType.Put; // F > K ? OptionType.Put : OptionType.Call;
var bbPrice = beta_black(beta, optType, F, K, T, sigma);
try
{
return(ClosedForm.ibachelier(optType, F, K, T, bbPrice));
}
catch (Exception e)
{
FS.WithInfo(e, $"beta ={beta}, optType = {optType}, F = {F}, K = {K}, T = {T}, sigma = {sigma}, bbPrice = {bbPrice}");
throw;
}
}
public static double black76(OptionType optType, double F, double K, double sdev)
{
var num = optType.ToEpsilon();
if (sdev < 0.0)
{
throw FS.FailWith($"sdev must be positive. Got {sdev}");
}
if (sdev == 0.0 || K <= 0.0)
{
return(Math.Max(num * (F - K), 0.0));
}
else
{
var num2 = (Math.Log(F / K) + 0.5 * sdev * sdev) / sdev;
var num3 = num2 - sdev;
return(num * (F * SpecialFunction.cdf_normal(num * num2) -
K * SpecialFunction.cdf_normal(num * num3)));
}
}
public static double beta_black(double beta, OptionType optType, double F, double K, double T, double sigma)
{
if (T < 0.0)
{
throw FS.FailWith($"T < 0 not allowed, {T}");
}
if (sigma < 0.0)
{
throw FS.FailWith($"sigma < 0 not allowed {sigma}");
}
var stdev = sigma * Math.Sqrt(T);
if (stdev == 0.0)
{
return(Math.Max(optType.ToEpsilon() * (F - K), 0.0));
}
var mu = inv_m1_beta_black(beta, F, stdev);
var d = (inv_g(beta, K) - mu) / stdev;
var t1 = K * SpecialFunction.cdf_normal(d);
var t2 = beta_black_trunc(beta, mu, stdev, d);
var put = t1 - t2;
var intrinsic = Math.Max(optType.ToEpsilon() * (F - K), 0.0);
if (optType == OptionType.Put)
{
return(Math.Max(put, intrinsic));
}
else if (optType == OptionType.Call)
{
return(Math.Max(put + F - K, intrinsic));
}
else
{
throw FS.E_CASE(optType);
}
}
private static double lambert_w_boost(double z)
{
if (z < 6.0)
{
throw FS.FailWith("require(z > 6)");
}
else if (z < 18)
{
// 6 < z < 18
// Max error in interpolated form: 1.985e-19
const double offset = 1.80937194824218750e+00;
double[] P =
{
-1.80690935424793635e+00,
-3.66995929380314602e+00,
-1.93842957940149781e+00,
-2.94269984375794040e-01,
1.81224710627677778e-03,
2.48166798603547447e-03,
1.15806592415397245e-04,
1.43105573216815533e-06,
3.47281483428369604e-09
};
double[] Q =
{
1.00000000000000000e+00,
2.57319080723908597e+00,
1.96724528442680658e+00,
5.84501352882650722e-01,
7.37152837939206240e-02,
3.97368430940416778e-03,
8.54941838187085088e-05,
6.05713225608426678e-07,
8.17517283816615732e-10
};
return(offset + boost_math_tools_evaluate_rational(P, Q, z));
}
else if (z < 9897.12905874) // 2.8 < log(z) < 9.2
{
// Max error in interpolated form: 1.195e-18
double Y = -1.40297317504882812e+00;
double[] P =
{
1.97011826279311924e+00,
1.05639945701546704e+00,
3.33434529073196304e-01,
3.34619153200386816e-02,
-5.36238353781326675e-03,
-2.43901294871308604e-03,
-2.13762095619085404e-04,
-4.85531936495542274e-06,
-2.02473518491905386e-08,
};
double[] Q =
{
1.00000000000000000e+00,
8.60107275833921618e-01,
4.10420467985504373e-01,
1.18444884081994841e-01,
2.16966505556021046e-02,
2.24529766630769097e-03,
9.82045090226437614e-05,
1.36363515125489502e-06,
3.44200749053237945e-09,
};
var log_w = Math.Log(z);
return(log_w + Y + boost_math_tools_evaluate_rational(P, Q, log_w));
}
else if (z < 7.896296e+13) // 9.2 < log(z) <= 32
{
// Max error in interpolated form: 6.529e-18
double Y = -2.73572921752929688e+00;
double[] P =
{
3.30547638424076217e+00,
1.64050071277550167e+00,
4.57149576470736039e-01,
4.03821227745424840e-02,
-4.99664976882514362e-04,
-1.28527893803052956e-04,
-2.95470325373338738e-06,
-1.76662025550202762e-08,
-1.98721972463709290e-11,
};
double[] Q =
{
1.00000000000000000e+00,
6.91472559412458759e-01,
2.48154578891676774e-01,
4.60893578284335263e-02,
