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layout="Title" style="Title">Pricing Asian Options</Text-field></Input></Group><Group><Input><Text-field alignment="centred" layout="Normal" style="Text"><Font encoding="ISO8859-1">\251 Maplesoft, a division of Waterloo Maple Inc., 2004</Font></Text-field></Input></Group><Group><Input><Text-field layout="Maple Plot"><Plot height="272" plot-scale="1.0" plot-xtrans="0.0" plot-ytrans="0.0" type="two-dimensional" 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collapsed="true"><Title><Text-field layout="Heading 1" style="Heading 1">Introduction</Text-field></Title><Group><Input><Text-field layout="Normal" style="Text">This worksheet demonstrates the use of Maple for computing the price of an Asian option, a derivative security that has gained popularity in financial markets in the last fifteen years.  </Text-field><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">The payoff of an Asian option is based on the difference between an asset's average price over a given time period, and a fixed price called the strike price. Asian options are popular because they tend to have lower volatility than options whose payoffs are based purely on a single price point.  It is also harder for big traders to manipulate an average price over an extended period than a single price, so Asian options offers further protection against risk.</Text-field><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">One disadvantage of Asian options is that their prices are very hard to compute using standard techniques.  Unlike European options, which can be priced using the classic Black-Scholes formula, there is no analytical formula for pricing an Asian option when the underlying asset is assumed to have a lognormal distribution, which is par for the course in financial modeling.</Text-field><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">In this application, we use two different approaches for computing these prices numerically.  (1) Solving a partial differential equation, and (2) Monte Carlo simulation.  We will see that the two numerical solutions that Maple derives are the same, providing strong validation for both the techniques and Maple's numerics.
</Text-field><Text-field layout="Normal" style="Text">In doing so, the following Maple techniques are highlighted:
</Text-field><Text-field firstindent="0.0" layout="Bullet Item" leftmargin="0.0" linebreak="space" rightmargin="0.0" style="Bullet Item"><Font executable="false" subscript="false" superscript="false">Solving partial differential equations numerically</Font></Text-field><Text-field firstindent="0.0" layout="Bullet Item" leftmargin="0.0" linebreak="space" rightmargin="0.0" style="Bullet Item"><Font executable="false" subscript="false" superscript="false">Calling external C++ routines from within Maple</Font></Text-field></Input></Group></Section><Section collapsed="true"><Title><Text-field layout="Heading 1" style="Heading 1">Problem statement</Text-field></Title><Group><Input><Text-field layout="Normal" style="Text">Arithmetic average Asian options are securities whose payoff depends on the average of the underlying stock price over a certain period of time. To be more precise, the value of the continuous arithmetic Asian call option at time<Font bold="false" italic="false" style="2D Math" subscript="false" superscript="false" underline="false"> </Font><Equation input-equation="t &lt;= T" style="2D Math">NiMxSSJ0RzYiSSJUR0Yl</Equation> is given by</Text-field><Text-field layout="Normal" style="Text"/></Input><Input><Text-field alignment="centred" bullet="none" firstindent="0.0" leftmargin="0.0" linebreak="space" linespacing="0.0" rightmargin="0.0" spaceabove="0.0" spacebelow="0.0" style="Text"><Equation input-equation="C[t, T](K) = exp(-r*(T-t))*E*[Int(S(u), u = 0 .. T)/T-K]^`+`" style="2D