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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.

168,695 papers · 148 categories

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9182736 · Mar 202019922001200920172026
48 results for frequency marching

Study uses high-frequency data to predict ruble depreciation during crisis.

problem Predicting ruble depreciation during the Russian invasion of Ukraine.
method Uses intraday high-frequency data (google searches and implied volatility) to model exchange rate fluctuations.
result Implied volatility is more effective than attention in predicting ruble depreciation.

This short note serves as a historical introduction to the Hopf problem: "Does there exist a complex structure on S6S^6?" This unsolved mathematical question was the subject of the Conference "MAM 1 - (Non-)Existence of Complex Structures on S6S^6", which took place at Philipps-Universität Marburg, Germany, between M…

2017-08-03abs ↗pdf ↗

New algorithm recovers 3D molecule structures from noisy data.

problem Recovering 3D molecule structures from noisy, randomly rotated copies.
method Smoothed analysis of orbit recovery over SO(3)SO(3) using frequency marching.
result Quasi-polynomial time algorithm for orbit recovery over SO(3)SO(3).

Topological anomaly scores predict return curves in S&P 500 stocks

problem Detecting anomalies in financial time series
method BallMapper, decoder-conditional VAE, Function-on-Function regression
result Anomaly history carries predictive content for return curves

This paper analyzes how banking risks spread through sentiment and policy shocks.

problem Systemic risk in the U.S. banking system during the 2023 crisis.
method Time-Varying Parameter Vector Autoregression (TVP-VAR) model with 30-day rolling windows.
result Risk spillovers were driven by perceived similarities in bank business models under interest rate pressure.

Improved KAN model explains brain dynamics through edge learning and synaptic strength.

problem Explaining brain dynamics and frequencies in different brain regions.
method ELKAN (Edge Learning KNN) model with edge learning and trimming, inspired by brain science.
result ELKAN model outperforms KAN in explaining brain frequencies and dynamics.

Study examines cryptocurrency behavior during and after the pandemic.

problem Impact of the pandemic on cryptocurrency long-term memory and volatility.
method Used wavelet-based Hurst exponent analysis on eleven important coins.
result Long-term memory of returns mildly affected during pandemic, but volatility suffered temporary impact.

In this paper we review the well-known fact that the only spheres admitting an almost complex structure are S^2 and S^6. The proof described here uses characteristic classes and the Bott periodicity theorem in topological K-theory. This paper originates from the talk "Almost Complex Structures on Spheres" given by the …

2017-07-12abs ↗pdf ↗

Study examines oil and US stock market interactions during coronavirus crisis.

problem Understanding the impact of coronavirus on oil and stock markets.
method Wavelet analysis of daily data from February 18, 2020 to August 15, 2020.
result Oil prices lead US stock prices at 3-5-day cycles during the first and second parts of March and April 2020.

These are lecture notes mainly aimed at graduate students on selected aspects of generalized geometry: in particular generalized complex and Kaehler structures and generalized holomorphic bundles. They are based on lectures given in March 2010 at the Chinese University of Hong Kong.

2010-08-05abs ↗pdf ↗

These are lecture notes on scale calculus and M-polyfolds written for a graduate course at UNICAMP March-June 2018 and an advanced mini-course given during the biannual meeting of Brazilian mathematicians, CBM-32, at IMPA in August 2019.

2019-08-04abs ↗pdf ↗

The study evaluates different probability models for uncertainty visualization using entropy calculations.

problem Choosing the right probability model affects memory use, run time, and accuracy in uncertainty visualization.
method Entropy calculation on ensemble data to compare various probability models (uniform, Gaussian, histogram, quantile).
result Models matching the ensemble data distribution have the lowest entropy, indicating better accuracy.

Study investor sentiment and disagreement on StockTwits during COVID-19.

problem Understanding investor beliefs and sentiment during the pandemic.
method Analysis of social media data (StockTwits) for investor messages.
result Sentiment and disagreement sharply decreased in early March 2020, followed by a reversal.

We review results on and around the almost complex structure on S6S^6, both from a classical and a modern point of view. These notes have been prepared for the Workshop "(Non)-existence of complex structures on S6S^6" (\emph{Erste Marburger Arbeitsgemeinschaft Mathematik -- MAM-1}), held in Marburg in March 2017.

