Study the hitting density of Ornstein-Uhlenbeck process, providing semi-analytical solutions.
problem First passage hitting density of Ornstein-Uhlenbeck process.
method Two complementary formulations, heat potentials, linear Volterra integral equations, Abel equation approximation, numerical solutions.
result Semi-analytical solutions for hitting density of Ornstein-Uhlenbeck process.
The paper simulates Lévy processes and their extremum and hitting time.
problem Simulating Lévy processes and their extremum and hitting time accurately and efficiently.
method Using characteristic functions and conditional characteristic functions, with conformal deformations and precalculated values on multi-grids.
result Accurate and fast simulation of Lévy processes and their extremum and hitting time.
Improved track reconstruction using recurrent neural networks.
problem Reconstructing tracks from hits in detectors with many fake hits.
method Combining hit preprocessing and deep neural network in one stage.
result Proposed method is more accurate, faster, and does not require preprocessing.
Predicts which songs will be Billboard hits using Spotify data.
problem Predicting which songs will become chart-topping hits.
method Used a dataset of 1.8 million hit and non-hit songs, extracted audio features, and tested four models (random forest achieved 88% accuracy).
result Random forest model achieved 88% accuracy in predicting Billboard song success.
When estimating high-frequency covariance (quadratic covariation) of two arbitrary assets observed asynchronously, simple assumptions, such as independence, are usually imposed on the relationship between the prices process and the observation times. In this paper, we introduce a general endogenous two-dimensional nonp…
New deep learning methods improve track reconstruction in particle physics.
problem Reconstructing particle tracks from detector hits in GEM detectors.
method Two-stage approach combining hits preprocessing and deep neural networks.
result Deep neural networks can accurately reconstruct tracks without preprocessing.
New model captures fast price excursions in finance.
problem Capturing fast price excursions in financial models.
method Heston model with fast-reversion limit.
result Model shows significant hitting probabilities for barrier options.
Predicting dance hits from 1985-2013 using musical features.
problem Predicting which songs will be dance hits.
method Built a database of dance hit songs with features, used multiple classifiers.
result Best model predicts top 10 dance hits with good accuracy.
HitNet uses a Hit-or-Miss layer to enhance feature interpretability in capsule networks.
problem Difficulty in interpreting complex neural network architectures.
method Replacing the last layer with a Hit-or-Miss layer that trains capsules to hit or miss a target capsule using centripetal loss.
result HitNet achieves better performance than initial CapsNet on various datasets and provides interpretable feature representations.
In this paper we explore an identity in distribution of hitting times of a finite variation process (Yor's process) and a diffusion process (geometric Brownian motion with affine drift), which arise from various applications in financial mathematics. As a result, we provide analytical solutions to the fair charge of va…
Minimal hitting time on origami equals diophantine type for certain slopes.
problem Determining hitting time on origami surfaces.
method Analyzing hitting time and diophantine type on specific origami models.
result For genus 4 origami, hitting time equals diophantine type for certain slopes.
The paper analyzes McKean-Vlasov equations with hitting times, proving global solvability.
problem Analyzing blow-ups in McKean-Vlasov equations involving hitting times.
method Connection to the supercooled Stefan problem, comparison principles, and new transform.
result Proves global solvability for McKean-Vlasov dynamics under certain conditions.
The paper optimizes RV estimation by efficient sampling in time-changed diffusion models.
problem Improving realized variance (RV) estimation in time-changed diffusion models.
method Theoretical analysis and simulations of hitting time and realized business time sampling schemes.
result Realized business time sampling is empirically most efficient for high noise levels.
Derives integral representations for a Lévy process and its extremum, hitting time, with fast evaluation.
problem Efficiently evaluating the joint probability density function of a Lévy process, its supremum, and hitting time.
method Integral representations, Laplace-Fourier transforms, summation by parts, conformal deformation, trapezoid rules, Gaver-Wynn-Rho algorithm.
result Explicit calculations and fast evaluation of the joint cpdf for Lévy processes.
