Statistics and Data Analysis for Financial Engineering

DOI10.1007/978-1-4939-2614-5zbMath1310.62002OpenAlexW4294576893MaRDI QIDQ5249571

David S. Matteson, David Ruppert

Publication date: 6 May 2015

Published in: Springer Texts in Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-1-4939-2614-5

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70) Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics (62-01) Mathematics for nonmathematicians (engineering, social sciences, etc.) (00A06) Introductory exposition (textbooks, tutorial papers, etc.) pertaining to game theory, economics, and finance (91-01) Actuarial science and mathematical finance (91Gxx)

Related Items (10)

Quantifying the data-dredging bias in structural break tests ⋮ Local influence diagnostics for the test of mean-variance efficiency and systematic risks in the capital asset pricing model ⋮ Copula-Based Functional Bayes Classification With Principal Components and Partial Least Squares ⋮ Rates of Bootstrap Approximation for Eigenvalues in High-Dimensional PCA ⋮ On fair designs of c<scp>ross‐chain</scp> exchange for cryptocurrencies via Monte Carlo simulation ⋮ Pretest and shrinkage estimators for log-normal means ⋮ Learning discontinuous piecewise affine fitting functions using mixed integer programming over lattice ⋮ Simulation of multidimensional diffusions with sticky boundaries via Markov chain approximation ⋮ Some properties of portfolios constructed from principal components of asset returns ⋮ Constructing an optimal portfolio on the Bulgarian stock market using hybrid genetic algorithm for pre- and post-COVID-19 periods

Uses Software

• Unnamed Item

This page was built for publication: Statistics and Data Analysis for Financial Engineering