19,459 research outputs found
Local Risk-Minimization under Transaction Costs
We propose a new approach to the pricing and hedging of contingent claims under transaction costs in a general incomplete market in discrete time. Under the assumptions of a bounded mean-variance tradeoff, substantial risk and a nondegeneracy condition on the conditional variances of asset returns, we prove the existence of a locally risk-minimizing strategy inclusive of transaction costs for every square-integrable contingent claim. Then we show that local riskminimization is robust under the inclusion of transaction costs: The preceding strategy which is locally risk-minimizing inclusive of transaction costs in a model with bid-ask spreads on the underlying asset is also locally risk-minimizing without transaction costs in a fictitious model which is frictionless and where the fictitious asset price lies between the bid and ask price processes of the original model. In particular, our results apply to any nondegenerate model with a finite state space if the transaction cost parameter is sufficiently small
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 investorâs 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
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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
Limit Theorems for Partial Hedging Under Transaction Costs
We study shortfall risk minimization for American options with path dependent
payoffs under proportional transaction costs in the Black--Scholes (BS) model.
We show that for this case the shortfall risk is a limit of similar terms in an
appropriate sequence of binomial models. We also prove that in the continuous
time BS model for a given initial capital there exists a portfolio strategy
which minimizes the shortfall risk. In the absence of transactions costs
(complete markets) similar limit theorems were obtained in Dolinsky and Kifer
(2008, 2010) for game options. In the presence of transaction costs the markets
are no longer complete and additional machinery required. Shortfall risk
minimization for American options under transaction costs was not studied
before
Combining Alpha Streams with Costs
We discuss investment allocation to multiple alpha streams traded on the same
execution platform with internal crossing of trades and point out differences
with allocating investment when alpha streams are traded on separate execution
platforms with no crossing. First, in the latter case allocation weights are
non-negative, while in the former case they can be negative. Second, the
effects of both linear and nonlinear (impact) costs are different in these two
cases due to turnover reduction when the trades are crossed. Third, the
turnover reduction depends on the universe of traded alpha streams, so if some
alpha streams have zero allocations, turnover reduction needs to be recomputed,
hence an iterative procedure. We discuss an algorithm for finding allocation
weights with crossing and linear costs. We also discuss a simple approximation
when nonlinear costs are added, making the allocation problem tractable while
still capturing nonlinear portfolio capacity bound effects. We also define
"regression with costs" as a limit of optimization with costs, useful in
often-occurring cases with singular alpha covariance matrix.Comment: 21 pages; minor misprints corrected; to appear in The Journal of Ris
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