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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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48 results for Barrier Functions

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

2008-09-10abs ↗pdf ↗

Research provides explicit NPV expressions for double barrier strategies.

problem Calculating expected NPVs of double barrier strategies for regular diffusions.
method Explicit expression using bivariate q-scale function with perturbation technique.
result Explicit expressions for expected NPVs are derived for certain cases.

This paper is devoted to the pricing of Barrier options by optimal quadratic quantization method. From a known useful representation of the premium of barrier options one deduces an algorithm similar to one used to estimate nonlinear filter using quadratic optimal functional quantization. Some numerical tests are fulfi…

2010-12-05abs ↗pdf ↗

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…

2013-12-11abs ↗pdf ↗

New technique improves submodular maximization with barrier functions.

problem Maximizing submodular functions under complex constraints.
method Inspired by barrier functions in continuous optimization, a novel potential function is proposed for approximate minimization.
result Guaranteed 2(k+1+ε)2(k+1+ε)-approximation factor for feasible sets.

Many problems in statistical learning, imaging, and computer vision involve the optimization of a non-convex objective function with singularities at the boundary of the feasible set. For such challenging instances, we develop a new interior-point technique building on the Hessian-barrier algorithm recently introduced …

2019-11-04abs ↗pdf ↗

The paper proves barriers to approximating functions with small weights and depth in neural networks.

problem Proving barriers to approximating functions with constant depth neural networks.
method Reduction to open problems and natural-proof barriers in circuit complexity, and a new approach to polynomially-bounded functions.
result There are fundamental barriers to proving results beyond depth 4 for constant-depth neural networks.

Develops semi-closed form solutions for barrier and American options on time-dependent OU process.

problem Valuation of barrier and American options on a time-dependent Ornstein-Uhlenbeck process.
method Semi-closed form solutions involving numerical solution of Fredholm equations and integration of Jacobi theta functions.
result Method is more efficient than backward finite difference method and can be as efficient as forward finite difference solver with better accuracy and stability.

A new sampling method for log-concave distributions with warm starts and barriers.

problem Sampling from log-concave distributions constrained by convex bodies with barriers.
method Robust sampling framework using spectral approximations to Hessian of barrier functions.
result Improved mixing times for polytopes and spectrahedra, faster than previous methods.

Path integral method calculates PDBS option prices with time-dependent parameters.

problem Pricing proportional double-barrier step options with time-dependent interest rates and volatilities.
method Path integral method applied to a quantum mechanical analogy of barrier options.
result Derivation of pricing kernel for PDBS options with time-dependent parameters.

Study on size and depth of neural networks for approximating benign functions, showing barriers and explicit results.

problem Understanding how size and depth of neural networks affect their ability to approximate benign functions.
method Analyzing ReLU networks for benign functions, proving barriers and explicit results.
result Explicit benign functions that cannot be approximated by networks of certain sizes or depths, showing barriers to size and depth separation.

Optimizes dividend control in a bankruptcy process using a special Levy process.

problem Optimizing dividend payouts in a bankruptcy process.
method Using a non-standard spectrally negative Levy process with endogenous regime switching.
result Optimal dividend control is of the barrier type and the optimal barrier can be identified.

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

problem IPMs' efficiency is hindered in hyperbolic spaces.
method Analyzing the barrier parameter growth in hyperbolic and Hadamard spaces.
result The barrier parameter grows polynomially with the domain's diameter in hyperbolic spaces.

We consider an insurance company modelling its surplus process by a Brownian motion with drift. Our target is to maximise the expected exponential utility of discounted dividend payments, given that the dividend rates are bounded by some constant. The utility function destroys the linearity and the time homogeneity of …

2018-09-06abs ↗pdf ↗

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

problem Calculating prices for multi-step barrier options with varying barriers and time steps.
method Derives a general, explicit expression for option prices using the Black-Scholes model and a multi-step reflection principle.
result Derives a multi-step reflection principle that generalizes the reflection principle of Brownian motion.