3.60207838982301946e-03,
1.13001153242430471e-04,
1.33690948263488455e-06,
4.97253225968548872e-09,
3.39460723731970550e-12,
};
var log_w = Math.Log(z);
return(log_w + Y + boost_math_tools_evaluate_rational(P, Q, log_w));
}
else if (z < 2.6881171e+43) // 32 < log(z) < 100
{
// Max error in interpolated form: 2.015e-18
double Y = -4.01286315917968750e+00;
double[] P =
{
5.07714858354309672e+00,
-3.32994414518701458e+00,
-8.61170416909864451e-01,
-4.01139705309486142e-02,
-1.85374201771834585e-04,
1.08824145844270666e-05,
1.17216905810452396e-07,
2.97998248101385990e-10,
1.42294856434176682e-13,
};
double[] Q =
{
1.00000000000000000e+00,
-4.85840770639861485e-01,
-3.18714850604827580e-01,
-3.20966129264610534e-02,
-1.06276178044267895e-03,
-1.33597828642644955e-05,
-6.27900905346219472e-08,
-9.35271498075378319e-11,
-2.60648331090076845e-14,
};
var log_w = Math.Log(z);
return(log_w + Y + boost_math_tools_evaluate_rational(P, Q, log_w));
}
else // 100 < log(z) < 710
{
// Max error in interpolated form: 5.277e-18
double Y = -5.70115661621093750e+00;
double[] P =
{
6.42275660145116698e+00,
1.33047964073367945e+00,
6.72008923401652816e-02,
1.16444069958125895e-03,
7.06966760237470501e-06,
5.48974896149039165e-09,
-7.00379652018853621e-11,
-1.89247635913659556e-13,
-1.55898770790170598e-16,
-4.06109208815303157e-20,
-2.21552699006496737e-24,
};
double[] Q =
{
1.00000000000000000e+00,
3.34498588416632854e-01,
2.51519862456384983e-02,
6.81223810622416254e-04,
7.94450897106903537e-06,
4.30675039872881342e-08,
1.10667669458467617e-10,
1.31012240694192289e-13,
6.53282047177727125e-17,
1.11775518708172009e-20,
3.78250395617836059e-25,
};
var log_w = Math.Log(z);
return(log_w + Y + boost_math_tools_evaluate_rational(P, Q, log_w));
}
}
public static double cdfinv_normal(double p)
/******************************************************************************/
/*
* Purpose:
*
* R8_NORMAL_01_CDF_INVERSE inverts the standard normal CDF.
*
* Discussion:
*
* The result is accurate to about 1 part in 10^16.
*
* Licensing:
*
* This code is distributed under the GNU LGPL license.
*
* Modified:
*
* 19 March 2010
*
* Author:
*
* Original FORTRAN77 version by Michael Wichura.
* C version by John Burkardt.
*
* Reference:
*
* Michael Wichura,
* The Percentage Points of the Normal Distribution,
* Algorithm AS 241,
* Applied Statistics,
* Volume 37, Number 3, pages 477-484, 1988.
*
* Parameters:
*
* Input, double P, the value of the cumulative probability
* densitity function. 0 < P < 1. If P is outside this range, an "infinite"
* value is returned.
*
* Output, double R8_NORMAL_01_CDF_INVERSE, the normal deviate value
* with the property that the probability of a standard normal deviate being
* less than or equal to this value is P.
*/
{
var const1 = 0.180625;
var const2 = 1.6;
double q;
double r;
var split1 = 0.425;
var split2 = 5.0;
double value;
if (p <= 0.0)
{
if (p < 0)
{
throw FS.FailWith($"p is lower than 0, with {p}");
}
value = -R8_HUGE;//r8_huge ( );
return(value);
}
if (1.0 <= p)
{
if (p > 1)
{
throw FS.FailWith($"p is higher than 1 with {p}");
}
value = R8_HUGE; // r8_huge ( );
return(value);
}
q = p - 0.5;
//if ( r8_abs ( q ) <= split1 )
if (Math.Abs(q) <= split1)
{
r = const1 - q * q;
value = q * (((((((a[7] * r + a[6]) * r + a[5]) * r + a[4]) * r + a[3]) * r + a[2]) * r + a[1]) * r + a[0]) /
(((((((b[7] * r + b[6]) * r + b[5]) * r + b[4]) * r + b[3]) * r + b[2]) * r + b[1]) * r + b[0]);
}
else
{
if (q < 0.0)
{
r = p;
}
else
{
r = 1.0 - p;
}
if (r <= 0.0)
{
value = -1.0;
throw FS.FailWith($"Error, cdfinv with p = {p}");
//exit ( 1 );// exception??