Math">NiMvLSZJIkNHNiI2JEkidEdGJ0kiVEdGJzYjSSJLR0YnKigtSSRleHBHNiRJKnByb3RlY3RlZEdGMUkoX3N5c2xpYkdGJzYjLCQqJkkickdGJyIiIiwmRipGN0YpISIiRjdGOUY3SSJFR0YnRjcpNyMsJiomLUkkSW50R0YwNiQtSSJTR0YnNiNJInVHRicvRkU7IiIhRipGN0YqRjlGN0YsRjlJIitHRjFGNw==</Equation> </Text-field></Input><Input><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">where <Equation input-equation="S(t)" style="2D Math">NiMtSSJTRzYiNiNJInRHRiU=</Equation> is the stock price at time <Equation input-equation="t" style="2D Math">NiNJInRHNiI=</Equation>, <Equation input-equation="T" style="2D Math">NiNJIlRHNiI=</Equation> is the expiration date, and <Equation input-equation="K" style="2D Math">NiNJIktHNiI=</Equation> is the strike price. </Text-field><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">Since no general closed form solution for the price of the arithmetic average Asian option is known, a variety of numerical methods have been developed. These include formulation as a PDE, Monte Carlo simulation, and numeric inversion of the Laplace transform. </Text-field><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">In this worksheet we demonstrate how these methods can be easily and quickly implemented in Maple.</Text-field><Text-field layout="Normal" style="Text"/></Input></Group></Section><Section collapsed="true"><Title><Text-field layout="Heading 1" style="Heading 1">Initialization</Text-field></Title><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">restart;
MCSamplePath := define_external(MCSamplePath, LIB = "libasian.so", 
                                S::ARRAY(float[8]), 
                                N::integer[4],   
                                T::float[8], 
                                S0::float[8],
                                r::float[8],
                                sigma::float[8]):

Payoff := define_external('Payoff', LIB = "libasian.so", 
                          'S'::ARRAY(float[8]),
                          'K'::float[8],
                          'N'::integer[4],
                          RETURN::float[8]):

QMCInitialize := define_external(QMCInitialize, LIB = "libasian.so", 'N'::integer[4], RETURN::integer[4]):

QMCSamplePath := define_external(QMCSamplePath, LIB = "libasian.so", 
                                 'S'::ARRAY(float[8]), 
                                 'N'::integer[4],   
                                 'T'::float[8], 
                                 'S0'::float[8],
                                 'r'::float[8],
                                 'sigma'::float[8]):

MCInitialize := define_external(MCInitialize, LIB = "libasian.so"):

ArithmeticAsian := proc(T, S0, r, sigma, K, N, M, SamplePath)
    local S, V, i;

    S := Array(1..N, datatype = float[8]);
    V := 0.;

    for i from 1 to M do
        SamplePath(S, N, T, S0, r, sigma);
        V := V+Payoff(S, K, N);
    end:
    return exp(-r*T)*V/M;
end proc:
</Text-field></Input></Group><Group><Input><Text-field alignment="left" bullet="none" firstindent="0.0" leftmargin="0.0" linebreak="space" linespacing="0.0" prompt="&gt; " rightmargin="0.0" spaceabove="0.0" spacebelow="0.0" style="Maple Input">MCInitialize():</Text-field></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">N := 10^3: S := Array(1..N, datatype = float[8]):
</Text-field></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">N2 := 384: S2 := Array(1..N2, datatype = float[8]):</Text-field></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">QMCInitialize(N2):</Text-field></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">Tau := (T, sigma) -&gt; sigma^2*T/4:</Text-field></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">Nu := (r, sigma) -&gt; 2*r/sigma^2-1:</Text-field></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">Kappa := (T, sigma, K, S0) -&gt; Tau(T, sigma)*K/S0:
Mu := (nu, p) -&gt; sqrt(nu^2+2*p):</Text-field></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">U := (p, nu, kappa) -&gt; W(p, Mu(nu, p), nu, kappa):
_EnvInfinity := infinity:
