Paper introduces benchmark-neutral pricing for long-term contracts.
problem High prices of long-term contracts under risk-neutral pricing.
method Uses growth optimal portfolio as numeraire and new pricing measure.
result Identifies minimal possible prices for contingent claims.
Generative model uses DDPMs for risk-neutral derivative pricing.
problem Derivative pricing using arbitrage-free models.
method Developed a framework using DDPMs to generate risk-neutral asset price dynamics.
result Empirically validated the method for both European and path-dependent derivatives.
A new beta model reduces bias in market neutral strategies.
problem Bias in beta estimation for market neutral strategies.
method Derive a metric of correlation with leverage effect to identify market beta and volatility changes.
result Empirical test confirms the reactive beta model's ability to reduce bias.
Generative model prices options and extracts risk-neutral densities.
problem Price options and extract risk-neutral densities from market data.
method Model log-returns as a generative model, using neural nets for location, scale, and higher-order moments, with stringent conditions to avoid arbitrage.
result The model efficiently generates samples to price options and accommodates diverse risk-neutral densities.
The paper explores neutral 4-manifolds with null boundaries using causal topology.
problem Neutral 4-manifolds with null boundaries and their topological properties.
method Neutral causal topology, foliation of null hypersurfaces, and geometric constructions.
result Neutral 4-manifolds with null boundaries and their topological properties.
Characterizes neutral deformation modes of minimal surfaces.
problem Understanding the energy content of deformation modes of minimal surfaces.
method Analyzes the energy content of stretching, drilling, and bending modes of minimal surfaces.
result All isometries of a minimal surface are globally neutral and give rise to soft elasticity.
Examines GARCH intensity model for risk-neutral option pricing.
problem Volatility clustering, leverage effect, and conditional asymmetry in financial returns.
method Risk-neutral option pricing method under GARCH intensity model.
result Flexibility in volatility changes according to probability measure.
Paper proposes GN-GloVe to learn gender-neutral word embeddings.
problem Inherit strong gender stereotypes in embeddings trained on human-generated corpora.
method Proposes a novel training procedure to isolate gender information in word vectors.
result GN-GloVe successfully isolates gender information without sacrificing functionality.
The paper studies nilpotent structures in oriented neutral vector bundles and neutral hyperKähler structures.
problem Nilpotent structures in oriented neutral vector bundles and their relation to neutral hyperKähler structures.
method Defined H-nilpotent structures for Lie subgroups of SO(2n,2n) related to neutral hyperKähler structures. result Existence of complex and paracomplex structures forming neutral hyperKähler structures if and only if there exists an H-nilpotent structure. Study finds all 4D neutral manifolds.
problem Classifying neutral manifolds in four dimensions.
method Examined homogeneous semi-symmetric neutral manifolds.
result Identified all four-dimensional neutral manifolds.
Paper calculates Greeks and risk-neutral density for CEV model options.
problem Calculating Greeks and risk-neutral density for CEV model options.
method Asymptotic analysis under CEV model.
result Formulae for Greeks and risk-neutral density.
Study finds cryptocurrency market diversity patterns inconsistent with neutral models.
problem Cryptocurrency market diversity patterns not consistent with neutral models.
method Analysis borrowing methods from ecology, focusing on diversity patterns and community structure.
result Cryptocurrency market diversity patterns not consistent with neutral models, suggesting strong interactions between species.
The purpose of this article is to review some recent results on the geometry of neutral signature metrics in dimension four and their twistor spaces. The following topics are considered: Neutral Kähler and hyperkähler surfaces, Walker metrics, Neutral anti-self-dual 4-manifolds and projective structures, Twistor spaces…
The paper shows that benchmark-neutral pricing minimizes option prices.
problem Pricing extreme-maturity European put options on diversified indices.
method Benchmark-neutral pricing applied to a drifted time-transformed squared Bessel process.
result Benchmark-neutral price is the minimal possible price, risk-neutral price is more expensive.
AlphaZeroBeta uses deep reinforcement learning for market-neutral portfolios, outperforming traditional methods.
problem Traditional portfolio management methods often fail during market regime shifts or when assumptions break down.
method Combines a composite reward function and CNN-GRU policy trained end-to-end via Recurrent PPO.
result Achieves higher Sharpe ratios than baselines while maintaining near-zero benchmark correlations.
