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.
Proves quantitative Alexandrov theorem for capillary surfaces.
Quantum neural networks can approximate noisy functions accurately.
AI enhances quantitative investment for better returns and risk control.
Research integrates sentiment analysis with reinforcement learning for better trading strategies.
Study PL bordism theories with quantitative bounds on filling simplices.
We review classical results where the method of the moving planes has been used to prove symmetry properties for overdetermined PDE's boundary value problems (such as Serrin's overdetermined problem) and for rigidity problems in geometric analysis (like Alexandrov soap bubble Theorem), and we give an overview of some r…
We prove a quantitative version of Obata's Theorem involving the shape of functions with null mean value when compared with the cosine of distance functions from single points. The deficit between the diameters of the manifold and of the corresponding sphere is bounded likewise. These results are obtained in the genera…
This research develops a dynamic risk management system for industrial companies.
Alpha-GPT 2.0 integrates human insights into AI-driven investment research.
Teaching tool simplifies Monte Carlo simulation for project risk analysis.
This paper introduces a new task to better understand Transformers in quantitative contexts.
"What are the origins of risks?" and "How material are they?" -- these are the two most fundamental questions of any risk analysis. Quantitative Structuring -- a technology for building financial products -- provides economically meaningful answers for both of these questions. It does so by considering risk as an inves…
Quantitative model predicts Sri Lankan stock market using NLP, clustering, and time-series forecasting.
Quantformer uses transformer to predict stock returns, outperforming traditional strategies.
On a Riemannian manifold with a positive lower bound on the Ricci tensor, the distance of isoperimetric sets from geodesic balls is quantitatively controlled in terms of the gap between the isoperimetric profile of the manifold and that of a round sphere of suitable radius. The deficit between the diameters of the mani…
We give emphasis on the use of chaos-based rigorous nonlinear technique called Visibility Graph Analysis, to study one economic time series - gold price of USA. This method can offer reliable results with fiinite data. This paper reports the result of such an analysis on the times series depicting the fluctuation of go…
Paper analyzes arbitrage in uncertain markets, providing quantitative asset pricing.
Stock price prediction is a challenging task, but machine learning methods have recently been used successfully for this purpose. In this paper, we extract over 270 hand-crafted features (factors) inspired by technical and quantitative analysis and tested their validity on short-term mid-price movement prediction. We f…
Study shows convergence for mean curvature flow on almost minimal totally real submanifolds.
Sig-SDE model integrates signatures with SDEs for financial data.
Despite its empirical success and recent theoretical progress, there generally lacks a quantitative analysis of the effect of batch normalization (BN) on the convergence and stability of gradient descent. In this paper, we provide such an analysis on the simple problem of ordinary least squares (OLS). Since precise dyn…
Quantitative analysis of order-splitting behavior in Japanese stock market.
Quantifies nearly spherical subsets in complex ball geometry.
EKH adds metrics to knot theory, enabling more detailed analysis.
Factor Engine simplifies financial factor computation and analysis in Python.
Quantitative analysis of soccer players' passing ability focuses on descriptive statistics without considering the players' real contribution to the passing and ball possession strategy of their team. Which player is able to help the build-up of an attack, or to maintain the possession of the ball? We introduce a novel…
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…
QRAFTI uses multi-agent framework to improve equity factor research.
ERICA assesses reproducibility in cluster analysis.
A quantitative analysis of the basic components of the daily DJIA. The parameters of the underlying Lorentzian states are obtained by fitting the data. Statistical properties of the states are discussed. This is a practical development of the general method introduced in arXiv:1203.6021.
ERICA assesses replicability of cluster analysis results.
Improved earnings predictions through text-morphed earnings calls.
New cyclicity measures defined in weighted Besov spaces, with stability and geometric analysis.
The paper uses clustering and integer programming to optimize stock selection for investment funds.
The variability of the clusters generated by clustering techniques in the domain of latitude and longitude variables of fatal crash data are significantly unpredictable. This unpredictability, caused by the randomness of fatal crash incidents, reduces the accuracy of crash frequency (i.e., counts of fatal crashes per c…
We study the asymptotic behavior of the difference between the values at risk VaR(L) and VaR(L+S) for heavy tailed random variables L and S for application in sensitivity analysis of quantitative operational risk management within the framework of the advanced measurement approach of Basel II (and III). Here L describe…
Sharp inequalities and symmetries on Riemannian surfaces quantified.
In this work, a heuristic as operational tool to estimate the lactate threshold and to facilitate its integration into the training process of recreational runners is proposed. To do so, we formalize the principles for the lactate threshold estimation from empirical data and an iterative methodology that enables experi…
Quantitative CT predicts ILD patterns and prognosis.
Paper proposes a new approach to GDPR compliance using data protection analytics.
We establish blow-up profiles for any blowing-up sequence of solutions of general conformally invariant fully nonlinear elliptic equations on Euclidean domains. We prove that (i) the distance between blow-up points is bounded from below by a universal positive number, (ii) the solutions are very close to a single stand…
QGMS framework detects market endpoints using geometric patterns.
On a periodic basis, publicly traded companies are required to report fundamentals: financial data such as revenue, operating income, debt, among others. These data points provide some insight into the financial health of a company. Academic research has identified some factors, i.e. computed features of the reported d…
PDA method optimizes neural networks with global convergence rate analysis.
The purpose of this research paper it is to present a new approach in the framework of a biased roulette wheel. It is used the approach of a quantitative trading strategy, commonly used in quantitative finance, in order to assess the profitability of the strategy in the short term. The tools of backtesting and walk-for…
Proves a quantitative index theorem for positive scalar curvature metrics.
We combine Riemannian geometry with the mean field theory of high dimensional chaos to study the nature of signal propagation in generic, deep neural networks with random weights. Our results reveal an order-to-chaos expressivity phase transition, with networks in the chaotic phase computing nonlinear functions whose g…
Revealing latent structure in data is an active field of research, having introduced exciting technologies such as variational autoencoders and adversarial networks, and is essential to push machine learning towards unsupervised knowledge discovery. However, a major challenge is the lack of suitable benchmarks for an o…