Quantitative Structuring reveals risk sources and performance measures.
problem Model risk in financial products.
method Investment structuring approach to analyze risk.
result Reveals precise risk sources and performance measures.
On-device research index
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.
169,341 papers · 148 categories
Trend · papers per month
48 results for “Quantitative Structuring”
Why Quantitative Structuring?q-fin.GN
Paper introduces Quantitative Structuring for clearer financial product quality.
problem Making financial products as easy to recognize as consumer products.
method Provides an informal introduction to Quantitative Structuring, detailing its applications in product design and beyond.
result Introduces a technology for manufacturing quality financial products.
Improved optimal regularity for harmonic almost complex structures.
problem Establishing optimal regularity for harmonic almost complex structures.
method Quantitative stratification method and rectifiability of singular strata.
result Optimal regularity theory for energy minimizing harmonic almost complex structures.
QGMS framework detects market endpoints using geometric patterns.
problem Identifying market endpoints in large-scale movements.
method Hybrid of geometric pattern recognition and quantitative modeling.
result Consistently identifies market endpoints before major reversals.
The paper establishes conditions for complex structures on manifolds with given vector fields.
problem Conditions for complex structures on manifolds with given vector fields.
method Intrinsic, diffeomorphic invariant conditions for vector fields to have desired regularity.
result Quantitative results for sub-Hermitian geometry and formally integrable elliptic structures.
Study on Riemannian isoperimetric inequality, finding it true generically.
problem Direct analogue of Euclidean isoperimetric inequality is false on Riemannian manifolds.
method Used Lojasiewicz-Simon inequality for real analytic metrics.
result Modified quantitative isoperimetric inequality holds for real analytic metrics.
Mapping chemical performance on molecular structures using locally interpretable explanationsstat.ML
New method explains complex fuel compound classifications.
problem Understanding complex quantitative structure-activity relationship models.
method Locally Interpretable Machine-Agnostic Explanations (LIME) applied to 2-D chemical structures.
result Replicates chemical intuition, allowing direct acceptance/rejection of decisions.
Similarity algebra extends algebraic structures with quantitative bounds.
problem Exact algebraic structures with strict axioms.
method Framework for approximate algebraic and Lie structures with -estimates.
result Similarity structures converge to classical algebraic objects as .
New *K-means method finds cancer signatures without NMF.
problem Identifying cancer signatures from genome data.
method Applying *K-means clustering to 1,389 cancer samples.
result 3 cancers lack cluster-like structures, 2 have high correlations.
Paper shows stability of metric reconstruction for orbifolds from spectral data.
problem Determining the metric structure of collapsing orbifolds from spectral data.
method Improved quantitative unique continuation for wave operator on Riemannian manifolds.
result Quantitative stability of inverse problem for Riemannian orbifolds.
Framework mitigates overfitting in quantitative trading strategies.
problem Overfitting during strategy transition from backtest to live trading.
method Three-stage protocol: IS, WFA, OOS; majority pass, purge gaps, cliff veto, etc.
result Demonstrates how to detect overfitting through performance decay and drawdown behavior.
New method interprets layered neural network communities quantitatively.
problem Limited interpretability of layered neural networks.
method Defining and quantifying the effect of each input/output dimension on communities.
result Reveals the role of each part of a layered neural network.
CNNs generate forecasts for stochastic processes without parameter estimation.
problem Forecasting and simulation of stochastic processes without specific system assumptions.
method Convolutional Neural Networks (CNNs) as generative models.
result Ability to generate forecasts and simulations without identifying or estimating specific system structures or parameters.
AutoAlpha efficiently discovers effective alpha factors for quantitative investment.
problem Mining effective alpha factors for successful quantitative investment models.
method Hierarchical evolutionary algorithm with PCA-QD search, warm start, and replacement methods.
result AutoAlpha discovers and generates effective formulaic alphas for portfolio optimization.
The Quantitative Relations between Stock Prices and Quantities of Tradable Stock Shares and Its Applicationsphysics.soc-ph
This paper analyzes the quantitative relations between stock prices and quantities of tradable stock shares in Chinese stock markets at six time points by means of Exploratory Data Analysis (EDA) method. It is found the resulting formulae have the same structure but different parameters. This paper also uses these rela…
Paper proposes NNAFC for automatic financial factor construction.
problem Manual factor construction is time-consuming and prone to bias.
method NNAFC uses neural networks to automatically construct diversified financial factors.
result NNAFC outperforms GP in constructing more informative and diversified factors.
