Quantitative Methods

Error bound for the asymptotic expansion of the Hartman-Watson integral ArXiv ID: 2504.04992 “View on arXiv” Authors: Unknown Abstract This note gives a bound on the error of the leading term of the $t\to 0$ asymptotic expansion of the Hartman-Watson distribution $θ(r,t)$ in the regime $rt=ρ$ constant. The leading order term has the form $θ(ρ/t,t)=\frac{“1”}{“2πt”}e^{"-\frac{1"}{“t”} (F(ρ)-π^2/2)} G(ρ) (1 + \vartheta(t,ρ))$, where the error term is bounded uniformly over $ρ$ as $|\vartheta(t,ρ)|\leq \frac{“1”}{“70”}t$. ...

Copulas forFinance- A Reading Guide and Some Applications ArXiv ID: ssrn-1032533 “View on arXiv” Authors: Unknown Abstract Copulas are a general tool to construct multivariate distributions and to investigate dependence structure between random variables. However, the concept of cop Keywords: Copulas, Multivariate Distributions, Dependence Structure, Random Variables, Statistical Modeling, Quantitative Methods Complexity vs Empirical Score Math Complexity: 7.5/10 Empirical Rigor: 2.0/10 Quadrant: Lab Rats Why: The paper focuses on theoretical copula constructions and dependence structures with advanced mathematics, but lacks implementation details, backtests, or empirical data. flowchart TD A["Research Goal:<br>Review Copulas for Finance"] --> B["Key Methodology:<br>Literature Review & Analysis"] B --> C["Data/Input:<br>Financial Return Datasets<br>and Models"] C --> D["Computational Process:<br>Model Fitting &<br>Dependence Estimation"] D --> E["Key Outcomes:<br>Capturing Non-Linear Dependence<br>and Risk Assessment"]