</Text-field></Input></Group></Section><Section collapsed="true"><Title><Text-field layout="Heading 1" style="Heading 1">Solution 1: PDE formulation</Text-field></Title><Group><Input><Text-field layout="Normal" style="Text">It was shown by Vecer ("A new PDE approach for pricing arithmetic average Asian options", Journal of Computational Finance, vol. 4, No. 4, 105-113) that the value of the Asian option at time <Equation input-equation="0" style="2D Math">NiMiIiE=</Equation> is given by</Text-field><Text-field alignment="centred" bullet="none" firstindent="0.0" leftmargin="0.0" linebreak="space" linespacing="0.0" rightmargin="0.0" spaceabove="0.0" spacebelow="0.0" style="Text"><Equation input-equation="S[0]*u*(0, (S[0]-K)/S[0])" style="2D Math">NiMqKCZJIlNHNiI2IyIiISIiIkkidUdGJkYpNiRGKComLCZGJEYpSSJLR0YmISIiRilGJEYvRik=</Equation> </Text-field><Text-field alignment="left" bullet="none" firstindent="0.0" leftmargin="0.0" linebreak="space" linespacing="0.0" rightmargin="0.0" spaceabove="0.0" spacebelow="0.0" style="Text">where the function <Equation input-equation="u(t, z)" style="2D Math">NiMtSSJ1RzYiNiRJInRHRiVJInpHRiU=</Equation> satisfies the following PDE</Text-field><Text-field layout="Normal" style="Text"/><Text-field alignment="centred" bullet="none" firstindent="0.0" leftmargin="0.0" linebreak="space" linespacing="0.0" rightmargin="0.0" spaceabove="0.0" spacebelow="0.0" style="Text"><Equation input-equation="u[t]+r*(1-t/T-z)*u[z]+(1-t/T-z)^2*sigma^2*u[z, z]/2 = 0" style="2D Math">NiMvLCgmSSJ1RzYiNiNJInRHRiciIiIqKEkickdGJ0YqLChGKkYqKiZGKUYqSSJUR0YnISIiRjBJInpHRidGMEYqJkYmNiNGMUYqRioqLEYqRioiIiNGMEYtRjVJJnNpZ21hR0YnRjUmRiY2JEYxRjFGKkYqIiIh</Equation> </Text-field><Text-field alignment="left" bullet="none" firstindent="0.0" leftmargin="0.0" linebreak="space" linespacing="0.0" rightmargin="0.0" spaceabove="0.0" spacebelow="0.0" style="Text">with the boundary condition</Text-field><Text-field alignment="centred" bullet="none" firstindent="0.0" leftmargin="0.0" linebreak="space" linespacing="0.0" rightmargin="0.0" spaceabove="0.0" spacebelow="0.0" style="Text"><Equation input-equation="u(T, z) = z^`+`" style="2D Math">NiMvLUkidUc2IjYkSSJUR0YmSSJ6R0YmKUYpSSIrR0kqcHJvdGVjdGVkR0Ys</Equation> </Text-field><Text-field alignment="left" bullet="none" firstindent="0.0" leftmargin="0.0" linebreak="space" linespacing="0.0" rightmargin="0.0" spaceabove="0.0" spacebelow="0.0" style="Text"/><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">We first set up the equation:</Text-field><Text-field layout="Normal" style="Text"> </Text-field></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">q := t -&gt; 1-t/T:</Text-field></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">pde := diff(u(t, z), t)+r*(q(t)-z)*diff(u(t, z), z)+1/2*(q(t)-z)^2*sigma^2*diff(u(t, z), z, z) = 0;</Text-field></Input><Output><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiM+SSRwZGVHNiIvLCgtSSVkaWZmR0kqcHJvdGVjdGVkR0YqNiQtSSJ1R0YlNiRJInRHRiVJInpHRiVGLyIiIiooSSJyR0YlRjEsKEYxRjEqJkYvRjFJIlRHRiUhIiJGN0YwRjdGMS1GKTYkRixGMEYxRjEqKEY0IiIjSSZzaWdtYUdGJUY7LUYpNiRGLC1JIiRHRio2JEYwRjtGMSNGMUY7IiIh</Equation></Text-field></Output></Group><Group><Input><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">Boundary conditions.</Text-field><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">ibc1 := u(T, z) = Heaviside(z)*z;
ibc2 := u(t, -1) = 0;
ibc3 := D[2](u)(t, 1) = 1; </Text-field></Input><Output><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiM+SSVpYmMxRzYiLy1JInVHRiU2JEkiVEdGJUkiekdGJSomLUkqSGVhdmlzaWRlRzYkSSpwcm90ZWN0ZWRHRjBJKF9zeXNsaWJHRiU2I0YrIiIiRitGMw==</Equation></Text-field></Output></Group><Group><Output><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiM+SSVpYmMyRzYiLy1JInVHRiU2JEkidEdGJSEiIiIiIQ==</Equation></Text-field></Output></Group><Group><Output><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiM+SSVpYmMzRzYiLy0tJkkiREc2JEkqcHJvdGVjdGVkR0YsSShfc3lzbGliR0YlNiMiIiM2I0kidUdGJTYkSSJ0R0YlIiIiRjQ=</Equation></Text-field></Output></Group><Group><Input><Text-field layout="Normal" style="Text">Let's assume a fixed time period of 1 year, a starting price of $100, a strike