S30ABF computes the European option price given by the Black–Scholes–Merton formula together with its sensitivities (Greeks).
SUBROUTINE S30ABF ( |
CALPUT, M, N, X, S, T, SIGMA, R, Q, P, LDP, DELTA, GAMMA, VEGA, THETA, RHO, CRHO, VANNA, CHARM, SPEED, COLOUR, ZOMMA, VOMMA, IFAIL) |
INTEGER |
M, N, LDP, IFAIL |
REAL (KIND=nag_wp) |
X(M), S, T(N), SIGMA, R, Q, 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) |
CALPUT |
|
S30ABF computes the price of a European 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, by the Black–Scholes–Merton formula (see
Black and Scholes (1973) and
Merton (1973)). The annual volatility,
, risk-free interest rate,
, and dividend yield,
, must be supplied as input. For a given strike price,
, the price of a European call with underlying price,
, and time to expiry,
, is
and the corresponding European put price is
and where
denotes the cumulative Normal distribution function,
and
- 1: CALPUT – CHARACTER(1)Input
On entry: determines whether the option is a call or a put.
- A call. The holder has a right to buy.
- A put. The holder has a right to sell.
Constraint:
or .
- 2: M – INTEGERInput
On entry: the number of strike prices to be used.
Constraint:
.
- 3: N – INTEGERInput
On entry: the number of times to expiry to be used.
Constraint:
.
- 4: X(M) – REAL (KIND=nag_wp) arrayInput
On entry: must contain
, the th strike price, for .
Constraint:
, where , the safe range parameter, for .
- 5: S – REAL (KIND=nag_wp)Input
On entry: , the price of the underlying asset.
Constraint:
, where , the safe range parameter.
- 6: T(N) – REAL (KIND=nag_wp) arrayInput
On entry: must contain
, the th time, in years, to expiry, for .
Constraint:
, where , the safe range parameter, for .
- 7: SIGMA – REAL (KIND=nag_wp)Input
On entry: , the volatility of the underlying asset. Note that a rate of 15% should be entered as 0.15.
Constraint:
.
- 8: R – REAL (KIND=nag_wp)Input
On entry: , the annual risk-free interest rate, continuously compounded. Note that a rate of 5% should be entered as 0.05.
Constraint:
.
- 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:
.
- 10: P(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
P contains the computed option prices.
- 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 S30ABF is called.
Constraint:
.
- 12: DELTA(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
DELTA contains the sensitivity,
, of the option price to change in the price of the underlying asset.
- 13: GAMMA(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
GAMMA contains the sensitivity,
, of
DELTA to change in the price of the underlying asset.
- 14: VEGA(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
VEGA contains the sensitivity,
, of the option price to change in the volatility of the underlying asset.
- 15: THETA(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
THETA contains the sensitivity,
, of the option price to change in the time to expiry of the option.
- 16: RHO(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
RHO contains the sensitivity,
, of the option price to change in the annual risk-free interest rate.
- 17: CRHO(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
CRHO containing the sensitivity,
, of the option price to change in the annual cost of carry rate,
, where
.
- 18: VANNA(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
VANNA contains the sensitivity,
, of
VEGA to change in the price of the underlying asset or, equivalently, the sensitivity of
DELTA to change in the volatility of the asset price.
- 19: CHARM(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
CHARM contains the sensitivity,
, of
DELTA to change in the time to expiry of the option.
- 20: SPEED(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
SPEED contains the sensitivity,
, of
GAMMA to change in the price of the underlying asset.
- 21: COLOUR(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
COLOUR contains the sensitivity,
, of
GAMMA to change in the time to expiry of the option.
- 22: ZOMMA(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
ZOMMA contains the sensitivity,
, of
GAMMA to change in the volatility of the underlying asset.
- 23: VOMMA(LDP,N) – REAL (KIND=nag_wp) arrayOutput
On exit: the leading
part of the array
VOMMA contains the sensitivity,
, of
VEGA to change in the volatility of the underlying asset.
- 24: IFAIL – INTEGERInput/Output
-
On entry:
IFAIL must be set to
,
. If you are unfamiliar with this parameter you should refer to
Section 3.3 in the Essential Introduction for details.
For environments where it might be inappropriate to halt program execution when an error is detected, the value
is recommended. If the output of error messages is undesirable, then the value
is recommended. Otherwise, if you are not familiar with this parameter, the recommended value is
.
When the value is used it is essential to test the value of IFAIL on exit.
On exit:
unless the routine detects an error or a warning has been flagged (see
Section 6).
If on entry
or
, explanatory error messages are output on the current error message unit (as defined by
X04AAF).
The accuracy of the output is dependent on the accuracy of the cumulative Normal distribution function,
. 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.
None.