Super-resolution improves MRI resolution and accuracy for biomarker assessment.
problem Inadequate SNR for accurate quantification in high-resolution MRI.
method Utilized deep learning super-resolution to maintain SNR for T2 relaxation time biomarkers while generating high-resolution images.
result Super-resolution successfully maintains high-resolution and accurate biomarkers for MRI.
Paper proves a quantitative estimate for transforming almost complex structures into standard ones.
problem Transforming almost complex structures into standard ones on bounded domains.
method Proves existence of global diffeomorphisms under Hölder-Zygmund conditions.
result Existence of a global diffeomorphism in a specified Hölder-Zygmund class.
AlphaCFG discovers alpha factors using grammar-guided search.
problem Discovering formulaic alpha factors in finance.
method AlphaCFG uses a grammar-based framework to define and discover alpha factors with syntactic and semantic constraints.
result AlphaCFG outperforms state-of-the-art methods in trading profitability and efficiency.
The stability analysis of socioeconomic systems has been centered on answering whether small perturbations when a system is in a given quantitative state will push the system permanently to a different quantitative state. However, typically the quantitative state of socioeconomic systems is subject to constant change. …
The financial market and turbulence have been broadly compared on account of the same quantitative methods and several common stylized facts they shared. In this paper, the She-Leveque (SL) hierarchy, proposed to explain the anomalous scaling exponents deviated from Kolmogorov monofractal scaling of the velocity fluctu…
FinRL automates trading in quantitative finance with deep reinforcement learning.
problem Steep development curve for traders to automate trading decisions.
method Open-source framework implementing DRL algorithms and reward functions.
result FinRL simplifies strategy design and reduces debugging workloads.
Enhances genetic programming for stock alpha discovery with warm start and structural constraints.
problem Overwhelming search space and computational burden in traditional genetic programming for alpha factor discovery.
method Proposes a new GP framework with warm start and structural constraints to enhance search performance and interpretability.
result Superior out-of-sample prediction results and higher portfolio returns compared to benchmarks.
Theorem generalizes Reifenberg's for measures with bounds on β-numbers.
problem Bounding measures away from k-rectifiable sets with β-numbers.
method Assumptions on Jones' β-numbers to measure closeness to subspaces.
result Effective measure bounds on μ away from a closed k-rectifiable set.
Study extends bounds on sample covariance matrices with general dependence.
problem Quantitative bounds on sample covariance matrices with i.i.d. columns.
method Extends previous work on deterministic equivalent to rectangular random matrices with general dependence structure.
result Proves quantitative bounds involving dimensions and spectral parameter, including closer proximity to real positive semi-line.
In this paper, we give a proof of the quantitative Morse theorem stated by {Y. Yomdin} in \cite{Y1}. The proof is based on the quantitative Sard theorem, the quantitative inverse function theorem and the quantitative Morse lemma.
PS-VAE extracts multi-parameter MRI biomarkers with uncertainty quantification.
problem Uncertainty in inverse problems limits clinical acceptance of quantitative MRI methods.
method Physics-Structured Variational Autoencoder (PS-VAE) integrating physics simulator and self-supervised learning.
result PS-VAE provides full covariance of inter-parameter correlations and accelerates multi-parametric MRI quantification.
The study shows how discrete graphs can resemble hypercube structures under certain curvature conditions.
problem Understanding the structure of graphs with specific curvature conditions.
method Analyzing weighted graphs with lower Ricci curvature bounds and eigenvalue closeness to establish structural similarity.
result Discrete graphs with specific curvature conditions are close to hypercube structures in terms of Frobenius distance and eigenfunctions.
New cyclicity measures defined in weighted Besov spaces, with stability and geometric analysis.
problem Characterizing cyclicity in weighted Besov spaces.
method Defining cyclicity indices based on potential theory and capacity, studying stability under perturbations, and linking zero set structure to cyclicity.
result Novel invariants and conditions for cyclicity in various function spaces.
This study compares various methods for learning Bayesian Network structures.
problem Learning the structure of Bayesian Networks from data is challenging due to the large search space and NP-hard nature of the problem.
method Compared various state-of-the-art methods for structural learning, including different scores and algorithmic approaches.
result Provided a detailed comparison of methods for BNs with discrete and continuous variables, and varying levels of noise.
Qlib aims to integrate AI into quantitative investment.
problem Challenges in applying AI to quantitative investment.
method Design and develop Qlib to accommodate AI-driven workflow.
result Qlib realizes the potential of AI technologies in quantitative investment.