Let (Xt)t≥0 be a continuous-time, time-homogeneous strong Markov process with possible jumps and let τ be its first hitting time of a Borel subset of the state space. Suppose X is sampled at random times and suppose also that X has not hit the Borel set by time t. What is the intensity process of τ ba…
Price limit trading rules are adopted in some stock markets (especially emerging markets) trying to cool off traders' short-term trading mania on individual stocks and increase market efficiency. Under such a microstructure, stocks may hit their up-limits and down-limits from time to time. However, the behaviors of pri…
Adaptive denoising models adjust the number of steps based on noise level.
problem Generating data with lower intrinsic dimensions.
method Adaptive diffusion models using Doob's h-transform to terminate at a random time.
result Adaptive models simplify termination to a first-hitting rule, enhancing adaptability.
New complexity measure MEHC refines MDP upper bounds and rewards informativeness.
problem Refining complexity measures for MDPs and understanding reward informativeness.
method Introducing MEHC, a new complexity measure that tightens MDP diameter by accounting for reward structure.
result MEHC replaces diameter in upper bounds on optimal value span and UCRL2-like algorithms' regret.
Solves financial and non-financial problems using heat potentials.
problem Calibrating default boundaries, calculating default probabilities, and finding hitting time probabilities.
method Classical method of heat potentials, recently extended by the author.
result Successfully solved several financial and non-financial problems.
This paper improves bond market making by adjusting hit-ratios for client flow quality.
problem Economic misleading of raw hit-ratios in corporate bond market making.
method Stochastic-control framework with residual-quality-adjusted hit-ratio.
result Optimal quotes decompose into various components, improving service/economics frontier.
Research in psychology and neuroscience has successfully modeled decision making as a process of noisy evidence accumulation to a decision bound. While there are several variants and implementations of this idea, the majority of these models make use of a noisy accumulation between two absorbing boundaries. A common as…
Study bond market making with hit-ratio target using optimal control and HJB equations.
problem Optimizing bond market making with hit-ratio target in OTC markets.
method Stochastic optimal control approach, dualizing hit-ratio target, HJB equation, Riccati equation, linearization.
result Explicit quote decompositions into riskless spread, inventory-risk correction, and hit-ratio correction.
Directly analyzes SGLD hitting times for stationary points, providing tighter bounds.
problem Analyzing the hitting time of SGLD to stationary points.
method Direct analysis using linear algebra and probability theory, avoiding complex Cheeger's constant bounds.
result Tighter bounds on hitting times compared to previous work, showing dimension-independent behavior under suitable conditions.
Paper analyzes Hit-and-Run's convergence rates and applies similar methods to randomized Kaczmarz.
problem Quantifying advantages of Hit-and-Run's coordinate-free property.
method Sharp estimates via coupling methods and mixing time bounds.
result Ballistic and superdiffusive convergence rates in certain settings.
In this paper, we investigate the cooling-off effect (opposite to the magnet effect) from two aspects. Firstly, from the viewpoint of dynamics, we study the existence of the cooling-off effect by following the dynamical evolution of some financial variables over a period of time before the stock price hits its limit. S…
The hitting measure is singular and has dimension less than 1 for cocompact Fuchsian groups.
problem Analyzing the hitting measure and Hausdorff dimension for cocompact Fuchsian groups.
method Geometric and probabilistic analysis of random walks on cocompact Fuchsian groups.
result The hitting measure is singular with respect to Lebesgue measure and has a Hausdorff dimension strictly less than 1.
Researchers prove hitting measure singularity for most Fuchsian and Kleinian groups.
problem Singularity of hitting measure for random walks on discrete subgroups.
method Algebraic and geometric convergence, hyperbolic Dehn filling.
result Proved singularity conjecture for certain measures on cocompact Fuchsian and Kleinian groups.
Volterra square-root process boundary behavior and martingale measures
problem Boundary behavior of the Volterra square-root process
method Comparison principles for Volterra integral equations and generalized Riemann-Liouville fractional equations
result Finiteness of negative p-moments and atom at the boundary for rough kernels The paper improves competitive and dynamic regret bounds for smoothed online learning.
problem Smoothed online learning with hitting and switching costs.
method Optimization problems to minimize hitting cost, dynamic regret modification of existing algorithms.
result Improved competitive and dynamic regret bounds for various function classes.
KANEL combines models for early hit enrichment in virtual screening.
problem Assessing model accuracy in chemical bioactivity predictions.
method Ensemble workflow using Kolmogorov-Arnold Networks (KANs) and other models.
result Improves early hit enrichment metrics like PPV@N.
