NAG Library Routine Document

s30bbf  (opt_lookback_fls_greeks)

 Contents

    1  Purpose
    7  Accuracy

1
Purpose

s30bbf computes the price of a floating-strike lookback option together with its sensitivities (Greeks).

2
Specification

Fortran Interface
Subroutine s30bbf ( calput, m, n, sm, s, t, sigma, r, q, p, ldp, delta, gamma, vega, theta, rho, crho, vanna, charm, speed, colour, zomma, vomma, ifail)
Integer, Intent (In):: m, n, ldp
Integer, Intent (Inout):: ifail
Real (Kind=nag_wp), Intent (In):: sm(m), s, t(n), sigma, r, q
Real (Kind=nag_wp), Intent (Inout):: p(ldp,n), delta(ldp,n), gamma(ldp,n), vega(ldp,n), theta(ldp,n), rho(ldp,n), crho(ldp,n), vanna(ldp,n), charm(ldp,n), speed(ldp,n), colour(ldp,n), zomma(ldp,n), vomma(ldp,n)
Character (1), Intent (In):: calput
C Header Interface
#include nagmk26.h
void  s30bbf_ ( const char *calput, const Integer *m, const Integer *n, const double sm[], const double *s, const double t[], const double *sigma, const double *r, const double *q, double p[], const Integer *ldp, double delta[], double gamma[], double vega[], double theta[], double rho[], double crho[], double vanna[], double charm[], double speed[], double colour[], double zomma[], double vomma[], Integer *ifail, const Charlen length_calput)

3
Description

s30bbf computes the price of a floating-strike lookback call or put option, together with the Greeks or sensitivities, which are the partial derivatives of the option price with respect to certain of the other input parameters. A call option of this type confers the right to buy the underlying asset at the lowest price, Smin, observed during the lifetime of the contract. A put option gives the holder the right to sell the underlying asset at the maximum price, Smax, observed during the lifetime of the contract. Thus, at expiry, the payoff for a call option is S-Smin, and for a put, Smax-S.
For a given minimum value the price of a floating-strike lookback call with underlying asset price, S, and time to expiry, T, is
Pcall = S e-qT Φa1 - Smin e-rT Φa2 + S e-rT   σ2 2b S Smin -2b / σ2 Φ -a1 + 2b σ T -e bT Φ -a1 ,  
where b=r-q0. The volatility, σ, risk-free interest rate, r, and annualised dividend yield, q, are constants.
The corresponding put price is
Pput = Smax e-rT Φ -a2 - S e-qT Φ -a1 + S e-rT   σ2 2b - S Smax -2b / σ2 Φ a1 - 2b σ T + ebT Φ a1 .  
In the above, Φ denotes the cumulative Normal distribution function,
Φx = - x ϕy dy  
where ϕ denotes the standard Normal probability density function
ϕy = 12π exp -y2/2  
and
a1 = ln S / Sm + b + σ2 / 2 T σT a2=a1-σT  
where Sm is taken to be the minimum price attained by the underlying asset, Smin, for a call and the maximum price, Smax, for a put.
The option price Pij=PX=Xi,T=Tj is computed for each minimum or maximum observed price in a set Smin i  or Smax i , i=1,2,,m, and for each expiry time in a set Tj, j=1,2,,n.

4
References

Goldman B M, Sosin H B and Gatto M A (1979) Path dependent options: buy at the low, sell at the high Journal of Finance 34 1111–1127