}
r = Math.Sqrt(-Math.Log(r));
if (r <= split2)
{
r = r - const2;
value = (((((((c[7] * r + c[6]) * r + c[5]) * r + c[4]) * r + c[3]) * r + c[2]) * r + c[1]) * r + c[0]) /
(((((((d[7] * r + d[6]) * r + d[5]) * r + d[4]) * r + d[3]) * r + d[2]) * r + d[1]) * r + d[0]);
}
else
{
r = r - split2;
value = (((((((e[7] * r + e[6]) * r + e[5]) * r + e[4]) * r + e[3]) * r + e[2]) * r + e[1]) * r + e[0]) /
(((((((f[7] * r + f[6]) * r + f[5]) * r + f[4]) * r + f[3]) * r + f[2]) * r + f[1]) * r + f[0]);
}
if (q < 0.0)
{
value = -value;
}
}
return(value);
}
public BetaBlackPack(double beta, OptionType callPut, double f, double k, double t, double sigma)
{
if (beta < 0 || beta >= 1.0)
{
throw FS.FailWith($"Beta must be in [0, 1.0), got {beta}");
}
if (sigma <= 0.0)
{
throw FS.FailWith($"Sigma must be positive, got {sigma}");
}
Beta = beta;
CallPut = callPut;
F = f;
K = k;
T = t;
Sigma = sigma;
//! Nota bene: Use AD for first order derivatives and FD on AD for second order
//
// Mu = BetaBlack.inv_m1_beta_black(beta, f, sigma * Math.Sqrt(t));
double beta_b = 0.0;
double f_b = 0.0;
double k_b = 0.0;
double t_b = 0.0;
double sigma_b = 0.0;
Price = BetaBlack.beta_black_b(beta, callPut, f, k, t, sigma, ref beta_b, ref f_b, ref k_b, ref t_b, ref sigma_b, 1.0);
dPV_dS = f_b;
dPV_dK = k_b;
dPV_dT = t_b;
dPV_dVol = sigma_b;
dPV_dBeta = beta_b;
var eps = Math.Sqrt(DoubleUtils.DoubleEpsilon);
{
var dF = eps * (1.0 + Math.Abs(f));
double betaUp_b = 0.0;
double fUp_b = 0.0;
double kUp_b = 0.0;
double tUp_b = 0.0;
double sigmaUp_b = 0.0;
double pUp = BetaBlack.beta_black_b(beta, callPut, f + dF, k, t, sigma, ref betaUp_b, ref fUp_b, ref kUp_b, ref tUp_b, ref sigmaUp_b, 1.0);
double betaDown_b = 0.0;
double fDown_b = 0.0;
double kDown_b = 0.0;
double tDown_b = 0.0;
double sigmaDown_b = 0.0;
double pDown = BetaBlack.beta_black_b(beta, callPut, f - dF, k, t, sigma, ref betaDown_b, ref fDown_b, ref kDown_b, ref tDown_b, ref sigmaDown_b, 1.0);
d2PV_dFdBeta = (betaUp_b - betaDown_b) / (2.0 * dF);
d2PV_dS2 = (fUp_b - fDown_b) / (2.0 * dF);
d2PV_dKdS = (kUp_b - kDown_b) / (2.0 * dF);
d2PV_dSdT = (tUp_b - tDown_b) / (2.0 * dF);
d2PV_dSdVol = (sigmaUp_b - sigmaDown_b) / (2.0 * dF);
}
{
var dK = eps * (1.0 + Math.Abs(k));
double betaUp_b = 0.0;
double fUp_b = 0.0;
double kUp_b = 0.0;
double tUp_b = 0.0;
double sigmaUp_b = 0.0;
double pUp = BetaBlack.beta_black_b(beta, callPut, f, k + dK, t, sigma, ref betaUp_b, ref fUp_b, ref kUp_b, ref tUp_b, ref sigmaUp_b, 1.0);
double betaDown_b = 0.0;
double fDown_b = 0.0;
double kDown_b = 0.0;
double tDown_b = 0.0;
double sigmaDown_b = 0.0;
double pDown = BetaBlack.beta_black_b(beta, callPut, f, k - dK, t, sigma, ref betaDown_b, ref fDown_b, ref kDown_b, ref tDown_b, ref sigmaDown_b, 1.0);
d2PV_dKdBeta = (betaUp_b - betaDown_b) / (2.0 * dK);
