Free probability theory (14 resultados)

stapled. Condición: Very Good. Estado de la sobrecubierta: Good. 1st Edition. text copy VG w owner's stamp; w some reader notes and signs of use; Parzen at Stanford; Answers: 1966 reprint, 9 page booklet; very clean, attractive, helpful.

Condición: Good. Former library copy. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Taschenbuch. Condición: Neu. Neuware - Reactive PublishingModern portfolio construction operates in a high-dimensional regime where the number of assets routinely approaches or exceeds the number of observations. Classical covariance estimators break down in this setting, producing unreliable risk forecasts, distorted principal components, and unstable optimization results.This book develops the mathematical and computational framework needed to address these failures. It presents free probability and random matrix theory as practical tools for spectral analysis, covariance estimation, and risk modeling of large portfolios. Readers move from the Marchenko-Pastur law and free convolution to concrete procedures for cleaning empirical spectra, recovering population eigenvalues, and constructing robust risk measures under realistic market conditions.Core topics include: - Spectral methods for high-dimensional covariance matrices- Free deconvolution and eigenvalue cleaning techniques- Bias-corrected estimators for portfolio risk and factor models- Applications to covariance shrinkage, principal component analysis, and stress testing- Numerical implementation considerations for realistic asset universesThe material is self-contained yet rigorous, bridging theoretical results with the requirements of quantitative portfolio management. It is written for researchers, quant developers, and advanced practitioners who need reliable tools when classical multivariate statistics no longer apply.Vincent Bisette provides a focused treatment of free probability and random matrix methods tailored to the specific challenges of large-scale financial risk modeling.…

Hardcover. Condición: As new. Papers from a workshop on random matrices and operator algebra free products held Mar. 1995 at the Fields Institute for Research in Mathematical Sciences. Field Institute Communications 12. vii, 312 p. 26 cm. White hardcover with green print.

Hardcover. Condición: Brand New. 312 pages. 10.50x7.50x1.00 inches. In Stock.

Hardcover. Condición: As New. Estado de la sobrecubierta: Good. 2nd Edition. pre owned, no writing, clean; very famous international and American Probability classics; vol 2 is topical (few have read all chapters); these copies are very handsome, so are the WHITE (chipped, edge worn) free jackets; (jackets are good;) so are the newish navy linen covers, which feature bold GILT on their spines; both 1966; the set is NOT recommended as collectible; both books are tight, clean, sturdy, and newish; there are a few minor flaws and they are minimally distractive (you might not notice them);I ship anywhere you wish; now! V-2 is 1e; ~4-lbs, boxed; (very) fairly priced: the Feller volumes are historic; may increase in price, as a matched set (scarcity); Goettingen Math. …

Hardcover. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

paperback. Condición: New. Paperback. Pub Date: 2001 Pages: 478 Publisher: Higher Education Press used textbook reading traces.

Condición: New. Print on Demand.

PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Paperback. Condición: new. Paperback. Reactive PublishingModern portfolio construction operates in a high-dimensional regime where the number of assets routinely approaches or exceeds the number of observations. Classical covariance estimators break down in this setting, producing unreliable risk forecasts, distorted principal components, and unstable optimization results.This book develops the mathematical and computational framework needed to address these failures. It presents free probability and random matrix theory as practical tools for spectral analysis, covariance estimation, and risk modeling of large portfolios. Readers move from the Marchenko-Pastur law and free convolution to concrete procedures for cleaning empirical spectra, recovering population eigenvalues, and constructing robust risk measures under realistic market conditions.Core topics include: Spectral methods for high-dimensional covariance matricesFree deconvolution and eigenvalue cleaning techniquesBias-corrected estimators for portfolio risk and factor modelsApplications to covariance shrinkage, principal component analysis, and stress testingNumerical implementation considerations for realistic asset universesThe material is self-contained yet rigorous, bridging theoretical results with the requirements of quantitative portfolio management. It is written for researchers, quant developers, and advanced practitioners who need reliable tools when classical multivariate statistics no longer apply.Vincent Bisette provides a focused treatment of free probability and random matrix methods tailored to the specific challenges of large-scale financial risk modeling. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In probability theory and statistics, a random matrix is a matrix-valued random variable. Many important properties of physical systems can be represented mathematically as matrix problems. For example, the thermal conductivity of a lattice can be computed from the dynamical matrix of the particle-particle interactions within the lattice.In the case of disordered physical systems (such as amorphous materials), the corresponding matrices are randomised. Essentially, the physics of these systems can be captured in simplified forms by studying ordered counterparts (such as crystals), and disordered counterparts. In the latter case, the mathematical properties of matrices with elements drawn randomly from statistical distributions (i.e. random matrices) determine the physical properties.…

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Please note that the content of this book primarily consists of articlesavailable from Wikipedia or other free sources online. In the algebraicaxiomatization of probability theory, the primary concept is not that ofprobability of an event, but rather that of a random variable.Probability distributions are determined by assigning an expectation toeach random variable. The measurable space and the probability measurearise from the random variables and expectations by means of well-knownrepresentation theorems of analysis. One of the important features ofthe algebraic approach is that apparently infinite-dimensionalprobability distributions are not harder to formalize thanfinite-dimensional ones.…