price of $100, and <Equation input-equation="sigma = 0.2, r = 0.15" style="2D Math">NiM2JC9JJnNpZ21hRzYiLUkmRmxvYXRHSSpwcm90ZWN0ZWRHRik2JCIiIyEiIi9JInJHRiYtRig2JCIjOiEiIw==</Equation></Text-field><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">T := 1; S0 := 100.; K := 100.; sigma := 0.2; r := 0.15;</Text-field></Input><Output><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiM+SSJURzYiIiIi</Equation></Text-field><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiM+SSNTMEc2IiQiJCsiIiIh</Equation></Text-field><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiM+SSJLRzYiJCIkKyIiIiE=</Equation></Text-field><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiM+SSZzaWdtYUc2IiQiIiMhIiI=</Equation></Text-field><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiM+SSJyRzYiJCIjOiEiIw==</Equation></Text-field></Output></Group><Group><Input><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">Now we solve the PDE numerically using Maple's built-in solver.</Text-field><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">pds := pdsolve(pde, {ibc1, ibc2, ibc3}, numeric, spacestep = 0.001, timestep = 0.001):
val := pds:-value(t = 0, output = listprocedure):
v := eval(u(t, z), val):
</Text-field></Input></Group><Group><Input><Text-field layout="Normal" style="Text">Finally, we evaluate <Equation input-equation="S[0]*u*(0, (S[0]-K)/S[0])" style="2D Math">NiMqKCZJIlNHNiI2IyIiISIiIkkidUdGJkYpNiRGKComLCZGJEYpSSJLR0YmISIiRilGJEYvRik=</Equation> at Maple's numerical solution of <Equation input-equation="u(z,t)" style="2D Math">NiMtSSJ1RzYiNiRJInpHRiVJInRHRiU=</Equation>.  This gives a price of $8.40088.  This will provide a benchmark for the next  solution approach.</Text-field><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">S0*v((S0-K)/S0);</Text-field></Input><Output><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiMkIjUrKyQ0YXMnenkzJSkhIz4=</Equation></Text-field></Output></Group></Section><Section collapsed="true"><Title><Text-field layout="Heading 1" style="Heading 1">Solution 2: Monte Carlo simulation </Text-field></Title><Group><Input><Text-field layout="Normal" style="Text">Monte Carlo is one of the most popular methods for pricing securities whose prices are given in terms of expected values. The approach consists of the following steps:</Text-field><Text-field layout="Normal" style="Text"/><Text-field bullet="dot" layout="Normal" style="Text">simulate sample paths of the underlying assets</Text-field><Text-field bullet="dot" layout="Normal" style="Text">evaluate the discounted cash flows of the derivative security on each sample path</Text-field><Text-field bullet="dot" layout="Normal" style="Text">average the discounted cash flows over the sample paths.</Text-field></Input><Input><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" style="Text">To generate sample paths, we will use Marsaglia's random variate generator, implemented as an external C++ routine:</Text-field><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text"><Font bold="true" family="Monospaced">void MCInitialize() 
{ 
    Ziggurat::Reset();
}</Font>
</Text-field><Text-field layout="Normal" style="Text">Maple's interface to the above C++ routine is defined in the Initialization section:</Text-field><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" style="Text">The following C++ function generates a sample stock path.</Text-field><Text-field layout="Normal" style="Text"><Font bold="true" family="Monospaced">
void MCSamplePath(double *S, int N, double T, double S0, double r, double sigma)
{
    double h = 1./(N-1);
    double C = exp(r*h-sigma*sigma*h/2);

    S[0] = S0;
    for (int i = 0; i &lt; N-1; i++) {
        S[i+1] = S[i]*C*exp(sigma*sqrt(h)*Ziggurat::Next());
    }
}</Font>
