1.

Record Nr.

UNISA990006070320203316

Autore

Chiesa cattolica

Titolo

Horae diurnae breviarii Romani ex decreto sacrosancti Concilii Tridentini restituti, s. Pii V pontificis maximi jussu editi. Clementis VIII ac Urbani VIII Auctoritate recogniti, cum officiis sanctorum ex indulto apostolico novissime emanatis

Pubbl/distr/stampa

Venetiis : Apud Nicolaum Pezzana, 1739

Descrizione fisica

[32], 550, CLXIX, [10] p., 1 carta di tav. : ill. ; 12°

Collocazione

XV.7. 232

Lingua di pubblicazione

Latino

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Vignetta calcografica sul frontespizio

Testo stampato in rosso e nero



2.

Record Nr.

UNISA996418279803316

Autore

De Luca Giovanni

Titolo

Statistical Analysis of Operational Risk Data [[electronic resource] /] / by Giovanni De Luca, Danilo Carità, Francesco Martinelli

Pubbl/distr/stampa

Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020

ISBN

3-030-42580-0

Edizione

[1st ed. 2020.]

Descrizione fisica

1 online resource (IX, 84 p. 68 illus., 44 illus. in color.)

Collana

SpringerBriefs in Statistics, , 2191-544X

Disciplina

519.5

Soggetti

Statistics 

Risk management

Economic theory

Bank marketing

Applied mathematics

Engineering mathematics

Statistics for Business, Management, Economics, Finance, Insurance

Risk Management

Economic Theory/Quantitative Economics/Mathematical Methods

Financial Services

Applications of Mathematics

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

1 The Operational Risk -- 2 Identification of the Risk Classes -- 3 Severity Analysis -- 4 Frequency Analysis -- 5 Convolution and Risk Class Aggregation -- 6 Conclusions.

Sommario/riassunto

This concise book for practitioners presents the statistical analysis of operational risk, which is considered the most relevant source of bank risk, after market and credit risk. The book shows that a careful statistical analysis can improve the results of the popular loss distribution approach. The authors identify the risk classes by applying a pooling rule based on statistical tests of goodness-of-fit, use the theory of the mixture of distributions to analyze the loss severities, and apply copula functions for risk class aggregation. Lastly, they assess



operational risk data in order to estimate the so-called capital-at-risk that represents the minimum capital requirement that a bank has to hold. The book is primarily intended for quantitative analysts and risk managers, but also appeals to graduate students and researchers interested in bank risks.