Improved algorithm tags B meson flavours in collider experiments.
problem Tagging neutral B mesons' flavours in collider environments. method Probabilistic model combining vertex and track info with machine learning.
result Increases overall performance in flavour tagging.
Compactification of AdS5 allows studying meson behavior in QCD.
problem Understanding meson behavior in Quantum Chromodynamics (QCD).
method Deforming AdS5 metric to model Coulomb interaction between charges.
result Proposed conformal deformation provides a quantum mechanical description of mesons.
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.
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.
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.
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…
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…
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.
This paper considers aspects of 4-manifold topology from the point of view of the null cone of a neutral metric, a point of view we call neutral causal topology. In particular, we construct and investigate neutral 4-manifolds with null boundaries that arise from canonical 3- and 4-dimensional settings. A null hypersurf…
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 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 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.
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…
Study extends wealth tax neutrality framework to heterogeneous investors.
problem Analyzing wealth tax neutrality in populations with varying return-generating ability.
method Extended Fokker-Planck framework to heterogeneous investors, deriving extended Fokker-Planck equation.
result Proportional wealth tax no longer neutral due to varying return-generating ability, leading to different real incidence and wealth distribution changes.
Investment strategy for NYSE stocks minimizes market correlation.
problem Minimizing market correlation for steady returns.
method Combining momentum, fundamentals, and analyst recommendations; feature selection; backtesting various portfolio construction methods.
result Risk parity outperformed other methods, offering higher Sharpe ratio and lower beta.
The paper embeds CR manifolds into twistor spaces and constructs neutral hyperkähler metrics.
problem Embedding CR manifolds into twistor spaces and constructing neutral hyperkähler metrics.
method Embedding a real analytic twistor CR manifold into the twistor space of a Poincaré-Einstein metric, constructing the associated Fefferman ambient metric as a neutral hyperkähler metric.
result The construction of neutral hyperkähler metrics associated with twistor CR manifolds.
We give the classification of constant mean curvature rotational surfaces of elliptic, hyperbolic, and parabolic type in the four-dimensional pseudo-Euclidean space with neutral metric.
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.
Enhances EEG signal classification using non-Gaussian neutral vectors.
problem Challenges in classifying EEG signals for brain-computer interfaces.
method Transformed mDWT coefficients into neutral vectors, applied feature selection.
result Feature selection improves classification accuracy.
Proposes a method to construct risk-neutral marginals from arbitrage-free option prices.
problem Lack of risk-neutral marginals that are free of arbitrage and easy to use.
method Explicit construction of risk-neutral marginals from discrete arbitrage-free option prices.
result Explicit construction guarantees risk-neutral marginals free of butterfly and calendar arbitrage.
We establish a connection between capillary floating in neutral equilibrium and the billiard ball problem. This allows us to reduce the question of floating in neutral equilibrium at any orientation with a prescribed contact angle for infinite homogeneous cylinders to a question about billiard caustics for their orthog…
Study of pure spinors on neutral manifolds with applications to supersymmetric solutions.
problem Characterizing pure spinors and their properties on neutral manifolds.
method Using the theory of real spinorial forms and differential systems, the square of pure spinors is analyzed.
result Non-pure spinors correspond to specific structures in signature (4,4), and parallel spinors are characterized by differential systems.
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.
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.
Geometric QCD framework establishes stable vacuum for quark confinement.
problem Quark confinement in QCD.
method Geometric construction of stable vacuum using Hodge-dual surfaces.
result Existence and stability of the Hodge-dual surface in 4D ensures quark confinement.
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.
Study classifies gradient almost Ricci solitons in Lorentzian and neutral signatures.
problem Classifying gradient almost Ricci solitons in different signatures.
method Proved local isometry and constructed examples.
result Found that gradient almost Ricci solitons are locally isometric to specific types of manifolds.
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.
Three types of Einstein metrics are disqualified as potential local maxima.
problem Identifying local maxima of the Hilbert action in Einstein metrics.
method Analysis of three infinite families of neutrally stable homogeneous Einstein metrics.
result Three families of Einstein metrics ruled out as local maxima.