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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,982 papers · 148 categories

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12.5%25.0%37.5%50.0% · Dec 199319922001200920172026
48 results for frequency doubling

News might trigger jump arrivals in financial time series. The "bad" and "good" news seems to have distinct impact. In the research, a double exponential jump distribution is applied to model downward and upward jumps. Bayesian double exponential jump-diffusion model is proposed. Theorems stated in the paper enable est…

2014-04-08abs ↗pdf ↗

Study confirms complex crypto market dynamics via non-linear potentials.

problem Linear models fail to capture complex financial market dynamics.
method Analyzed high-frequency crypto currency data to confirm non-linear drift and potential functions.
result Markets exhibit either single-well or double-well potentials, indicating varying levels of uncertainty or stress.

Deep neural networks can generalize by reducing high-frequency noise over time, not always following a monotonic learning bias.

problem Understanding the learning dynamics and generalization of over-parameterized DNNs.
method Experimental analysis of deep double descent, focusing on the spectral bias of DNNs.
result The high-frequency components of DNNs diminish over training, leading to a second descent in test error.

Modeling price clustering in financial markets using discrete distributions.

problem Price clustering phenomenon in financial markets.
method Discrete price model based on mixture of double Poisson distributions with dynamic volatility and proportions.
result Higher instantaneous volatility weakens price clustering at ultra-high frequencies.

New method bypasses global fit for LISA's Galactic binaries, extracting population parameters directly.

problem Disentangling LISA's Galactic binary sources from backgrounds in a computationally intensive process.
method Simulation-based approach using normalizing flow to infer population parameters.
result Direct inference of population parameters from LISA's frequency strain series.

Study predicts evolution patterns for pretzel knots, revealing abrupt transitions and hidden non-linearity.

problem Predicting evolution of Khovanov polynomials for pretzel knots.
method Conjectured explicit evolution formulas, revealed abrupt transitions, and identified additional Lyapunov exponents.
result Abrupt transitions and hidden non-linearity in evolution of Khovanov polynomials for thick knots.

The paper develops a neural network method for estimating drift functions of diffusion processes from discrete observations.

problem Nonparametric estimation of drift function for diffusion processes from high-frequency discrete observations.
method Neural network-based estimator for drift function estimation.
result Derives a non-asymptotic convergence rate for the neural network estimator.

In the present work we introduce a novel multi-agent model with the aim to reproduce the dynamics of a double auction market at microscopic time scale through a faithful simulation of the matching mechanics in the limit order book. The agents follow a noise decision making process where their actions are related to a s…

2010-05-03abs ↗pdf ↗

Improved stock trading model using sentiment analysis and machine learning.

problem Enhancing reinforcement learning models for high-frequency stock trading.
method Combining deep Q network with ARBR sentiment indicator, applying PCA and LSTM, incorporating market sentiment.
result Significantly improved performance in stock trading, achieving a maximum annualized rate of return of 54.5%.

RL agent learns to place limit orders for trading signals in financial markets.

problem Training an RL agent to execute trading signals in limit order book markets.
method Deep Duelling Double Q-learning with APEX architecture, using synthetic alpha signals.
result RL agent outperforms heuristic trading strategies in inventory management and order placing.

Let M\mathbb{M} be a compact CC^\infty-smooth Riemannian manifold of dimension nn, n3n\geq 3, and let φλ:ΔMφλ+λφλ=0\varphi_λ: Δ_M \varphi_λ+ λ\varphi_λ= 0 denote the Laplace eigenfunction on M\mathbb{M} corresponding to the eigenvalue λλ. We show that Hn1({φλ=0})Cλα,H^{n-1}(\{ \varphi_λ=0\}) \leq C λ^α, where α>1/2α>1/2 is a constant, whi…

2016-05-09abs ↗pdf ↗

The paper analyzes the joint dynamics of prices and order flow in electronic order books.

problem Understanding the micro-dynamics of asset prices in high-frequency trading environments.
method Double coarse-graining procedure and Principal Component Analysis to extract meaningful information.
result The VAR model captures the stability of liquidity modes and their dynamical evolution.

A Klein surface is a surface with a dianalytic structure. A double of a Klein surface XX is a Klein surface YY such that there is a degree two morphism (of Klein surfaces) YXY\rightarrow X. There are many doubles of a given Klein surface and among them the so-called natural doubles which are: the complex double, the …

2014-04-03abs ↗pdf ↗

We define a general notion of abstract double Lie algebroid. We show (1) that the double Lie algebroid of a double Lie groupoid is a double Lie algebroid in this sense; (2) that the double cotangent constructed from Lie algebroid structures on a vector bundle A and its dual A* is a double Lie algebroid if and only if (…

1998-08-17abs ↗pdf ↗

HyFAD improves time series imputation by combining time and frequency diffusion.

problem Improve time series imputation by handling frequency-sensitive denoising and balancing global and local dynamics.
method HyFAD is a hybrid time-frequency diffusion model with frequency-aware embedding, built on DDPM paradigm.
result HyFAD achieves state-of-the-art performance in time series imputation.