</Text-field><Text-field layout="Normal" style="Text">We have defined a corresponding Maple routine called <Font bold="true">MCSamplePath</Font> that invokes this C++ routine:</Text-field><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">T := 1.: sigma := 0.2: r := 0.15: S0 := 100.:</Text-field></Input></Group><Group><Input><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" style="Text">Generate a sample path</Text-field><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">MCSamplePath(S, N, T, S0, r, sigma);</Text-field></Input></Group><Group><Input><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">Plot the sample path.</Text-field><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">plots[pointplot]([seq([(i-1)*T/N, S[i]], i = 1..N)], connect = true);</Text-field></Input><Output><Text-field layout="Maple Plot"><Plot height="400" plot-scale="1.0" plot-xtrans="0.0" plot-ytrans="0.0" type="two-dimensional" 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layout="Normal" prompt="&gt; " style="Maple Input">K := 100.;</Text-field></Input><Output><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiM+SSJLRzYiJCIkKyIiIiE=</Equation></Text-field></Output></Group><Group><Input><Text-field layout="Normal" style="Text">The estimated price of the option using 10 sample paths</Text-field></Input></Group><Group><Input><Text-field alignment="left" bullet="none" firstindent="0.0" leftmargin="0.0" linebreak="space" linespacing="0.0" prompt="&gt; " rightmargin="0.0" spaceabove="0.0" spacebelow="0.0" style="Maple Input">ArithmeticAsian(T, S0, r, sigma, K, 10^4, 10, MCSamplePath);</Text-field></Input><Output><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiMkIit0TUYnbyghIio=</Equation></Text-field></Output></Group><Group><Input><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">And using 10,000 sample paths.  We note that the estimated price is closer but not identical to the results obtained by the PDE approach.  </Text-field></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">ArithmeticAsian(T, S0, r, sigma, K, 10^4, 10^4, MCSamplePath);</Text-field></Input><Output><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiMkIispXHp6RSkhIio=</Equation></Text-field></Output></Group><Group><Input><Text-field layout="Normal" style="Text"/><Text-field layout="Normal" style="Text">One of the main weaknesses of the MC approach is that it tends to waste points due to clustering. This compromises performance when the sample size is small (or the dimension is large). We can often improve the performance by holding more regularly distributed (usually deterministic) points using a technique called Quasi Monte Carlo simulation, which we do using the C++ routine <Font bold="true">QMCSamplePath</Font>.</Text-field><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">P := Array(1..4):
for j from 1 to 4 do
    QMCSamplePath(S2, N2, T, S0, r, sigma);
    P[j] := plots[pointplot]([seq([(i-1)*T/N2, S[i]], i = 1..N2)], connect = true);
end do:
plots[display](convert(P, list));</Text-field></Input><Output><Text-field layout="Maple Plot"><Plot height="400" plot-scale="1.0" plot-xtrans="0.0" plot-ytrans="0.0" type="two-dimensional" 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layout="Normal" style="Text">Using the Quasi Monte Carlo simulation method, we arrive at virtually the same price as with the PDEs approach.</Text-field><Text-field layout="Normal" style="Text"/></Input></Group><Group><Input><Text-field layout="Normal" prompt="&gt; " style="Maple Input">ArithmeticAsian(T, S0, r, sigma, K, N, 10^5, QMCSamplePath);</Text-field></Input><Output><Text-field layout="Maple Output" style="2D Output"><Equation style="2D Output">NiMkIiskKTQtNyUpISIq</Equation></Text-field></Output></Group><Text-field/><Text-field/></Section><Group><Input><Text-field layout="Normal" style="Text"><Font italic="true">
Legal Notice: The copyright for this application is owned by Maplesoft. The application is intended to demonstrate the use of Maple to solve a particular problem. It has been made available for product evaluation purposes only and may not be used in any other context without the express permission of Maplesoft.  </Font>
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