// d2PV_dKdS = (fUp_b - fDown_b) / (2.0 * dK);
d2PV_dK2 = (kUp_b - kDown_b) / (2.0 * dK);
d2PV_dKdT = (tUp_b - tDown_b) / (2.0 * dK);
d2PV_dVoldK = (sigmaUp_b - sigmaDown_b) / (2.0 * dK);
}
{
var dSigma = eps * (1.0 + Math.Abs(sigma));
double betaUp_b = 0.0;
double fUp_b = 0.0;
double kUp_b = 0.0;
double tUp_b = 0.0;
double sigmaUp_b = 0.0;
double pUp = BetaBlack.beta_black_b(beta, callPut, f, k, t, sigma + dSigma, ref betaUp_b, ref fUp_b, ref kUp_b, ref tUp_b, ref sigmaUp_b, 1.0);
double betaDown_b = 0.0;
double fDown_b = 0.0;
double kDown_b = 0.0;
double tDown_b = 0.0;
double sigmaDown_b = 0.0;
double pDown = BetaBlack.beta_black_b(beta, callPut, f, k, t, sigma - dSigma, ref betaDown_b, ref fDown_b, ref kDown_b, ref tDown_b, ref sigmaDown_b, 1.0);
d2PV_dVoldBeta = (betaUp_b - betaDown_b) / (2.0 * dSigma);
// d2PV_dSdVol = (fUp_b - fDown_b) / (2.0 * dSigma);
// d2PV_dVoldK = (kUp_b - kDown_b) / (2.0 * dSigma);
d2PV_dVoldT = (tUp_b - tDown_b) / (2.0 * dSigma);
d2PV_dVol2 = (sigmaUp_b - sigmaDown_b) / (2.0 * dSigma);
}
}
public static double beta_black_b(double beta, OptionType optType, double F, double K, double T, double sigma
, ref double beta_b, ref double F_b, ref double K_b, ref double T_b, ref double sigma_b, double res_b)
{
if (T < 0.0)
{
throw FS.FailWith($"T < 0 not allowed, {T}");
}
if (sigma < 0.0)
{
throw FS.FailWith($"sigma < 0 not allowed {sigma}");
}
var sqrtT = Math.Sqrt(T);
var stdev = sigma * sqrtT;
if (stdev == 0.0)
{
return(Math.Max(optType.ToEpsilon() * (F - K), 0.0));
}
var dmu_dbeta = 0.0;
var dmu_dF = 0.0;
var dmu_dstdev = 0.0;
var mu = inv_m1_beta_black_b(beta, F, stdev, ref dmu_dbeta, ref dmu_dF, ref dmu_dstdev, 1.0);
var digb_dbeta = 0.0;
var digb_dK = 0.0;
var igb = inv_g_b(beta, K, ref digb_dbeta, ref digb_dK, 1.0);
var d = (igb - mu) / stdev;
var dNd_dd = 0.0;
var Nd = SpecialFunction.cdf_normal_b(d, ref dNd_dd, 1.0);
var t1 = K * Nd;
var dt2_dbeta = 0.0;
var dt2_dmu = 0.0;
var dt2_dstdev = 0.0;
var dt2_dd = 0.0;
var t2 = beta_black_trunc_b(beta, mu, stdev, d, ref dt2_dbeta, ref dt2_dmu, ref dt2_dstdev, ref dt2_dd, 1.0);
var res = t1 - t2;
// now rewind
var t1_b = res_b;
var t2_b = -res_b;
beta_b += t2_b * dt2_dbeta;
var mu_b = t2_b * dt2_dmu;
var stdev_b = t2_b * dt2_dstdev;
var d_b = t2_b * dt2_dd;
K_b += t1_b * Nd;
var Nd_b = t1_b * K;
d_b += Nd_b * dNd_dd;
var igb_b = d_b / stdev;
mu_b += -d_b / stdev;
stdev_b += -d_b * (igb - mu) / stdev / stdev;
beta_b += igb_b * digb_dbeta;
K_b += igb_b * digb_dK;
beta_b += mu_b * dmu_dbeta;
F_b += mu_b * dmu_dF;
stdev_b += mu_b * dmu_dstdev;
sigma_b += stdev_b * sqrtT;
T_b += stdev_b * sigma / (2.0 * sqrtT);
if (optType == OptionType.Put)
{
return(res);
}
else if (optType == OptionType.Call)
{
F_b += res_b;
K_b += -res_b;
return(res + F - K);
}
else
{
throw FS.E_CASE(optType);
}
}