We define double principal bundles (DPBs), for which the frame bundle of a double vector bundle, double Lie groups and double homogeneous spaces are basic examples. It is shown that a double vector bundle can be realized as the associated bundle of its frame bundle. Also dual structures, gauge transformations and conne…

2016-11-02abs ↗pdf ↗

SSMs have a built-in bias towards low-frequency components, which can be adjusted.

problem Frequency bias in SSMs affects their performance on long-range sequences.
method Proposed two mechanisms to tune frequency bias: scaling initialization or applying a Sobolev-norm-based filter.
result Tuning frequency bias improves SSMs' performance on long-range sequence learning tasks.

This paper establishes an equivalence between transitive double Lie algebroids and core diagrams.

problem Understanding and characterizing transitive double Lie algebroids.
method Using core diagrams and equivalence of transitive core diagrams with transitive double Lie groupoids.
result Transitive double Lie algebroids are completely determined by their core diagrams.

We define an abstract notion of double Lie algebroid, which includes as particular cases: (1) the double Lie algebroid of a double Lie groupoid in the sense of the author, such as the iterated tangent bundle of an ordinary manifold, and various iterated tangent/cotangent constructions in symplectic and Poisson geometry…

2000-11-24abs ↗pdf ↗

The paper examines how parabolic frequency behaves under Ricci flow and Ricci-harmonic flow on manifolds.

problem Understanding the behavior of parabolic frequency under Ricci flow and Ricci-harmonic flow.
method Investigates the monotonicity of parabolic frequency for solutions of linear and heat equations with bounded curvatures.
result Establishes monotonicity results for parabolic frequency under specific curvature conditions.

New method constrains CNN filter frequencies to improve robustness.

problem CNN bias towards low frequency components, leading to poor performance in scenario transformations.
method Frequency domain regularization by constraining filter spectra, training valid frequency range end-to-end.
result Demonstrated effectiveness in defending adversarial perturbations, reducing generalization gap, and improving transfer learning.

We develop new algebraic methods refining the Witt group of linking forms and Ranicki's torsion algebraic L-groups into double Witt groups and double L-groups. At each prime ideal of the underlying ring, our double Witt groups capture infinitely many more integral signatures of the linking form than the single Witt gro…

2015-03-24abs ↗pdf ↗

Study uses multi-kernel Hawkes models to analyze high-frequency price dynamics.

problem Understanding responsive speeds of market participants in high-frequency trading.
method Multi-kernel Hawkes models with conditional Hessian analysis for optimization.
result Existence of multi-kernels (UHF, VHF, HF) in high-frequency price dynamics.

Paper extends SI method for detecting CPs in complex systems' frequency domain.

problem Identifying change points in complex systems' frequency domain.
method Extends SI framework to frequency domain using DFT properties and develops valid p-values.
result Reliable detection of genuine CPs with strong statistical guarantees.

A theory of double affine and special double affine bundles, i.e. differential manifolds with two compatible (special) affine bundle structures, is developed as an affine counterpart of the theory of double vector bundles. The motivation and basic examples come from Analytical Mechanics, where double affine bundles hav…

2009-04-14abs ↗pdf ↗

Existence of double bubbles with high constant mean curvatures in Riemannian manifolds.

problem Existence of double bubbles with high constant mean curvatures in Riemannian manifolds.
method Perturbations of geodesic standard double bubbles centered at critical points of the ambient scalar curvature and aligned along eigen-vectors of the ambient Ricci tensor, with general multiplicity results via Lusternik-Schnirelman theory.
result Existence of double bubbles with high constant mean curvatures in Riemannian manifolds.

We show that if K is any knot whose Ozsvath-Szabo concordance invariant tau(K) is positive, the all-positive Whitehead double of any iterated Bing double of K is topologically but not smoothly slice. We also show that the all-positive Whitehead double of any iterated Bing double of the Hopf link (e.g., the all-positive…

2009-12-28abs ↗pdf ↗

Proves monotonicity of parabolic frequency on all manifolds without curvature assumptions.

problem Monotonicity of parabolic frequency on manifolds.
method Analyzes parabolic frequency function on manifolds, proving monotonicity without curvature assumptions.
result Monotonicity of parabolic frequency on all manifolds, no curvature assumption needed.