Sharp asymptotic lower bounds of the expected quadratic variation of
discretization error in stochastic integration are given. The theory relies on
inequalities for the kurtosis and skewness of a general random variable which
are themselves seemingly new. Asymptotically efficient schemes which attain the
lower bounds are constructed explicitly. The result is directly applicable to
practical hedging problem in mathematical finance; it gives an asymptotically
optimal way to choose rebalancing dates and portofolios with respect to
transaction costs.
Explicit robust hedging strategies for convex or concave payoffs under a
continuous semimartingale model with uncertainty and small transaction costs
are constructed. In an asymptotic sense, the upper and lower bounds of the
cumulative volatility enable us to super-hedge convex and concave payoffs
respectively. The idea is a combination of Mykland's conservative delta hedging
and Leland's enlarging volatility. We use a specific sequence of stopping times
as rebalancing dates, which can be superior to equidistant one even when there
is no model uncertainty.
We study convex risk measures describing the upper and lower bounds of a good
deal bound, which is a subinterval of a no-arbitrage pricing bound. We call
such a convex risk measure a good deal valuation and give a set of equivalent
conditions for its existence in terms of market. A good deal valuation is
characterized by several equivalent properties and in particular, we see that a
convex risk measure is a good deal valuation only if it is given as a risk
indifference price. An application to shortfall risk measure is given.
We study specific nonlinear transformations of the Black-Scholes implied
volatility to show remarkable properties of the volatility surface. Model-free
bounds on the implied volatility skew are given. Pricing formulas for the
European options which are written in terms of the implied volatility are
given. In particular, we prove elegant formulas for the fair strikes of the
variance swap and the gamma swap.
The validity of an approximation formula for European option prices under a
general stochastic volatility model is proved in the light of the Edgeworth
expansion for ergodic diffusions. The asymptotic expansion is around the
Black-Scholes price and is uniform in bounded payoff func- tions. The result
provides a validation of an existing singular perturbation expansion formula
for the fast mean reverting stochastic volatility model.
Asymptotic error distribution for approximation of a stochastic integral with
respect to continuous semimartingale by Riemann sum with general stochastic
partition is studied. Effective discretization schemes of which asymptotic
conditional mean-squared error attains a lower bound are constructed. Two
applications are given; efficient delta hedging strategies with transaction
costs and effective discretization schemes for the Euler-Maruyama approximation
are constructed.