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Explore Single-Period Asset Arbitrage

This example explores basic arbitrage concepts in a single-period, two-state asset portfolio. The portfolio consists of a bond, a long stock, and a long call option on the stock.

It uses these Symbolic Math Toolbox™ functions:

  • equationsToMatrix to convert a linear system of equations to a matrix.

  • linsolve to solve the system.

  • Symbolic equivalents of standard MATLAB® functions, such as diag.

This example symbolically derives the risk-neutral probabilities and call price for a single-period, two-state scenario.

Define Parameters of the Portfolio

Create the symbolic variable r representing the risk-free rate over the period. Set the assumption that r is a positive value.

syms r positive

Define the parameters for the beginning of a single period, time = 0. Here S0 is the stock price, and C0 is the call option price with strike, K.

syms S0 C0 K positive

Now, define the parameters for the end of a period, time = 1. Label the two possible states at the end of the period as U (the stock price over this period goes up) and D (the stock price over this period goes down). Thus, SU and SD are the stock prices at states U and D, and CU is the value of the call at state U. Note that SD<=K<=SU.

syms SU SD CU positive

The bond price at time = 0 is 1. Note that this example ignores friction costs.

Collect the prices at time = 0 into a column vector.

prices = [1 S0 C0]'
prices = 

(1S0C0)

Collect the payoffs of the portfolio at time = 1 into the payoff matrix. The columns of payoff correspond to payoffs for states D and U. The rows correspond to payoffs for bond, stock, and call. The payoff for the bond is 1 + r. The payoff for the call in state D is zero since it is not exercised (because SD<=K).

payoff = [(1 + r), (1 + r); SD, SU; 0, CU]
payoff = 

(r+1r+1SDSU0CU)

CU is worth SU - K in state U. Substitute this value in payoff.

payoff = subs(payoff, CU, SU - K)
payoff = 

(r+1r+1SDSU0SU-K)

Solve for Risk-Neutral Probabilities

Define the probabilities of reaching states U and D.

syms pU pD real

Under no-arbitrage, eqns == 0 must always hold true with positive pU and pD.

eqns = payoff*[pD; pU] - prices
eqns = 

(pDr+1+pUr+1-1SDpD-S0+SUpU-C0-pUK-SU)

Transform equations to use risk-neutral probabilities.

syms pDrn pUrn real;
eqns = subs(eqns, [pD; pU], [pDrn; pUrn]/(1 + r))
eqns = 

(pDrn+pUrn-1SDpDrnr+1-S0+SUpUrnr+1-C0-pUrnK-SUr+1)

The unknown variables are pDrn, pUrn, and C0. Transform the linear system to a matrix form using these unknown variables.

[A, b] = equationsToMatrix(eqns, [pDrn, pUrn, C0]')
A = 

(110SDr+1SUr+100-K-SUr+1-1)

b = 

(1S00)

Using linsolve, find the solution for the risk-neutral probabilities and call price.

x = linsolve(A, b)
x = 

(S0-SU+S0rSD-SU-S0-SD+S0rSD-SUK-SUS0-SD+S0rSD-SUr+1)

Verify the Solution

Verify that under risk-neutral probabilities, x(1:2), the expected rate of return for the portfolio, E_return equals the risk-free rate, r.

E_return = diag(prices)\(payoff - [prices,prices])*x(1:2);
E_return = simplify(subs(E_return, C0, x(3)))
E_return = 

(rrr)

Test for No-Arbitrage Violations

As an example of testing no-arbitrage violations, use the following values: r = 5%, S0 = 100, and K = 100. For SU < 105, the no-arbitrage condition is violated because pDrn = xSol(1) is negative (SU >= SD). Further, for any call price other than xSol(3), there is arbitrage.

xSol = simplify(subs(x, [r,S0,K], [0.05,100,100]))
xSol = 

(-SU-105SD-SUSD-105SD-SU20SD-105SU-10021SD-SU)

Plot Call Price as a Surface

Plot the call price, C0 = xSol(3), for 50 <= SD <= 100 and 105 <= SU <= 150. Note that the call is worth more when the "variance" of the underlying stock price is higher for example, SD = 50, SU = 150.

fsurf(xSol(3), [50,100,105,150])
xlabel SD
ylabel SU
title 'Call Price'

Figure contains an axes object. The axes object with title Call Price, xlabel SD, ylabel SU contains an object of type functionsurface.

Reference

Advanced Derivatives, Pricing and Risk Management: Theory, Tools and Programming Applications by Albanese, C., Campolieti, G.