Overlay framework simplifies exotic derivative pricing.
problem Inconsistent pricing models for exotics.
method Combines path reweighting and conic optimisation.
result Practically model-independent price bands for exotics.
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48 results for “model-independent”
We consider the problem of finding model-independent bounds on the price of an Asian option, when the call prices at the maturity date of the option are known. Our methods differ from most approaches to model-independent pricing in that we consider the problem as a dynamic programming problem, where the controlled proc…
Simple method calculates WWR for regulatory and accounting purposes.
problem Estimating WWR for regulatory and accounting capital requirements.
method Model-independent approach using integral expressions and component calibration.
result WWR effects for FVA are significantly more material than for CVA.
The study analyzes financial markets with transaction costs and proves asset pricing theorems.
problem Model-independent financial markets with proportional transaction costs.
method Develops a Fundamental and Superhedging Theorem, proving equivalence to Consistent Price Systems.
result The superhedging price in the presence of transaction costs matches the frictionless case for a suitable process.
The study examines how including additional call option prices affects model-independent price bounds for exotic derivatives.
problem Improving model-independent price bounds for exotic derivatives using additional call option prices.
method Characterization of market settings that guarantee improved price bounds and exclusion of any improvement.
result The inclusion of additional call option prices can significantly impact model-independent price bounds.
Extends hedging strategies without relying on specific market models.
problem Deriving hedging strategies for markets without traded claims.
method Relates model-independent replication strategies to local martingales with closed-form solutions via PDEs.
result Provides a general framework and applies it to various market scenarios.
In this paper we investigate model-independent bounds for exotic options written on a risky asset. Based on arguments from the theory of Monge-Kantorovich mass-transport we establish a dual version of the problem that has a natural financial interpretation in terms of semi-static hedging. In particular we prove that th…
We consider the pricing and hedging of exotic options in a model-independent set-up using \emph{shortfall risk and quantiles}. We assume that the marginal distributions at certain times are given. This is tantamount to calibrating the model to call options with discrete set of maturities but a continuum of strikes. In …
In a discrete-time market, we study model-independent superhedging, while the semi-static superhedging portfolio consists of {\it three} parts: static positions in liquidly traded vanilla calls, static positions in other tradable, yet possibly less liquid, exotic options, and a dynamic trading strategy in risky assets …
Study examines short-term IVS dynamics using a model-independent approach.
problem Understanding the short-term behavior of implied volatility surface (IVS).
method Model-independent, distribution-based approach imposing cumulant conditions on asset log return distribution.
result Derives a quadratic expansion for implied volatility and asymptotic expressions for ATM skew and curvature.
Paper develops pricing and hedging for insider traders without assuming specific models.
problem Pricing and hedging financial derivatives for an insider trader in a model-independent setting.
method Adapts Skorokhod embedding approach to insider information and time-invariant payoffs.
result Proves duality results and monotonicity principle for geometric properties of optimal models.
Since Hobson's seminal paper [D. Hobson: Robust hedging of the lookback option. In: Finance Stoch. (1998)] the connection between model-independent pricing and the Skorokhod embedding problem has been a driving force in robust finance. We establish a general pricing-hedging duality for financial derivatives which are s…
In this article we discuss the problem of calculating optimal model-independent (robust) bounds for the price of Asian options with discrete and continuous averaging. We will give geometric characterisations of the maximising and the minimising pricing model for certain types of Asian options in discrete and continuous…
VarPro selects features without model dependence, achieving balanced performance.
problem Finding a small set of features with high explanatory power.
method Rule-based variable priority approach, avoiding model-specific methods and artificial data.
result VarPro has a consistent filtering property for noise variables and achieves balanced performance.
The abstract establishes a model-independent relationship for life insurance valuation and validation.
problem Validating best estimate calculation models in traditional life insurance.
method Derives a model-independent relationship and lower bound formula for valuation.
result Validates models for Solvency~II best estimate calculation using publicly available data.
In this note we give a simple, model-independent construction of Chern classes as natural transformations from differential complex K-theory to differential integral cohomology. We verify the expected behaviour of these Chern classes with respect to sums and suspension.