5
Arguments

1:     calput – Character(1)Input
On entry: determines whether the option is a call or a put.
calput='C'
A call; the holder has a right to buy.
calput='P'
A put; the holder has a right to sell.
Constraint: calput='C' or 'P'.
2:     m – IntegerInput
On entry: the number of minimum or maximum prices to be used.
Constraint: m1.
3:     n – IntegerInput
On entry: the number of times to expiry to be used.
Constraint: n1.
4:     smm – Real (Kind=nag_wp) arrayInput
On entry: smi must contain Smin i , the ith minimum observed price of the underlying asset when calput='C', or Smax i , the maximum observed price when calput='P', for i=1,2,,m.
Constraints:
  • smiz ​ and ​ smi 1 / z , where z = x02amf , the safe range parameter, for i=1,2,,m;
  • if calput='C', smiS, for i=1,2,,m;
  • if calput='P', smiS, for i=1,2,,m.
5:     s – Real (Kind=nag_wp)Input
On entry: S, the price of the underlying asset.
Constraint: sz ​ and ​s1.0/z, where z=x02amf, the safe range parameter.
6:     tn – Real (Kind=nag_wp) arrayInput
On entry: ti must contain Ti, the ith time, in years, to expiry, for i=1,2,,n.
Constraint: tiz, where z = x02amf , the safe range parameter, for i=1,2,,n.
7:     sigma – Real (Kind=nag_wp)Input
On entry: σ, the volatility of the underlying asset. Note that a rate of 15% should be entered as 0.15.
Constraint: sigma>0.0.
8:     r – Real (Kind=nag_wp)Input
On entry: the annual risk-free interest rate, r, continuously compounded. Note that a rate of 5% should be entered as 0.05.
Constraint: r0.0 and absr-q>10×eps×maxabsr,1, where eps=x02ajf, the machine precision.
9:     q – Real (Kind=nag_wp)Input
On entry: the annual continuous yield rate. Note that a rate of 8% should be entered as 0.08.
Constraint: q0.0 and absr-q>10×eps×maxabsr,1, where eps=x02ajf, the machine precision.
10:   pldpn – Real (Kind=nag_wp) arrayOutput
On exit: pij contains Pij, the option price evaluated for the minimum or maximum observed price Smin i  or Smax i  at expiry tj for i=1,2,,m and j=1,2,,n.
11:   ldp – IntegerInput
On entry: the first dimension of the arrays p, delta, gamma, vega, theta, rho, crho, vanna, charm, speed, colour, zomma and vomma as declared in the (sub)program from which s30bbf is called.
Constraint: ldpm.
12:   deltaldpn – Real (Kind=nag_wp) arrayOutput
On exit: the leading m×n part of the array delta contains the sensitivity, PS, of the option price to change in the price of the underlying asset.
13:   gammaldpn – Real (Kind=nag_wp) arrayOutput
On exit: the leading m×n part of the array gamma contains the sensitivity, 2PS2, of delta to change in the price of the underlying asset.
14:   vegaldpn – Real (Kind=nag_wp) arrayOutput
On exit: vegaij, contains the first-order Greek measuring the sensitivity of the option price Pij to change in the volatility of the underlying asset, i.e., Pij σ , for i=1,2,,m and j=1,2,,n.
15:   thetaldpn – Real (Kind=nag_wp) arrayOutput
On exit: thetaij, contains the first-order Greek measuring the sensitivity of the option price Pij to change in time, i.e., - Pij T , for i=1,2,,m and j=1,2,,n, where b=r-q.
16:   rholdpn – Real (Kind=nag_wp) arrayOutput
On exit: rhoij, contains the first-order Greek measuring the sensitivity of the option price Pij to change in the annual risk-free interest rate, i.e., - Pij r , for i=1,2,,m and j=1,2,,n.
17:   crholdpn – Real (Kind=nag_wp) arrayOutput
On exit: crhoij, contains the first-order Greek measuring the sensitivity of the option price Pij to change in the annual cost of carry rate, i.e., - Pij b , for i=1,2,,m and j=1,2,,n, where b=r-q.
18:   vannaldpn – Real (Kind=nag_wp) arrayOutput
On exit: vannaij, contains the second-order Greek measuring the sensitivity of the first-order Greek Δij to change in the volatility of the asset price, i.e., - Δij T = - 2 Pij Sσ , for i=1,2,,m and j=1,2,,n.
19:   charmldpn – Real (Kind=nag_wp) arrayOutput
On exit: charmij, contains the second-order Greek measuring the sensitivity of the first-order Greek Δij to change in the time, i.e., - Δij T = - 2 Pij ST , for i=1,2,,m and j=1,2,,n.
20:   speedldpn – Real (Kind=nag_wp) arrayOutput
On exit: speedij, contains the third-order Greek measuring the sensitivity of the second-order Greek Γij to change in the price of the underlying asset, i.e., - Γij S = - 3 Pij S3 , for i=1,2,,m and j=1,2,,n.
21:   colourldpn – Real (Kind=nag_wp) arrayOutput
On exit: colourij, contains the third-order Greek measuring the sensitivity of the second-order Greek Γij to change in the time, i.e., - Γij T = - 3 Pij ST , for i=1,2,,m and j=1,2,,n.
22:   zommaldpn – Real (Kind=nag_wp) arrayOutput
On exit: zommaij, contains the third-order Greek measuring the sensitivity of the second-order Greek Γij to change in the volatility of the underlying asset, i.e., - Γij σ = - 3 Pij S2σ , for i=1,2,,m and j=1,2,,n.
23:   vommaldpn – Real (Kind=nag_wp) arrayOutput
On exit: vommaij, contains the second-order Greek measuring the sensitivity of the first-order Greek Δij to change in the volatility of the underlying asset, i.e., - Δij σ = - 2 Pij σ2 , for i=1,2,,m and j=1,2,,n.
24:   ifail – IntegerInput/Output
On entry: ifail must be set to 0, -1​ or ​1. If you are unfamiliar with this argument you should refer to Section 3.4 in How to Use the NAG Library and its Documentation for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value -1​ or ​1 is recommended. If the output of error messages is undesirable, then the value 1 is recommended. Otherwise, if you are not familiar with this argument, the recommended value is 0. When the value -1​ or ​1 is used it is essential to test the value of ifail on exit.
On exit: ifail=0 unless the routine detects an error or a warning has been flagged (see Section 6).