2017-07-26abs ↗pdf ↗

Applying standard techniques from Toeplitz operator theory, we analyze the asymptotics of the Hilbert-Smith norms of the TQFT operators coming from isotopy classes of one dimensional oriented submanifolds on a closed oriented surface. We thereby obtain a Toeplitz operator interpretation and generalization of the asympt…

2006-05-11abs ↗pdf ↗

Suppose SS is a closed orientable surface and S~\tilde{S} is a finite sheeted regular cover of SS. The following question was posed by Julién Marché in Mathoverflow: Do the lifts of simple curves from SS generate H1(S~,Z)H_{1}(\tilde{S},\mathbb{Z})? A family of examples is given for which the answer is "no".

2015-08-19abs ↗pdf ↗

These lecture notes are based on a mini-course given by the author at the sixth KAWA Winter School on March 23-26, 2015 at the Centro De Giorgi of Scuola Normale Superiore in Pisa. They provide an introduction to the study of the Kahler-Ricci flow on compact Kahler manifolds, and a detailed exposition of some recent de…

2015-08-19abs ↗pdf ↗

Two possible definitions of fixed points in the self-similar analysis of time series are considered. One definition is based on the minimal-difference condition and another, on a simple averaging. From studying stock market time series, one may conclude that these two definitions are practically equivalent. A forecast …

1998-03-05abs ↗pdf ↗

Develops discrete geometry for non-constant curvature surfaces.

problem Modeling surfaces of non-constant curvature, especially with non-constant negative curvature.
method Derived and numerically integrated Lelieuvre formulas for C1,1C^{1,1} hyperbolic surfaces. Proposed iterative and fast marching methods for solving implicit equations and computing geodesic distances.
result Explicit construction of immersions is not provided, but equations are described implicitly.

These are the written discussions of the paper "Bayesian measures of model complexity and fit" by D. Spiegelhalter et al. (2002), following the discussions given at the Annual Meeting of the Royal Statistical Society in Newcastle-upon-Tyne on September 3rd, 2013.

2013-10-10abs ↗pdf ↗

Detects potential depegs in Curve's StableSwap pools to protect LPs.

problem Detecting and alerting LPs to potential depegs in Curve's StableSwap pools.
method Constructed metrics based on price and trading data, fine-tuned BOCD algorithm.
result Model detects USDC depeg 5 hours before price dip, with few false alarms.

The predictions of the S&P 500 returns made in 2007 have been tested and the underlying models amended. The period between 2003 and 2008 should be described by the dependence of the S&P 500 stock market index on real GDP because the population pyramid was highly inaccurate. The 2008 trough and 2009 rally are well predi…

2010-03-29abs ↗pdf ↗

Define an arithmetic variety to be the quotient of a bounded symmetric domain by an arithmetic group. An arithmetic variety is algebraic, and the theorem in question states that when one applies an automorphism of the field of complex numbers to the coefficients of an arithmetic variety the resulting variety is again a…

2001-06-23abs ↗pdf ↗

Topological quantum field theories with gauge group SU2\textrm{SU}_2 associate to each surface with marked points ΣΣ and each integer r>0r>0 a vector space Vr(Σ)V_r (Σ) and to each simple closed curve γγ in ΣΣ an Hermitian operator TrγT_r^γ acting on that space. We show that the matrix elements of the operators TrγT_r^γ ha…

2012-06-05abs ↗pdf ↗

This article arose from a series of three lectures given at the Banach Center, Warsaw, during period of 24 March to 13 April, 2003. Morse functions are useful tool in revealing the geometric formation of its domain manifolds MM. They define the handle decompositions of MM from which the additive homologies $H_{\ast}(…

2004-08-02abs ↗pdf ↗

Study analyzes market co-movements in critical mineral investments using change point detection and cross-sectional analysis.

problem Market dynamics in critical mineral investments during significant global events.
method Combines change-point detection (PELT algorithm) with cross-sectional analysis on ESG-ranked ETFs.
result Investors herded during market downturns and shifted to anti-herding after positive news and geopolitical shocks.

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.

Investor expectations shifted pessimistically during the 2020 stock market crash and recovery.

problem Analyzing changes in investor expectations during the 2020 stock market crash and recovery.
method Surveying Vanguard clients at three points: before, during, and after the crash.
result Investor pessimism increased following the crash, with significant disagreement about future outcomes.

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.

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.

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.