We consider the pricing of American put options in a model-independent setting: that is, we do not assume that asset prices behave according to a given model, but aim to draw conclusions that hold in any model. We incorporate market information by supposing that the prices of European options are known. In this setting…
Overfitting has a limitation: a model-independent generalization gap bound based on Rényi entropystat.ML
New bound limits generalization gap for large models, independent of model complexity.
problem Understanding generalization gap in large-scale machine learning models.
method Established a model-independent upper bound for generalization gap using Rényi entropy.
result Generalization gap can be maintained with arbitrarily large models if data entropy is sufficient.
A variance swap is a derivative with a path-dependent payoff which allows investors to take positions on the future variability of an asset. In the idealised setting of a continuously monitored variance swap written on an asset with continuous paths it is well known that the variance swap payoff can be replicated exact…
Derived skein modulemath.QA
Propose a model-independent axiomatic framework for derived skein theory.
problem Derived skein theory of oriented 3-manifolds with coefficients in a ribbon tensor category.
method Design axioms for the 0th homology and gluing.
result Establishes relationships between derived and ordinary skein theory.
Study uses viscosity solutions to solve control problems involving measure-valued martingales.
problem Stochastic control problems with measure-valued martingale state processes.
method Viscosity solution approach exploiting structural properties of MVM processes.
result Value function is the unique viscosity solution to the HJB equation.
In a model independent discrete time financial market, we discuss the richness of the family of martingale measures in relation to different notions of Arbitrage, generated by a class of significant sets, which we call Arbitrage de la classe . The choice of reflects into the int…
Aggregating multiple types of complex data in stock market prediction: A model-independent frameworkq-fin.CP
Framework predicts stock market using mixed data types.
problem Challenges in predicting stock market with diverse data types.
method Model-independent framework for mixed data types (scalar, compositional, functional).
result Framework effectively predicts stock market opening prices.
Paper develops bounds for pricing Catastrophic Mortality Bonds.
problem Challenging task in valuing Catastrophic Mortality Bonds.
method Expresses bond payoff as an Asian put option and uses comonotonic theory.
result Derives model-independent bounds for bond pricing.
Agent maximizes utility with pathwise constraint on portfolio value.
problem Maximizing utility with a pathwise constraint on portfolio value.
method Max-plus decomposition for supermartingales, Black-Scholes-Merton model.
result Explicit form of optimal terminal wealth and process involved.
Study uses weak transport for non-convex costs in fixed-income markets.
problem Characterizing optimal caplet pricing in fixed-income markets.
method Introduced weak optimal transport for non-convex costs, reduced general costs to convex problems.
result Established robust super-replication results for fixed-income markets.
Robust, or model-independent properties of the variance swap are well-known, and date back to Dupire and Neuberger, who showed that, given the price of co-terminal call options, the price of a variance swap was exactly specified under the assumption that the price process is continuous. In Cox and Wang we showed that a…
We calibrate and test various variants of field theory models of the interest rate with data from eurodollars futures. A model based on a simple psychological factor are seen to provide the best fit to the market. We make a model independent determination of the volatility function of the forward rates from market data…
Dual Attainment in Multi-Period Multi-Asset Martingale Optimal Transport and Its Computationq-fin.MF
We prove dual attainment for multi-asset financial derivatives pricing.
problem Model-independent pricing and hedging of complex financial derivatives.
method Established duality and attained optimizers for multimarginal, multi-asset martingale optimal transport.
result Existence of dual optimizers under mild conditions for arbitrary numbers of assets and time periods.
New method combines simulations and data for anomaly detection.
problem Detecting new particle signals without direct evidence.
method Hybrid approach using reweighting and interpolation.
result Improved background estimation and classification.
Challenge uses unsupervised learning to detect new physics signals at LHC.
problem Detecting new physics signals at the LHC using unsupervised machine learning.
method Developed and evaluated anomaly detection algorithms on a large dataset.
result Benchmark dataset of >1 Billion simulated LHC events for future studies.
