Merton's portfolio problem
Encyclopedia
Merton's Portfolio Problem is a well known problem in continuous-time finance
. An investor with a finite lifetime must choose how much to consume and must allocate his wealth between stocks and a risk-free asset so as to maximize expected lifetime utility
. The problem was formulated and solved by Robert C. Merton
in 1969; research has continued to extend and generalize the model.
The objective is
where E is the expectation operator, u is a known utility function (which applies both to consumption and to the terminal wealth, or bequest, WT) and δ is the subjective discount rate.
The wealth evolves according to the stochastic differential equation
where r is the risk-free rate, (μ, σ) are the expected return and volatility of the stock market and dBt is the increment of the Wiener process
, i.e. the stochastic term of the SDE.
Additional assumptions. The utility function is of the constant relative risk aversion (CRRA) form:
Consumption cannot be negative: ct ≥ 0, while πt is unrestricted (that is borrowing or shorting stocks is allowed).
Investment opportunities are assumed constant, that is r, μ, σ are known and constant, in this (1969) version of the model, although Merton later allowed them to change.
problem, a closed-form solution exists. The optimal consumption and stock allocation depend on wealth and time as follows:
(Note that W and t do not appear on the righ-hand side, this implies that a constant fraction of wealth is invested in stocks, no matter what the age or prosperity of the investor)
where A is a constant.
Finance
"Finance" is often defined simply as the management of money or “funds” management Modern finance, however, is a family of business activity that includes the origination, marketing, and management of cash and money surrogates through a variety of capital accounts, instruments, and markets created...
. An investor with a finite lifetime must choose how much to consume and must allocate his wealth between stocks and a risk-free asset so as to maximize expected lifetime utility
Utility
In economics, utility is a measure of customer satisfaction, referring to the total satisfaction received by a consumer from consuming a good or service....
. The problem was formulated and solved by Robert C. Merton
Robert C. Merton
Robert Carhart Merton is an American economist, Nobel laureate in Economics, and professor at the MIT Sloan School of Management.-Biography:...
in 1969; research has continued to extend and generalize the model.
Problem statement
The investor lives from time 0 to time T; his wealth at time t is denoted Wt. He starts with a known initial wealth W0 (which may include the present value of wage income). At time t he must choose what amount of his wealth to consume: ct and what fraction of wealth to invest in a stock portfolio: πt (the remaining fraction 1 − πt being invested in the risk-free asset).The objective is
where E is the expectation operator, u is a known utility function (which applies both to consumption and to the terminal wealth, or bequest, WT) and δ is the subjective discount rate.
The wealth evolves according to the stochastic differential equation
Stochastic differential equation
A stochastic differential equation is a differential equation in which one or more of the terms is a stochastic process, thus resulting in a solution which is itself a stochastic process....
where r is the risk-free rate, (μ, σ) are the expected return and volatility of the stock market and dBt is the increment of the Wiener process
Wiener process
In mathematics, the Wiener process is a continuous-time stochastic process named in honor of Norbert Wiener. It is often called standard Brownian motion, after Robert Brown...
, i.e. the stochastic term of the SDE.
Additional assumptions. The utility function is of the constant relative risk aversion (CRRA) form:
Consumption cannot be negative: ct ≥ 0, while πt is unrestricted (that is borrowing or shorting stocks is allowed).
Investment opportunities are assumed constant, that is r, μ, σ are known and constant, in this (1969) version of the model, although Merton later allowed them to change.
Solution
Somewhat surprisingly for an optimal controlOptimal control
Optimal control theory, an extension of the calculus of variations, is a mathematical optimization method for deriving control policies. The method is largely due to the work of Lev Pontryagin and his collaborators in the Soviet Union and Richard Bellman in the United States.-General method:Optimal...
problem, a closed-form solution exists. The optimal consumption and stock allocation depend on wealth and time as follows:
(Note that W and t do not appear on the righ-hand side, this implies that a constant fraction of wealth is invested in stocks, no matter what the age or prosperity of the investor)
where A is a constant.
Extensions
Many variations of the problem have been explored, but most do not lead to a simple closed-form solution.- A utility function other than CRRA can be used.
- Transaction costs can be introduced. For proportional transaction costs the problem was solved by Davis and Norman in 1990. It is one of the few cases of stochastic singular control where the solution is known. For a graphical representation, the amount invested in each of the two assets can be plotted on the x- and y-axes; three diagonal lines through the origin can be drawn: the upper boundary, the Merton line and the lower boundary. The Merton line represents portfolios having the stock/bond proportion derived by Merton in the absence of transaction costs. As long as the point which represents the current portfolio is near the Merton line, i.e. between the upper and the lower boundary, no action needs to be taken. When the portfolio crosses above the upper or below the lower boundary, one should rebalance the portfolio to bring it back to the boundary. In 1994 Shreve and Soner provided an analysis of the problem via the Hamilton–Jacobi–Bellman equation and its viscosity solutions.
- When there are fixed transaction costs the problem was addressed by Eastman and Hastings in 1988. A numerical solution method was provided by Schroder in 1995.
- Finally Morton and Pliska (1995) considered trading costs that are proportional to the wealth of the investor, as a kind of penalty to discourage frequent trading, although this cost structure seems unrepresentative of real life transaction costs.
- The assumption of constant investment opportunities can be relaxed. This requires a model for how
change over time. An interest rate model could be added and would lead to a portfolio containing bonds of different maturities. Some authors have added a stochastic volatility model of stock market returns.
- Additional assets can be added, for example individual stocks. However, the problem becomes difficult or intractable.
- Bankruptcy can be incorporated. This problem was solved by Karatzas, Lehoczky, Sethi and Shreve in 1986. Many models incorporating bankruptcy are collected in Sethi (1997).