A general method to construct recombinant tree approximations for stochastic
volatility models is developed and applied to the Heston model for stock price
dynamics. In this application, the resulting approximation is a four tuple
Markov process. The ?first two components are related to the stock and
volatility processes and take values in a two dimensional Binomial tree. The
other two components of the Markov process are the increments of random walks
with simple values in {-1; +1}.
We prove limit theorems for the super-replication cost of European options in
a Binomial model with friction. The examples covered are markets with
proportional transaction costs and the illiquid markets. The dual
representation for the super-replication cost in these models are obtained and
used to prove the limit theorems. In particular, the existence of the liquidity
premium for the continuous time limit of the model proposed in [6] is proved.
Hence, this paper extends the previous convergence result of [13] to the
general non-Markovian case.
We study the problem of super-replication for game options under proportional
transaction costs. We consider a multidimensional model which is an extension
of the usual Black-Scholes (BS) model, in the sense that the volatility is a
progressively measurable function of the stock. For this case we show that the
super-replication price is the cheapest cost of a trivial super-replication
strategy. This result is an extension of previous papers (see [1], [2], [10]
and [11]) in which only European options with Markovian structure were
considered.
We show that shortfall risks of American options in a sequence of multinomial
approximations of the multidimensional Black--Scholes (BS) market converge to
the corresponding quantities for similar American options in the
multidimensional BS market with path dependent payoffs. In comparison to
previous papers we consider the multi assets case for which we use the weak
convergence approach.
We derive error estimates for multinomial approximations of American options
in a multidimensional jump--diffusion Merton's model. We assume that the
payoffs are Markovian and satisfy Lipschitz type conditions. Error estimates
for such type of approximations were not obtained before. Our main tool is the
strong approximations theorems for i.i.d. random vectors which were obtained
[14]. For the multidimensional Black--Scholes model our results can be extended
also to a general path dependent payoffs which satisfy Lipschitz type
conditions.
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.
This paper studies stability of Dynkin's games value under weak convergence.
We use these results to approximate game options prices with path dependent
payoffs in continuous time models by sequence of game options prices in
discrete time models which can be calculated by dynamical programming
algorithms. We also show that shortfall risks of American options in a sequence
of multinomial approximations of the multidimensional BS market converge to the
corresponding quantities for similar American options in the multidimensional
BS market with path dependent payoffs.