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346     7 Probability theory and stochastic simulation



                   and apply (7.162),
                                    1     2

                        dG = − 1 + (2)[1] dt + 2 Y − W t k  (1)dW t = Y − W t k  dW t  (7.168)
                                    2
                   to yield the integrand of (7.166). Using (7.166) in (7.165), we obtain the Mil’shtein rule

                                                            ∂b              1      2
                                                   )( W t ) +              ) [( W t ) −  t]
                    X t k+1  ≈ X t k  + a(t k , X t k  )( t) + b(t k , X t k  b(t k , X t k 2
                                                            ∂ X
                                                                (t k ,X t k  )
                                                                                     (7.169)
                   Further higher-order methods are discussed in Kloeden & Platen (2000).
                   Example. Stochastic calculus in quantitative finance

                   Stochasticcalculusisusedheavilyinquantitativefinance,asignificantemployerofnumerate
                   engineers. In Problem 6.B.5, we solved the Black–Scholes equation for the fair value of an
                   option. Here, we show how this equation is obtained, through stochastic calculus.
                     Consider the spot (market) price S(t) of some financial asset as a function of time. We
                   sample the price at uniform time periods t k = k( t) and let S k = S(t k ). A reasonable model
                   of the behavior of many assets is the lognormal random walk, which assumes that the return
                   between successive time periods
                                                     S k+1 − S k
                                                R k =                                (7.170)
                                                        S k
                   is normally distributed so that the spot price is governed by the SDE
                                                                                     (7.171)
                                              dS = µSdt + σ SdW t
                   µ is the drift rate, and is computed from a sequence of returns by
                                                          N s
                                                     1
                                              µ =           R k                      (7.172)
                                                   N s ( t)
                                                         k=1
                   σ is the volatility of the asset, and is estimated from
                                       1      N s
                              2                          2
                             σ =                (R k − R )     R = µ( t)             (7.173)
                                  (N s − 1)( t)
                                             k=1
                   In a simple type of derivative, a European option, we purchase at time t the right to either
                   buy (a call option) or sell (a put option) the underlying asset at some time T > t in the future
                   at an exercise price E. Thus, at time T, if we purchase the option, we will have a payoff

                                             max(S(T ) − E, 0),  call option
                              payoff(S(T )) =                                        (7.174)
                                             max(E − S(T ), 0),  put option
                   What is the fair price V (S, t) of this option at t < T when the spot price of the underlying
                   asset is S?
                     To compute this value, assume that we purchase an option and at the same time short
                   (i.e., sell assets we don’t actually have – this is often possible and legal) a quantity   of the
                   underlying asset. The value of this portfolio is   = V (S, t) −  S. Applying (7.162), the
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