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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.

168,742 papers · 148 categories

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12.5%25.0%37.5%50.0% · Nov 199319922001200920172026
48 results for digit distributions

New framework explains leading digit patterns without probabilistic assumptions.

problem Explaining leading digit distributions without relying on probabilistic models.
method Shift-invariant functional equation and affine-plus-periodic formulas.
result Unified mathematical foundation for understanding digit distributions.

Benford's law states that in data sets from different phenomena leading digits tend to be distributed logarithmically such that the numbers beginning with smaller digits occur more often than those with larger ones. Particularly, the law is known to hold for different types of financial data. The Illicit Financial Flow…

2012-01-17abs ↗pdf ↗

This paper explores IT governance for CBDC adoption in financial markets.

problem Adopting CBDC requires new IT governance models in financial markets.
method Systematic Literature Review (SLR) of 14 studies on IT resources and governance models.
result Many IT resources and preliminary IT designs for CBDC governance identified.

We introduce blockchains and distributed ledgers and describe their potential applications to money and banking. The analysis compares public and private ledgers and outlines the suitability of various types of ledgers for different purposes. Furthermore, a few historical prototypes of blockchains and distributed ledge…

2017-03-04abs ↗pdf ↗

Digital personas improve survey results for stable attributes but fail for subjective responses.

problem When can digital personas reliably approximate human survey findings?
method Using LISS panel, constructed personas from background variables and survey histories, tested against held-out post-cutoff answers.
result Digital personas improve alignment with human response distributions for stable attributes but fail for subjective responses.

Digital currencies exhibit multifractality due to heavy-tailed returns and temporal correlations.

problem Understanding market inefficiencies and predicting volatility in digital currencies.
method Multifractal cross-correlation analysis (MFCCA) and multifractal detrended fluctuation analysis (MFDFA).
result Temporal correlations are the primary source of multifractality in digital currency markets.

A method models continuous-time glucose distributions in children with diabetes.

problem Capturing subtle temporal changes in glucose distributions.
method Probabilistic framework using Gaussian mixtures and neural ODEs.
result Detects treatment-related improvements in glucose dynamics.

Study develops smart contract framework for procurement under demand variability.

problem Operational and economic implications of smart contract adoption under moderate uncertainty.
method Multi-supplier model with endogenized adoption costs, supplier readiness, and inventory penalties; analytical and numerical results.
result Partial adoption strategies support moderate demand variability, while excessive digital investment reduces profitability.

Paper fine-tunes a simulation-driven estimator to reduce out-of-distribution errors.

problem Out-of-distribution errors in simulation-driven parameter estimators.
method Fine-tuning a Two-Stage estimator to improve accuracy for true parameters outside the sampled range.
result The fine-tuning approach reduces out-of-distribution errors and improves accuracy.

Paper develops security model and pricing for stable digital currency in quantum blockchain network.

problem Securing and pricing stable digital currency in a quantum blockchain network.
method Developed a block-based quantum channel networking technology and a FinTech platform model with dynamic pricing.
result Established a generalized IoB security model using quantum channel networking and QKD.

Study examines Trump's crypto influence on markets, revealing conflicts and vulnerabilities.

problem Presidential power and cryptocurrency markets during Trump's second term.
method Mixed-methods approach combining quantitative and qualitative data.
result Political-linked digital assets became a distinct class with systemic vulnerabilities.

Paper addresses FL over MAC with DP constraints, proposing a novel consensus scheme.

problem Federated learning over a multiple access channel with differential privacy constraints.
method Proposes a novel consensus scheme using digital distributed stochastic gradient descent (D-DSGD) with artificial noise to preserve DP.
result Demonstrates improved convergence rate and DP level for a given MAC capacity.

In this paper, we show how to construct graph theoretical models of n-dimensional continuous objects and manifolds. These models retain topological properties of their continuous counterparts. An LCL collection of n-cells in Euclidean space is introduced and investigated. If an LCL collection of n-cells is a cover of a…

2017-05-02abs ↗pdf ↗

Incorrect fixed point assertions in digital topology are discussed.

problem Incorrect, incorrectly proven, or trivial fixed point assertions in digital topology.
method Continues earlier work on identifying and critiquing bad fixed point assertions.
result Clarifies the nature and extent of incorrect fixed point assertions in digital topology.

In this work, we study the problem of learning a single model for multiple domains. Unlike the conventional machine learning scenario where each domain can have the corresponding model, multiple domains (i.e., applications/users) may share the same machine learning model due to maintenance loads in cloud computing serv…

2018-05-19abs ↗pdf ↗

A new method streamlines digital payment programming using smart contracts.

problem High costs and security challenges in programming smart contracts for digital payments.
method Transforming digital currencies into token streams and using configurable templates to generate specialized smart contracts.
result Reduces payment programming costs and enhances security, self-enforcement, adaptability, and controllability.

Although the popular MNIST dataset [LeCun et al., 1994] is derived from the NIST database [Grother and Hanaoka, 1995], the precise processing steps for this derivation have been lost to time. We propose a reconstruction that is accurate enough to serve as a replacement for the MNIST dataset, with insignificant changes …

2019-05-25abs ↗pdf ↗

The abstract covers various aspects of eBusiness and eGovernment, including digital currencies, m-government services, gender inclusivity, eLearning, export performance, SME digitalization, and banking customer behavior.

problem Various challenges and opportunities in eBusiness and eGovernment.
method Critical review, UTAUT model with perceived risk theory, GAD approach, inductive research paradigm, one-on-one interviews, survey questionnaires, convenience sampling.
result Impediments to eLearning uptake, gender inclusivity in e-procurement, export performance of manufacturing firms, SME digitalization impact, measuring and modeling framework for Internet banking customers.

Two methods using low-discrepancy points improve data compression for neural networks.

problem Efficiently compress large datasets for neural network training.
method Two methods based on low-discrepancy points: digital nets with averaging and clustering.
result Second method outperforms supercompress in compression error and neural network accuracy.