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48 results for delta function

We consider a strictly pathwise setting for Delta hedging exotic options, based on Föllmer's pathwise Itō calculus. Price trajectories are dd-dimensional continuous functions whose pathwise quadratic variations and covariations are determined by a given local volatility matrix. The existence of Delta hedging strategie…

2015-10-30abs ↗pdf ↗

Characterizes smiles in delta satisfying specific conditions.

problem Characterizing no butterfly arbitrage smiles in delta.
method Using parametrization of the smile in delta, we characterize the set of smiles.
result Obtained a parametrization of the set via one real number and three positive functions.

Study calculates liquidity costs for delta hedging of European options.

problem Determining expected liquidity costs in delta hedging.
method Derives an integration formula for liquidity costs, including option prices and delta process.
result Expected liquidity costs can be calculated faster than Monte Carlo simulations.

New methods for delta-moves on algebraically split links identified.

problem Understanding delta-moves on algebraically split links.
method Introducing self and mixed delta-moves, proving equivalence, and calculating delta-splitting numbers.
result Two links are mixed delta-equivalent if they have the same pairwise linking number and components.

Modelling stock prices via jump processes is common in financial markets. In practice, to hedge a contingent claim one typically uses the so-called delta-hedging strategy. This strategy stems from the Black--Merton--Scholes model where it perfectly replicates contingent claims. From the theoretical viewpoint, there is …

2011-03-25abs ↗pdf ↗

New metric to measure liquidity position PNL, delta hedging algorithm for automated market makers.

problem Vulnerability of liquidity positions to price changes in underlying assets.
method Proposes a new metric for measuring PNL, delta hedging algorithm for various AMMs.
result New metric more accurately measures net value change due to price movement.

Delta-unlinking number measures how to unlink algebraically split links.

problem Measuring unlinking complexity of algebraically split links.
method Defining delta-unlinking number as minimum delta-moves to unlink, proving bounds and calculating specific values.
result Precise delta-unlinking numbers for algebraically split prime links up to 9 crossings, and 4-genus values for most.

We develop techniques for studying fundamental groups and integral singular homology of symmetric Delta-complexes, and apply these techniques to study moduli spaces of stable tropical curves of unit volume, with and without marked points. As one application, we show that Delta_g and Delta_{g,n} are simply connected, fo…

2019-08-22abs ↗pdf ↗

Study pairs of subspaces with or without a common complement in Hilbert spaces.

problem Characterize pairs of subspaces with or without a common complement in Hilbert spaces.
method Analyze pairs of subspaces (S, T) in the Grassmann manifold Gr(H) of a Hilbert space H, identifying Delta and Gamma based on the existence of a common complement.
result Delta is open and its connected components are parametrized by dimension and codimension. Gamma is a C^\infty submanifold characterized by dimensions and semi-Fredholm indices.

A Delta-groupoid is an algebraic structure which axiomitizes the combinatorics of a truncated tetrahedron. It is shown that there are relations of Delta-groupoids to rings, group pairs, and (ideal) triangulations of three-manifolds. In particular, one can associate a Delta-groupoid to ideal triangulations of knot compl…

2009-08-10abs ↗pdf ↗

Paper presents an efficient algorithm for estimating Lipschitz functions from noisy data.

problem Estimating unknown Lipschitz functions from noisy observations.
method Extends max-affine methods to Lipschitz setting using nonlinear feature expansion and adaptive partitioning.
result Achieves minimax convergence rate with respect to intrinsic dimension, up to logarithmic factors.

KrigHedge uses Gaussian processes to approximate option Greeks efficiently.

problem Computing option Greeks in complex models is computationally expensive or inexact.
method Gaussian process surrogates trained on noisy option prices, with analytical differentiation for sensitivities.
result The method provides accurate Delta approximations and quantifies hedging loss.

We refine the analysis of hedging strategies for options under the SABR model carried out in [2]. In particular, we provide a theoretical justification of the empirical observation made in [2] that the modified delta ("Bartlett's delta") introduced there provides a more accurate and robust hedging strategy than the con…

2017-04-11abs ↗pdf ↗

A Delta-groupoid is an algebraic structure which axiomatizes the combinatorics of a truncated tetrahedron. By considering two simplest examples coming from knot theory, we illustrate how can one associate a Delta-groupoid to an ideal triangulation of a three-manifold. We also describe in detail the rings associated wit…

2010-01-18abs ↗pdf ↗

Investors mispricing volatility and jump sensitivity in Delta hedging models still super-replicate the true claim.

problem Investors misestimate volatility and jump sensitivity in Delta hedging models.
method Analyzes the robustness of Delta hedging in jump-diffusion models, proving stochastic flow properties and convexity of value functions.
result An erroneously computed Delta strategy super-replicates the true claim in expectation under a wide class of models.

The paper introduces a measure to assess the relative value of a delta-Symmetric Strangle under the Black-Scholes model.

problem Measuring the relative value of a delta-Symmetric Strangle under the Black-Scholes model.
method Developed a new measure of relative value in terms of delta and volatility, bounded by a simple function of delta.
result The relative value of a delta-Symmetric Strangle is bounded by a simple function of delta and is independent of other factors.