Currently, machine learning plays an important role in the lives and individual activities of numerous people. Accordingly, it has become necessary to design machine learning algorithms to ensure that discrimination, biased views, or unfair treatment do not result from decision making or predictions made via machine le…
Paper studies pricing and hedging of nonreplicable insurance contracts using benchmark-neutral approach.
problem Pricing and hedging of long-term insurance contracts like variable annuities.
method Benchmark-neutral pricing framework using stock growth optimal portfolio as numéraire.
result Prices can be significantly lower than risk-neutral ones, offering attractive long-term risk-management.
The paper develops a model using risk-neutral pricing for financial decision-making.
problem Developing a representative agent model for financial decision-making.
method The approach involves using a pricing kernel that is transition independent, solving the eigenpair problem of a second-order differential operator, and finding a one-parameter family of eigenpairs.
result The paper finds a representative agent model derived from the eigenpairs, providing a necessary and sufficient condition for their existence.
Deep Hedging learns risk-neutral vol dynamics for option pricing.
problem Statistical arbitrage in market dynamics without transaction costs.
method Numerical approach to train market simulator and find risk-neutral density.
result Risk-neutral model for stochastic implied volatility can be used for pricing or Deep Hedging.
Optimizes risk-neutral probabilities for derivative pricing.
problem Deriving bounds on derivative values under multiple risk-neutral scenarios.
method Convex optimization over the set of risk-neutral probability distributions.
result Tractable finite-dimensional optimization problems for pricing.
Derivative pricing in risk-neutral equilibrium with uncertain volatilities.
problem Deriving prices for derivatives when agents have different beliefs about underlying dynamics.
method Existence proof of unique equilibrium price incorporating speculative resale value.
result Equilibrium price operator reflects strong aversion to model uncertainty.
The paper shows how to calculate risk-neutral default probabilities from bid and ask CDS quotes.
problem Calculating risk-neutral default probabilities from market quotes.
method Using conic finance framework and Poisson process to formulate and solve the calibration problem.
result A unique solution for risk-neutral default probabilities and implied liquidity.
Optimizes market-neutral portfolios using fractal models.
problem Improving stability and performance of market-neutral portfolios.
method Fractal walk model of returns, covariance matrix optimization, Hurst stability analysis.
result Portfolio system outperforms benchmark with higher risk-adjusted returns.
Simulates risk-neutral markets using neural spline flows.
problem Creating realistic risk-neutral market simulations.
method Developed a low-dimensional martingale representation and used neural spline flows for sampling.
result The calibrated simulator is closest to historical data with respect to Kullback-Leibler divergence.
Develops a binary tree model for option pricing with skew dynamics.
problem Option pricing in incomplete markets with skew dynamics.
method Binary tree model with skew Brownian motion dynamics.
result Model preserves skewness under both discrete and continuous time limits.
The paper bounds payoffs and option prices in discrete models.
problem Measuring risk in discrete models and incomplete markets.
method Analytical and simulated bounds for payoff functions and option prices.
result Analytical and simulated bounds for European and American options.
Develops a valuation model for in-play football bets.
problem Valuation and hedging of in-play football bets.
method Model scores using independent Poisson processes, applies Fundamental Theorems of Asset Pricing.
result Derives arbitrage-free valuation formulas for in-play bets.
Paper compares two annuity pricing models and finds insurer underestimates value.
problem Pricing variable annuities with guaranteed benefits.
method Examines classical risk-neutral and benchmark approaches.
result Insurer underestimates contract value under dynamic withdrawal strategy.
Novel methods transform correlated neutral vectors into independent variables.
problem Decorrelating correlated neutral vector variables that are not multivariate Gaussian distributed.
method Serial and parallel nonlinear transformations to achieve mutual independence.
result Highly negatively correlated neutral vectors can be transformed into mutually independent scalar variables.
This study compares financial density forecasts using risk-neutral and historical schemes.
problem Comparing the forecasting ability of risk-neutral and historical financial density models.
method Comprehensive comparison of 15 predictive schemes over 21 years, evaluating statistical consistency, local accuracy, and forecasting errors.
result Risk-neutral densities outperform historical-based predictions in terms of information content.
The aim of this paper is to give examples of compact neutral 4-manifolds (M,g) whose Ricci tensor ρ satisfies the relation ∇Xρ(X,X)=31Xτg(X,X). We present also a family of new Einstein bi-Hermitian neutral metrics on ruled surfaces of genus g>1.
Project estimates risk-neutral dependence from option prices.
problem Extracting risk-neutral dependence from option prices.
method Projection estimator using portfolios of observed options.
result Estimates risk-neutral dependence in incomplete markets.
