arXiv research

A new method uses deep learning to price barrier options.

We discuss the pricing methodology for Bonus Certificates and Barrier Reverse-Convertible Structured Products. Pricing for a European barrier condition is straightforward for products of both types and depends on an efficient interpolation of observed market option pricing. Pricing products We discuss the pricing metho…

Deep learning solves barrier options with stochastic volatility.

Root's barrier is continuous and finite under certain conditions.

We develop a conditional sampling scheme for pricing knock-out barrier options under the Linear Transformations (LT) algorithm from Imai and Tan (2006). We compare our new method to an existing conditional Monte Carlo scheme from Glasserman and Staum (2001), and show that a substantial variance reduction is achieved. W…

Sequential Monte Carlo (SMC) methods have successfully been used in many applications in engineering, statistics and physics. However, these are seldom used in financial option pricing literature and practice. This paper presents SMC method for pricing barrier options with continuous and discrete monitoring of the barr…

The conditional-mean barrier helps diagnose deterministic surrogates missing uncertainty.

Research provides explicit NPV expressions for double barrier strategies.

We use Lie symmetry methods to price certain types of barrier options. Usually Lie symmetry methods cannot be used to solve the Black-Scholes equation for options because the function defining the maturity condition for an option is not smooth. However, for barrier options, this restriction can be accommodated and a sy…

We propose a quasi-Monte Carlo algorithm for pricing knock-out and knock-in barrier options under the Heston (1993) stochastic volatility model. This is done by modifying the LT method from Imai and Tan (2006) for the Heston model such that the first uniform variable does not influence the stochastic volatility path an…

Barrier methods classify minimal submanifolds in hyperkaehler spaces.

This paper deals with a high-order accurate implicit finite-difference approach to the pricing of barrier options. In this way various types of barrier options are priced, including barrier options paying rebates, and options on dividend-paying-stocks. Moreover, the barriers may be monitored either continuously or disc…

IPMs struggle with hyperbolic spaces due to polynomially growing barrier parameters.

Efficient hybrid method for pricing barrier options with stochastic volatility.

Improved MLMC method for barrier options with non-Lipschitz coefficients.

In [8] Gerhardt proves longtime existence for the inverse mean curvature flow in globally hyperbolic Lorentzian manifolds with compact Cauchy hypersurface, which satisfy three main structural assumptions: a strong volume decay condition, a mean curvature barrier condition and the timelike convergence condition. Further…

The paper uses a Hamiltonian method to price barrier options under Vasicek interest rate model.

Study on existence and structure of P-area surfaces in Heisenberg group.

The paper calculates prices for multi-step barrier options under the Black-Scholes model.

Alternative solvability criterion for minimal surface equations and mean curvature flow.

As is known, an option price is a solution to a certain partial differential equation (PDE) with terminal conditions (payoff functions). There is a close association between the solution of PDE and the solution of a backward stochastic differential equation (BSDE). We can either solve the PDE to obtain option prices or…

We demonstrate effectiveness of the first-order algorithm from [Milstein, Tretyakov. Theory Prob. Appl. 47 (2002), 53-68] in application to barrier option pricing. The algorithm uses the weak Euler approximation far from barriers and a special construction motivated by linear interpolation of the price near barriers. I…

This paper concerns the dual risk model, dual to the risk model for insurance applications, where premiums are surplus-dependent. In such a model premiums are regarded as costs, while claims refer to profits. We calculate the mean of the cumulative discounted dividends paid until ruin, if the barrier strategy is applie…

A scalable framework optimizes multi-asset portfolios with constraints.

Ancient caloric functions on manifolds with polynomial growth are studied under volume doubling barrier.

We determine the price of digital double barrier options with an arbitrary number of barrier periods in the Black-Scholes model. This means that the barriers are active during some time intervals, but are switched off in between. As an application, we calculate the value of a structure floor for structured notes whose …

A time-dependent double-barrier option is a derivative security that delivers the terminal value $φ(S_T)$ at expiry $T$ if neither of the continuous time-dependent barriers $b_\pm:[0,T]\to \RR_+$ have been hit during the time interval $[0,T]$. Using a probabilistic approach we obtain a decomposition of the barrier opti…

Efficient semi-analytic methods for pricing double barrier options with time-dependent parameters.

We provided an analytical representation of the price of a barrier option with one type of special moving barrier. We consider the case that risk free rate, dividend rate and stock volatility are time dependent. We get a pricing formula and put call parity for barrier option when the moving barrier has a special relati…

Hamiltonian method applied to floating barrier options pricing.

Expectation propagation (EP) is a powerful approximate inference algorithm. However, a critical barrier in applying EP is that the moment matching in message updates can be intractable. Handcrafting approximations is usually tricky, and lacks generalizability. Importance sampling is very expensive. While Laplace propag…

We investigate the pricing of financial options under the 2-hypergeometric stochastic volatility model. This is an analytically tractable model that reproduces the volatility smile and skew effects observed in empirical market data. Using a regular perturbation method from asymptotic analysis of partial differential eq…

New efficient method for inverse Z-transform reduces complexity significantly.

The study examines a semi-symmetric metric connection in perfect fluid space-time and phantom barriers.

New method tackles bilevel optimization with polyhedral constraints.

Unified pricing method for FX options with barriers.

Path integral method calculates barrier option prices.

Post-training optimizes model performance beyond base model limits.

New study reveals a polynomial penalty for adapting to unknown margin parameters in batched nonparametric bandits.

We prove that the leaves of an inverse mean curvature flow provide a foliation of a future end of a cosmological spacetime $N$ under the necessary and sufficent assumptions that $N$ satisfies a future mean curvature barrier condition and a strong volume decay condition. Moreover, the flow parameter $t$ can be used to d…

For a given Markov process $X$ and survival function $\overline{H}$ on $\mathbb{R}^+$, the inverse first-passage time problem (IFPT) is to find a barrier function $b:\mathbb{R}^+\to[-\infty,+\infty]$ such that the survival function of the first-passage time $τ_b=\inf \{t\ge0:X(t)<b(t)\}$ is given by $\overline{H}$. In …

New method uncovers zero entropy in dependent observations after finite samples.

New CMC existence result for expanding cosmological spacetimes.

New symplectic barriers found in ball embeddings.

This work refines claims about neural network connectivity, showing that simultaneous linear connectivity is possible under certain conditions.

Paper applies subdiffusive dynamics to American and barrier options pricing.

We prove the existence and uniqueness of radial graphs over a given domain of $\mathbb{S}^{n}$ having boundary on the sphere $\mathbb{S}^{n}$ and whose mean curvature at every point equals a prescribed positive function satisfying suitable barrier-type and monotonicity conditions.

Barrier options are one of the most widely traded exotic options on stock exchanges. In this paper, we develop a new stochastic simulation method for pricing barrier options and estimating the corresponding execution probabilities. We show that the proposed method always outperforms the standard Monte Carlo approach an…