6
Error Indicators and Warnings

If on entry ifail=0 or -1, explanatory error messages are output on the current error message unit (as defined by x04aaf).
Errors or warnings detected by the routine:
ifail=1
On entry, calput=value was an illegal value.
ifail=2
On entry, m=value.
Constraint: m1.
ifail=3
On entry, n=value.
Constraint: n1.
ifail=4
On entry, smvalue=value.
Constraint: valuesmivalue for all i.
On entry with a call option, smvalue=value.
Constraint: for call options, smivalue for all i.
On entry with a put option, smvalue=value.
Constraint: for put options, smivalue for all i.
ifail=5
On entry, s=value.
Constraint: svalue and svalue.
ifail=6
On entry, tvalue=value.
Constraint: tivalue for all i.
ifail=7
On entry, sigma=value.
Constraint: sigma>0.0.
ifail=8
On entry, r=value.
Constraint: r0.0.
ifail=9
On entry, q=value.
Constraint: q0.0.
ifail=11
On entry, ldp=value and m=value.
Constraint: ldpm.
ifail=12
On entry, r=value and q=value.
Constraint: r-q>10×eps×maxr,1, where eps is the machine precision.
ifail=-99
An unexpected error has been triggered by this routine. Please contact NAG.
See Section 3.9 in How to Use the NAG Library and its Documentation for further information.
ifail=-399
Your licence key may have expired or may not have been installed correctly.
See Section 3.8 in How to Use the NAG Library and its Documentation for further information.
ifail=-999
Dynamic memory allocation failed.
See Section 3.7 in How to Use the NAG Library and its Documentation for further information.

7
Accuracy

The accuracy of the output is dependent on the accuracy of the cumulative Normal distribution function, Φ. This is evaluated using a rational Chebyshev expansion, chosen so that the maximum relative error in the expansion is of the order of the machine precision (see s15abf and s15adf). An accuracy close to machine precision can generally be expected.

8
Parallelism and Performance

s30bbf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this routine. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

9
Further Comments

None.

10
Example

This example computes the price of a floating-strike lookback put with a time to expiry of 6 months and a stock price of 87. The maximum price observed so far is 100. The risk-free interest rate is 6% per year and the volatility is 30% per year with an annual dividend return of 4%.

10.1
Program Text

Program Text (s30bbfe.f90)

10.2
Program Data

Program Data (s30bbfe.d)

10.3
Program Results

Program Results (s30bbfe.r)

© The Numerical Algorithms Group Ltd, Oxford, UK. 2017