New method estimates risk-neutral density for asset prices, improving on existing techniques.
problem Estimating risk-neutral density for asset prices accurately.
method Developed a nonparametric approach reformulated as a double-constrained optimization problem.
result Our approach outperforms existing methods in estimating risk-neutral density.
Investigates real-world interest rate dynamics using affine models.
problem Existence of affine realizations for Lévy-driven interest rate models.
method Transfers results from risk-neutral to real-world probability measure.
result Severe restrictions on market price of risk in infinite activity jump models.
Classifies surfaces with constant mean curvature in a specific type of space.
problem Classifying surfaces with constant mean curvature in a specific type of space.
method Classification based on the type of curvature (elliptic, hyperbolic, parabolic) and the rotational nature of the surfaces.
result Classification of constant mean curvature rotational surfaces.
Minimal surfaces can be transformed into others with unchanged bending content.
problem Understanding the deformation properties of minimal surfaces.
method Refined polar decomposition theorem to identify bending-neutral deformations.
result Every minimal surface can be transformed into another by a bending-neutral deformation.
Quantum Portfolios of quantum algorithms encoded on qbits have recently been reported. In this paper a discussion of the continuous variables version of quantum portfolios is presented. A risk neutral valuation model for options dependent on the measured values of the observables, analogous to the traditional Black-Sch…
Extends wealth tax neutrality framework to stochastic volatility and non-homothetic preferences.
problem Ensuring wealth taxes are neutral under various economic conditions.
method Extended Frøseth's neutrality framework to stochastic volatility and non-homothetic preferences, identified four channels of non-neutrality, and applied the framework to global minimum wealth taxes.
result Non-uniform assessment, general equilibrium effects, progressive thresholds, and endogenous labour supply can cause non-neutrality under CRRA preferences.
We reformulate wealth taxation using Fokker-Planck equations to ensure tax neutrality.
problem Ensuring tax neutrality in wealth taxation frameworks.
method Reformulating the neutral wealth tax framework using stochastic dynamics and statistical physics, specifically Fokker-Planck equations.
result The framework clarifies when wealth taxation is a benign rescaling of dynamics and when it introduces new physics.
Market-neutral pairs-trading strategies are justified by optimal control theory.
problem Investment strategies in cointegrated stocks with CRRA utility.
method Extended optimal control problem with verification result.
result Sharp well-posedness condition for market-neutral pairs-trading.
Study minimal surfaces in product spaces with neutral metrics.
problem Characterize minimal surfaces in product spaces with neutral metrics.
method Compute totally geodesic surfaces and relate to Gordon equations; classify compact minimal surfaces.
result Provide a topological classification of compact minimal surfaces.
Study Asian option pricing in NIG and VG Levy markets.
problem Value of Asian options in incomplete Levy markets.
method Two methods of constructing risk-neutral measures.
result Both methods generally produce similar prices.
Study on surfaces in pseudo-Euclidean space with neutral metric.
problem Characterizing surfaces in pseudo-Euclidean 4-space with neutral metrics.
method Defined and studied Lorentz general rotational surfaces with specific properties.
result Complete classification of various types of general rotational surfaces.
Developed Merton's model for public companies using observed liabilities.
problem Estimating default risk for public companies.
method Campbell and Shiller's approximation method for risk-neutral values and default probabilities.
result Formulas and ML estimators for public companies' default probabilities.
Study stability of pseudo-Kähler and neutral Calabi-Yau manifolds, finding stability in 2D but failing in higher dimensions.
problem Stability of compact pseudo-Kähler and neutral Calabi-Yau manifolds.
method Analysis of stability through deformation theory and construction of counterexamples.
result Stability of compact pseudo-Kähler surfaces but failure in higher dimensions.
New technique reduces bias in DNN models without sensitive attribute annotations.
problem Existing bias mitigation methods require instance-level annotations and do not guarantee removal of all sensitive information.
method Representation Neutralization for Fairness (RNF) debiases only the classification head of DNN models using neutralized representations.
result RNF effectively reduces discrimination of DNN models with minimal performance degradation.
It is shown that if a compact four-dimensional manifold with metric of neutral signature is Jordan-Osserman, then it is either of constant sectional curvature or Ricci flat.
Notation for spin coefficients for metrics of neutral signature in four dimensions is introduced. The utility and interpretation of spin coefficients is explored through themes in null geometry familiar from (complex) general relativity. Four-dimensional Walker geometry is exploited to provide examples and the generali…