Given a heterogeneous time-series sample, the objective is to find points in time (called change points) where the probability distribution generating the data has changed. The data are assumed to have been generated by arbitrary unknown stationary ergodic distributions. No modelling, independence or mixing assumptions…
This paper presents a Bayesian generative model for dependent Cox point processes, alongside an efficient inference scheme which scales as if the point processes were modelled independently. We can handle missing data naturally, infer latent structure, and cope with large numbers of observed processes. A further novel …
Paper compares two hedging strategies for Lévy models.
problem Difference between locally risk-minimizing and delta hedging strategies.
method Model-independent upper estimations and numerical examples for two Lévy models.
result Upper estimations for the difference between strategies.
A model-free version of the fundamental theorem of asset pricing and the super-replication theoremmath.PR
We propose a Fundamental Theorem of Asset Pricing and a Super-Replication Theorem in a model-independent framework. We prove these theorems in the setting of finite, discrete time and a market consisting of a risky asset S as well as options written on this risky asset. As a technical condition, we assume the existence…
Data Twinningstat.ML
Twinning splits data into fast, statistically similar sets.
problem Creating statistically similar data splits for Big Data.
method Twinning is a method based on SPlit for fast, model-independent dataset splitting.
result Twinning is orders of magnitude faster than SPlit.
Study dynamic trading in options to improve price bounds for exotic derivatives.
problem Improving price bounds for exotic derivatives through dynamic option trading.
method Extend semi-static trading strategies to include dynamic option trading, analyze duality results and pricing rules.
result Improved price bounds for exotic derivatives compared to conventional methods.
Paper compares algebraic quantum field theories and factorization algebras on Lorentzian manifolds.
problem Relationship between algebraic quantum field theories and factorization algebras on Lorentzian manifolds.
method Developed functorial constructions under natural hypotheses, including local constancy and descent axioms.
result Equivalence theorem between algebraic quantum field theories and prefactorization algebras.
New method bypasses assumptions for unbiased estimation of complex system interactions.
problem Inferring pair-wise and higher-order interactions from observational data.
method Cross-disciplinary approach using Targeted Learning for unbiased estimation.
result Universal estimator of all-order symmetric interactions without parametric assumptions.
Spread Divergencestat.ML
A new divergence measure for distributions with different supports.
problem Divergence not defined for distributions with different supports.
method Define Spread Divergence on modified distributions and maximize discriminatory power.
result Spread Divergence can be used to train generative models.
Aggregates models from different datasets using shared latent structures.
problem Aggregating models from heterogeneous datasets with shared latent structures.
method Bayesian nonparametrics for identifying correspondences among local model parameterizations.
result Framework successfully aggregates various model types across different applications.
Entropy measures financial drawdowns, volatility, and volatility regimes.
problem Analyzing financial time series with entropy measures.
method Transfer entropy, state space models, entropy of realised volatility.
result Entropy reveals information flows and volatility regimes in financial markets.
We introduce a model-independent approximation for the branching ratio of Hawkes self-exciting point processes. Our estimator requires knowing only the mean and variance of the event count in a sufficiently large time window, statistics that are readily obtained from empirical data. The method we propose greatly simpli…
Recent work of Dupire and Carr and Lee has highlighted the importance of understanding the Skorokhod embedding originally proposed by Root for the model-independent hedging of variance options. Root's work shows that there exists a barrier from which one may define a stopping time which solves the Skorokhod embedding p…
Compressing Green's function using intermediate representation between imaginary-time and real-frequency domainscond-mat.str-el
New method compresses Green's function data efficiently.
problem Efficiently representing complex correlation functions.
method Intermediate representation (IR) of analytical continuation.
result IR yields significantly compact form of correlation functions.
SGD reduces test error by decorrelating updates.
problem Improving generalization error in machine learning models.
method Derive a formula for generalization gap change due to SGD updates, compare to GD, and show decorrelation effect.
result SGD implicitly regularizes generalization error by decorrelating updates.
Deep learning identifies QCD transition properties from particle spectra.
problem Detecting the nature of the QCD transition from heavy-ion collision data.
method Supervised deep learning with a convolutional neural network.
result A neural network acts as an 'EoS-meter' for QCD transition properties.
While defaults are rare events, losses can be substantial even for credit portfolios with a large number of contracts. Therefore, not only a good evaluation of the probability of default is crucial, but also the severity of losses needs to be estimated. The recovery rate is often modeled independently with regard to th…