Math 2.0

Game theory, economics, finance, and other social and behavioral sciences Portfolio theory Problem

Merton's portfolio problem

Builds on Stochastic optimal controlGeometric Brownian motionHamilton–Jacobi–Bellman equation

Problem

Consider a market with a riskless asset with interest rate rr and a stock. The stock price follows the geometric Brownian motion dSt=μSt dt+σSt dWtdS_t = \mu S_t \, dt + \sigma S_t \, dW_t, where μ>r\mu > r, σ>0\sigma > 0 and WW is a Wiener process. An investor with initial wealth x>0x > 0 chooses, at each time tt, the fraction πt\pi_t of wealth held in the stock and a consumption rate ct≥0c_t \ge 0. Both are adapted to the information generated by WW. The wealth then evolves by dXt=(rXt+πt(μ−r)Xt−ct)dt+πtσXt dWt,X0=x.dX_t = \left( r X_t + \pi_t (\mu - r) X_t - c_t \right) dt + \pi_t \sigma X_t \, dW_t, \qquad X_0 = x. Let ρ>0\rho > 0 be a discount rate and let U(c)=c1−γ1−γU(c) = \dfrac{c^{1 - \gamma}}{1 - \gamma} with γ>0\gamma > 0 and γ≠1\gamma \ne 1. The problem is to find the strategies (π,c)(\pi, c) with Xt≥0X_t \ge 0 for all tt that maximise the expected discounted utility of consumption E∫0∞e−ρtU(ct) dt.E \int_0^\infty e^{-\rho t} U(c_t) \, dt.

Remarks

The problem is solved, and it is a standard example of stochastic optimal control. Write θ=(μ−r)/σ\theta = (\mu - r) / \sigma and assume ν=ρ−(1−γ)(r+θ2/(2γ))γ>0\nu = \dfrac{\rho - (1 - \gamma)\left( r + \theta^2 / (2 \gamma) \right)}{\gamma} > 0. The value function is V(x)=ν−γU(x)V(x) = \nu^{-\gamma} U(x). The optimal strategy holds the constant fraction π∗=μ−rγσ2\pi^* = \dfrac{\mu - r}{\gamma \sigma^2} in the stock and consumes at the rate ct=νXtc_t = \nu X_t. These follow from the Hamilton–Jacobi–Bellman equation ρV=max⁡π,c{U(c)+V′(x)(rx+π(μ−r)x−c)+12σ2π2x2V′′(x)}\rho V = \max_{\pi, c} \left\{ U(c) + V'(x) \left( r x + \pi (\mu - r) x - c \right) + \frac{1}{2} \sigma^2 \pi^2 x^2 V''(x) \right\} with the guess V=AUV = A U for a constant A>0A > 0. Merton also treated a finite horizon with utility of final wealth, and the logarithmic utility U=ln⁡U = \ln, which is the limit case γ=1\gamma = 1 and gives π∗=(μ−r)/σ2\pi^* = (\mu - r) / \sigma^2 and ct=ρXtc_t = \rho X_t.

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  1. Geometric Brownian motion concept
  2. Hamilton–Jacobi–Bellman equation concept
  3. Stochastic optimal control concept
  4. Merton's portfolio problem problem

Further reading

  1. Web https://en.wikipedia.org/wiki/Merton%27s_portfolio_problem
About this page
TagDZKBF576W5
URIm2://DZKBF576W5
Kindproblem
WritingW0 stub
MSC91G10, 93E20, 49L20
StatusThis copy of the site has no build data. Run m2 status DZKBF576W5.
AboutStochastic optimal control
UsesStochastic optimal control, Geometric Brownian motion, Hamilton–Jacobi–Bellman equation
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