We revisit the dividend payment problem in the dual model of Avanzi et al. ([2], [1], and [3]). Using the fluctuation theory of spectrally positive Lévy processes, we give a short exposition in which we show the optimality of barrier strategies for all such Lévy processes. Moreover, we characterize the optimal barrier …

2012-11-30abs ↗pdf ↗

For a given Markov process XX and survival function H\overline{H} on R+\mathbb{R}^+, the inverse first-passage time problem (IFPT) is to find a barrier function b:R+[,+]b:\mathbb{R}^+\to[-\infty,+\infty] such that the survival function of the first-passage time τb=inf{t0:X(t)<b(t)}τ_b=\inf \{t\ge0:X(t)<b(t)\} is given by H\overline{H}. In …

2013-06-12abs ↗pdf ↗

RHMC improves sampling polytopes defined by inequalities with barriers.

problem Sampling polytopes defined by inequalities efficiently.
method Riemannian Hamiltonian Monte Carlo (RHMC) with a hybrid of Lewis weights and logarithmic barriers.
result RHMC achieves mixing rate of ildeO(m1/3n4/3) ilde O(m^{1/3}n^{4/3}) for polytopes defined by mm inequalities in Rn\R^n.

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

problem Option pricing under Vasicek interest rate model with time-varying interest rates.
method Splitting time to maturity into infinite steps and using quantum mechanics methods for matrix elements, derived pricing kernel and integral expression.
result Numerical results of option prices as functions of underlying asset price, floating rate, and regression rate.

The Monte Carlo pathwise sensitivities approach is well established for smooth payoff functions. In this work, we present a new Monte Carlo algorithm that is able to calculate the pathwise sensitivities for discontinuous payoff functions. Our main tool is to combine the one-step survival idea of Glasserman and Staum wi…

2018-04-11abs ↗pdf ↗

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

problem Analyzing ancient caloric functions on manifolds beyond volume doubling.
method Time polynomial structure result on ancient caloric functions with polynomial growth.
result Finiteness result for ancient caloric functions is essentially sharp, except for multi-end cases.

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…

2016-07-31abs ↗pdf ↗

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

problem Pricing and calibration of double barrier options with time-dependent parameters.
method Two approaches: General Integral transform method and Heat Potential method.
result Semi-analytic techniques are more efficient for pricing double barrier options than traditional numerical methods.

The paper certifies neural network-based control barrier functions efficiently.

problem Certifying neural network-based barrier functions for safety in autonomous systems.
method Combines NN reachability and hyperplane arrangement enumeration for efficient certification.
result Soundly finds regions where neural networks are certified as barrier functions.

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…

2013-03-06abs ↗pdf ↗

Efficient hybrid method for pricing barrier options with stochastic volatility.

problem Valuation of barrier options on assets with stochastic volatility.
method Combining Monte Carlo simulation and semi-analytical heat potential method.
result Our method provides better accuracy and is orders of magnitude faster than existing methods.

Unified control theory and machine learning for safety in uncertain systems.

problem Safety guarantees for systems with measurement model uncertainty.
method Measurement-Robust Control Barrier Functions (MR-CBFs) for control synthesis.
result MR-CBFs ensure safety in perception systems with measurement model uncertainty.

Optimal reinsurance and dividend strategy for insurance companies in a finite time.

problem Maximizing dividends while managing risk in a finite time horizon.
method Dynamic control problem with Hamilton-Jacobi-Bellman equation, penalty approximation method.
result Smoothness of the value function and comparison principle for its gradient.

Develops a new method for pricing barrier options in time-dependent Heston model.

problem Pricing barrier options in a time-dependent Heston model with stochastic volatility.
method General Integral Transforms (GIT) method for a two-dimensional integral representation.
result Shows that the GIT method can be extended to two drivers with inhomogeneous correlation.

New method tackles bilevel optimization with polyhedral constraints.

problem Challenges in bilevel optimization with active-set changes and expensive Hessian inversions.
method Logarithmic barrier smoothing and proxy-gradient algorithm for differentiable approximation.
result Stationarity rates of O(K2/3)O(K^{-2/3}) in deterministic setting and O(K2/5)O(K^{-2/5}) under stochastic noise.

A scalable framework optimizes multi-asset portfolios with constraints.

problem Optimizing multi-asset portfolios with inequality constraints.
method Integrates neural policies with Pontryagin's Maximum Principle, enforcing feasibility via log-barrier regularization.
result Recover KKT-optimal policies in high-dimensional problems without violating constraints.