Invariants for surfaces up to rigid transformations, with a comeagre subset retrieval algorithm.

problem Identifying compact surfaces up to rigid transformations.
method Degree four polynomials in moments of delta function, effective inversion algorithm.
result Invariants and retrieval algorithm work on a comeagre subset of surfaces.

Delta method vs Bootstrap for deep learning classification shows strong linear relationship and faster computation.

problem Validating the Delta method for deep learning classification.
method Comparison of Delta method and Bootstrap on LeNet-based neural networks using MNIST and CIFAR-10 datasets.
result The Delta method provides a five times faster computation with strong linear predictive uncertainty relationship.

Delta finite-type invariants are defined analogously to finite-type invariants, using delta moves instead of crossing changes. We show that they are closely related to the lower central series of the commutator subgroup of the pure braid group.

1999-07-12abs ↗pdf ↗

We call a Delta Diagram any diagram of a knot or link whose regions (including the unbounded one) have 3, 4, or 5 sides. We prove that any knot or link admits a delta diagram. We define and estimate combinatorial link invariants stemming from this definition.

2015-12-20abs ↗pdf ↗

The paper classifies pretzel links with 2 components and gives conditions for those with 3 or more.

problem Classifying pretzel links based on their self delta-equivalence.
method Using Conway polynomials to determine self delta-equivalence for links with 2 or more components.
result Necessary and sufficient conditions for self delta-equivalence of pretzel links with 3 or more components.

We study generalizations of finite-type knot invariants obtained by replacing the crossing change in the Vassiliev skein relation by some other local move, analyzing in detail the band-pass and doubled-delta moves. Using braid-theoretic techniques, we show that, for a large class of local moves, generalized Goussarov's…

2005-11-08abs ↗pdf ↗

We study the conformal plate buckling equation (Laplace--Beltrami)^2 u =1, where the L-B operator is for the metric g = e^{2u}g_0, with g0g_0 the standard Euclidean metric on R^2. This conformal elliptic PDE of fourth order is equivalent to the nonlinear system of elliptic PDEs of second order, Delta u +K_g e^(2u)=0, D…

2001-04-18abs ↗pdf ↗

Develops a new method for statistical optimal allocation problems.

problem Statistical optimal allocation problems with constraints.
method Functional differentiability approach and Hadamard differentiability of value functions.
result Validates margin assumption for fast convergence rate of plug-in methods.

This paper uses Malliavin calculus to price and compute delta of financial derivatives in jump-diffusion models.

problem Pricing and delta computation of financial derivatives in jump-diffusion models with stochastic intensity.
method Utilizes Malliavin calculus to price and compute delta, applying the Euler scheme for convergence analysis.
result Established the convergence of approximated solution, financial derivative, and its delta Greeks.

In his famous Princeton Notes, Thurston introduced the so-called gluing equations defining the deformation variety. Later, Kashaev defined a non-commutative ring from H-triangulations of 3-manifolds and observed that for trefoil and figure-eight knot complements the abelianization of this ring is isomorphic to the ring…

2016-05-22abs ↗pdf ↗

We generalize the Manolescu-Owens smooth concordance invariant delta(K) of knots K in the 3-sphere to invariants delta_{p^n}(K) obtained by considering covers of order p^n, with p prime. Our main result shows that for any odd prime p, the direct sum of delta_{p^n} as n ranges through the natural numbers, yields a homom…

2008-09-05abs ↗pdf ↗

New quantization methods improve accuracy of Random Fourier Features.

problem Improving accuracy of Random Fourier Features for machine learning.
method Sigma-Delta and distributed noise-shaping quantization methods for 1-bit and low bit-depth quantization.
result Quantized RFFs allow high accuracy approximation of underlying kernels with polynomial error decay.

A new method simulates implied volatility surfaces for multiple assets.

problem Generating consistent market scenarios for multiple asset implied volatilities.
method Combining functional data analysis and neural SDEs with a penalty for model misspecification.
result Simulated market scenarios are consistent with historical features and lie within the sub-manifold of essentially free static arbitrage.

Partial differential equations with distributional sources---in particular, involving (derivatives of) delta distributions---have become increasingly ubiquitous in numerous areas of physics and applied mathematics. It is often of considerable interest to obtain numerical solutions for such equations, but any singular (…

2018-02-09abs ↗pdf ↗

Improved GEC models use scored data from large pretraining to outperform.

problem Addressing data sparsity in Grammatical Error Correction.
method Derive example-level scores from a smaller, higher-quality dataset and incorporate delta-log-perplexity into training schedules.
result Models trained on scored data achieve state-of-the-art results.

We present a new approach to the optimal portfolio problem for an insider with logarithmic utility. Our method is based on white noise theory, stochastic forward integrals, Hida-Malliavin calculus and the Donsker delta function.

2015-08-26abs ↗pdf ↗