8,307 research outputs found
Portfolio Selection in Incomplete Markets with Utility Maximisation
The problem of maximizing the expected utility is well understood in the context of a complete financial market. This dissertation studies the same problem in an arbitrage-free yet incomplete market. Jin and Zhou have characterized the set of the terminal wealths that can be replicated by admissible portfolios. The problem is then transformed into a static optimization problem. It is proved that the terminal wealth is attainable for all utility functions when the market parameters are deterministic. The optimal portfolio is obtained explicitly when the utility function is logarithmic even if the market parameters follow stochastic processes. However we do not succeed in extending this result to the power utility function
Option pricing with transaction costs using a Markov chain approximation
An efficient algorithm is developed to price European options in the presence of proportional transaction costs, using the optimal portfolio framework of Davis (in: Dempster, M.A.H., Pliska, S.R. (Eds.), Mathematics of Derivative Securities. Cambridge University Press, Cambridge, UK). A fair option price is determined by requiring that an infinitesimal diversion of funds into the purchase or sale of options has a neutral effect on achievable utility. This results in a general option pricing formula, in which option prices are computed from the solution of the investor's basic portfolio selection problem, without the need to solve a more complex optimisation problem involving the insertion of the option payoff into the terminal value function. Option prices are computed numerically using a Markov chain approximation to the continuous time singular stochastic optimal control problem, for the case of exponential utility. Comparisons with approximately replicating strategies are made. The method results in a uniquely specified option price for every initial holding of stock, and the price lies within bounds which are tight even as transaction costs become large. A general definition of an option hedging strategy for a utility maximising investor is developed. This involves calculating the perturbation to the optimal portfolio strategy when an option trade is executed
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Migration, credit markets, moral hazard, interlinkage.
A fast numerical algorithm is developed to price European options with
proportional transaction costs using the utility maximization framework
of Davis (1997). This approach allows option prices to be computed by
solving the investor's basic portfolio selection problem, without the inser-
tion of the option payo into the terminal value function. The properties
of the value function can then be used to drastically reduce the number of
operations needed to locate the boundaries of the no transaction region,
which leads to very e cient option valuation. The optimization problem
is solved numerically for the case of exponential utility, and comparisons
with approximately replicating strategies reveal tight bounds for option
prices even as transaction costs become large. The computational tech-
nique involves a discrete time Markov chain approximation to a continuous
time singular stochastic optimal control problem. A general de nition of
an option hedging strategy in this framework is developed. This involves
calculating the perturbation to the optimal portfolio strategy when an
option trade is execute
Efficient option pricing with transaction costs
A fast numerical algorithm is developed to price European options with proportional transaction costs using the utility-maximization framework of Davis (1997). This approach allows option prices to be computed by solving the investor’s basic portfolio selection problem without insertion of the option payoff into the terminal value function. The properties of the value function can then be used to drastically reduce the number of operations needed to locate the boundaries of the no-transaction region, which leads to very efficient option valuation. The optimization problem is solved numerically for the case of exponential utility, and comparisons with approximately replicating strategies reveal tight bounds for option prices even as transaction costs become large. The computational technique involves a discrete-time Markov chain approximation to a continuous-time singular stochastic optimal control problem. A general definition of an option hedging strategy in this framework is developed. This involves calculating the perturbation to the optimal portfolio strategy when an option trade is executed
On the Exact Solution of the Multi-Period Portfolio Choice Problem for an Exponential Utility under Return Predictability
In this paper we derive the exact solution of the multi-period portfolio
choice problem for an exponential utility function under return predictability.
It is assumed that the asset returns depend on predictable variables and that
the joint random process of the asset returns and the predictable variables
follow a vector autoregressive process. We prove that the optimal portfolio
weights depend on the covariance matrices of the next two periods and the
conditional mean vector of the next period. The case without predictable
variables and the case of independent asset returns are partial cases of our
solution. Furthermore, we provide an empirical study where the cumulative
empirical distribution function of the investor's wealth is calculated using
the exact solution. It is compared with the investment strategy obtained under
the additional assumption that the asset returns are independently distributed.Comment: 16 pages, 2 figure
Option Pricing with Transaction Costs Using a Markov Chain Approximation
An e cient algorithm is developed to price European options in the pres-
ence of proportional transaction costs, using the optimal portfolio frame-
work of Davis (1997). A fair option price is determined by requiring that
an in nitesimal diversion of funds into the purchase or sale of options
has a neutral e ect on achievable utility. This results in a general option
pricing formula, in which option prices are computed from the solution of
the investor's basic portfolio selection problem, without the need to solve
a more complex optimisation problem involving the insertion of the op-
tion payo into the terminal value function. Option prices are computed
numerically using a Markov chain approximation to the continuous time
singular stochastic optimal control problem, for the case of exponential
utility. Comparisons with approximately replicating strategies are made.
The method results in a uniquely speci ed option price for every initial
holding of stock, and the price lies within bounds which are tight even as
transaction costs become large. A general de nition of an option hedg-
ing strategy for a utility maximising investor is developed. This involves
calculating the perturbation to the optimal portfolio strategy when an
option trade is executed
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Finite Horizon Portfolio Selection
We study the problem of maximising expected utility of terminal wealth
over a nite horizon, with one risky and one riskless asset available, and
with trades in the risky asset subject to proportional transaction costs.
In a discrete time setting, using a utility function with hyperbolic risk
aversion, we prove that the optimal trading strategy is characterised by
a function of time (t), which represents the ratio of wealth held in the
risky asset to that held in the riskless asset. There is a time varying no
transaction region with boundaries b(t) < s(t), such that the portfo-
lio is only rebalanced when (t) is outside this region. The results are
consistent with similar studies of the in nite horizon problem with in-
termediate consumption, where the no transaction region has a similar,
but time independent, characterisation. We solve the problem numerically
and compute the boundaries of the no transaction region for typical model
parameters. We show how the results can be used to implement option
pricing models with transaction costs based on utility maximisation over
a nite horizo
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