Large unweighted directed graphs are commonly used to capture relations between entities. A fundamental problem in the analysis of such networks is to properly define the similarity or dissimilarity between any two vertices. Despite the significance of this problem, statistical characterization of the proposed metrics …
New algorithm tests Markov chains without hitting.
problem Testing Markov chains with unknown transition matrix.
method Combining approximation algorithms and spectral analysis.
result Efficient testing of Markov chains without hitting time dependence.
Equity default-swaps pay the holder a fixed amount of money when the underlying spot level touches a (far-down) barrier during the life of the instrument. While most pricing models give reasonable results when the barrier lies within the range of liquidly traded strikes of plain-vanilla option prices, the situation is …
We empirically investigated the relationships between the degree of efficiency and the predictability in financial time-series data. The Hurst exponent was used as the measurement of the degree of efficiency, and the hit rate calculated from the nearest-neighbor prediction method was used for the prediction of the dire…
We discuss the pricing of defaultable assets in an incomplete information model where the default time is given by a first hitting time of an unobservable process. We show that in a fairly general Markov setting, the indicator function of the default has an absolutely continuous compensator. Given this compensator we t…
We consider a controlled diffusion process (Xt)t≥0 where the controller is allowed to choose the drift μt and the volatility σt from a set $\K(x) \subset \R\times (0,\infty)$ when Xt=x. By choosing the largest σ2μ at every point in time an extremal process is constructed which is under suita…
In this paper we consider finite volume hyperbolic manifolds X with non-empty totally geodesic boundary. We consider the distribution of the times for the geodesic flow to hit the boundary and derive a formula for the moments of the associated random variable in terms of the orthospectrum. We show that the the first tw…
Model financial default cascades on sparse graphs via hitting times.
problem Capturing systemic risk in large, sparsely-connected financial networks.
method Dynamic particle systems with hitting times and convergence theory.
result Characterization of default time distribution in tree-like networks.
This study compares two neural models for financial forecasting, showing their superiority.
problem Improving financial market trend predictions using neural networks.
method Systematic comparison of N-HiTS and N-BEATS with conventional models.
result N-HiTS and N-BEATS enhance forecast accuracy and robustness in financial time series data.
We propose an interacting particle system to model the evolution of a system of banks with mutual exposures. In this model, a bank defaults when its normalized asset value hits a lower threshold, and its default causes instantaneous losses to other banks, possibly triggering a cascade of defaults. The strength of this …
High throughput screening of compounds (chemicals) is an essential part of drug discovery [7], involving thousands to millions of compounds, with the purpose of identifying candidate hits. Most statistical tools, including the industry standard B-score method, work on individual compound plates and do not exploit cross…
We analyze an optimal stopping problem with random maturity under a nonlinear expectation with respect to a weakly compact set of mutually singular probabilities P. The maturity is specified as the hitting time to level 0 of some continuous index process at which the payoff process is even allowed to have…
Holomorphic map connects Hitchin components to character varieties.
problem Complex affine spheres and their properties.
method Mapping class group equivariant holomorphic map from Hitchin components to character varieties.
result Holomorphic map includes holonomies of SL(3,C)-opers.
Paper reconciles different Ricci flow approaches and proves weak solutions.
problem Proving weak solutions for Ricci flows with singularities.
method Introducing a novel hitting estimate for Brownian motion, compensating for lack of lower heat kernel bounds.
result Every noncollapsed limit of Ricci flows and singular Ricci flows are weak solutions.
New algorithm determines dimensions of hit spaces in polynomial algebra.
problem Determining dimensions of quotient spaces in polynomial algebra.
method Linear algebra criterion and algorithmic approach.
result Determines dimensions of QPk for arbitrary k and positive degrees. A model for hit song prediction can be used in the pop music industry to identify emerging trends and potential artists or songs before they are marketed to the public. While most previous work formulates hit song prediction as a regression or classification problem, we present in this paper a convolutional neural netw…
SurvSurf predicts first hitting times for intermittent events without monotonic violations.
problem Predicting first hitting times for intermittent events with monotonicity guarantees.
method Partially monotonic neural network for sequential events, incorporating unobserved events.
result SurvSurf outperforms existing models in MSE and IBS metrics.
RLCache uses reinforcement learning to optimize cache management decisions.
problem Optimizing cache hit rate and storage size in computer systems.
method Designing three reinforcement learning agents for cache manager tasks and two advanced architectures.
result Reinforcement learning agents achieve higher cache hit rates and minimize storage space compared to heuristics.