Stable solution found for manifold topology from boundary data.
problem Determining manifold properties from boundary data and eigenvalues.
method Quantitative stability estimates and unique continuation for the wave operator.
result Eigenvalues and boundary values determine a metric space close to the manifold.
ERICA assesses reproducibility in cluster analysis.
problem Lack of a unified framework for evaluating cluster analysis replicability.
method ERICA (iterative clustering assignments) method to quantify replicability.
result Demonstrates ERICA's ability to identify reproducible cluster structure.
The book explores essential stats and psychology for quantitative trading.
problem Developing a quantitative trading system.
method Logical progression through articles on statistics, quantitative trading, and psychology.
result Essential elements for quantitative trading systems.
Learning Markov blanket (MB) structures has proven useful in performing feature selection, learning Bayesian networks (BNs), and discovering causal relationships. We present a formula for efficiently determining the number of MB structures given a target variable and a set of other variables. As expected, the number of…
Understanding cities is central to addressing major global challenges from climate and health to economic resilience. Although increasingly perceived as fundamental socio-economic units, the detailed fabric of urban economic activities is only now accessible to comprehensive analyses with the availability of large data…
Proves quantitative Alexandrov theorem for capillary surfaces.
problem Proving a quantitative version of the Alexandrov theorem for capillary hypersurfaces.
method Quantitative analysis of Montiel-Ros-type argument.
result Generalizes Julin-Niinikoski's result to capillary case.
Morpho-MNIST benchmarks unsupervised learning representations.
problem Lack of suitable benchmarks for evaluating learned representations.
method Extended MNIST dataset with morphometric analysis and proposed perturbations.
result Models can be quantitatively compared and characterised.
This study evaluates clustering algorithms on high-dimensional data.
problem Comparing clustering algorithms on high-dimensional datasets.
method Evaluation of K-means, DBSCAN, and Spectral Clustering using PCA, t-SNE, UMAP, and multiple metrics.
result UMAP preprocessing improves clustering quality across all algorithms, with Spectral Clustering excelling.
Deriving Derivativesq-fin.GN
Quantitative structuring is a rigorous framework for the design of financial products. We show how it incorporates traditional investment ideas while supporting a more accurate expression of clients' views. We touch upon adjacent topics regarding the safety of financial derivatives and the role of pricing models in pro…
The paper develops quantitative estimates for holomorphic sections over bounded domains.
problem Establishing precise inequalities for holomorphic sections over bounded domains.
method Develops Sobolev-type inequalities and applies them to holomorphic sections of Hermitian vector bundles.
result Quantitative Carleman-type estimates for holomorphic sections are derived, improving on previous non-quantitative results.
Proves upper bound on filling radius for manifolds with positive scalar curvature.
problem Bounding the filling radius of manifolds with positive scalar curvature.
method Quantitative operator K-theory and index theory.
result Proves a quantitative upper bound on the filling radius.
Study proves quantitative results for isoperimetric problem outside convex bodies in the plane.
problem Quantitative estimates for the relative isoperimetric problem outside convex bodies in the plane.
method Flow approach and Łojasiewicz estimates to prove quantitative stability for minimizers.
result Explicit constants and optimal exponents/rates for Łojasiewicz estimates and rates of convergence for gradient flow.
Quantifies tightness in 3D contact manifolds using sub-Riemannian metrics.
problem Estimating maximal tight neighbourhoods of Reeb orbits on 3D contact manifolds.
method Sub-Riemannian metrics and geometric constructions.
result Sharp estimates of tightness radius in terms of Schwarzian derivative bounds.
AI enhances quantitative investment for better returns and risk control.
problem Achieving stable returns through AI in quantitative investment.
method Application of AI technology in quantitative investment strategies.
result AI improves investment performance and risk management.
This paper presents quantitative shrinking target results for rotations and interval exchange transformations. To do this a quantitative version of a unique ergodicity criterion of Boshernitzan is established.
Scenario Constraints with Memory: A Finite-State Approach to Quantitative Financial Analysisq-fin.CP
A framework for analyzing financial systems under scenario constraints.
problem Quantifying worst-case and best-case performance in financial systems.
method Quantitative automata-based framework integrating event history automata and weighted finance finite automata.
result Exact calculation of upper and lower payoff bounds with interpretable witness event histories.
TradeExpert uses a mix of LLMs to predict stock movements.
problem Synthesizing insights from diverse financial data sources.
method A mix of four specialized LLMs analyzing different data types, with a General Expert LLM synthesizing the insights.
result TradeExpert outperforms existing benchmarks in stock movement prediction.