Statistical Inference in Financial and Insurance Mathematics with R

Finance and insurance companies are facing a wide range of parametric statistical problems. Statistical experiments generated by a sample of independent and identically distributed random variables are frequent and well understood, especially those consisting of probability measures of an exponential type. However, the aforementioned applications also offer non-classical experiments implying observation samples of independent but not identically distributed random variables or even dependent random variables. Three examples of such experiments are treated in this book. First, the Generalized Linear Models are studied. They extend the standard regression model to non-Gaussian distributions. Statistical experiments with Markov chains are considered next. Finally, various statistical experiments generated by fractional Gaussian noise are also described. In this book, asymptotic properties of several sequences of estimators are detailed. The notion of asymptotical efficiency is discussed for the different statistical experiments considered in order to give the proper sense of estimation risk. Eighty examples and computations with R software are given throughout the text. Examines a range of statistical inference methods in the context of finance and insurance applications Presents the LAN (local asymptotic normality) property of likelihoods Combines the proofs of LAN property for different statistical experiments that appears in financial and insurance mathematics Provides the proper description of such statistical experiments and invites readers to seek optimal estimators (performed in R) for such statistical experiments

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  • Author : Alexandre Brouste
  • Publisher : Elsevier
  • Pages : 202 pages
  • ISBN : 0081012616
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKStatistical Inference in Financial and Insurance Mathematics with R

Statistical Inference in Financial and Insurance Mathematics with R

Statistical Inference in Financial and Insurance Mathematics with R
  • Author : Alexandre Brouste
  • Publisher : Elsevier
  • Release : 22 November 2017
GET THIS BOOKStatistical Inference in Financial and Insurance Mathematics with R

Finance and insurance companies are facing a wide range of parametric statistical problems. Statistical experiments generated by a sample of independent and identically distributed random variables are frequent and well understood, especially those consisting of probability measures of an exponential type. However, the aforementioned applications also offer non-classical experiments implying observation samples of independent but not identically distributed random variables or even dependent random variables. Three examples of such experiments are treated in this book. First, the Generalized Linear Models

Statistical Inference for Copula and Tail Copula Models with Applications to Finance and Insurance

Statistical Inference for Copula and Tail Copula Models with Applications to Finance and Insurance
  • Author : Liang Peng,Zhengjun Zhang
  • Publisher : Chapman & Hall/CRC
  • Release : 15 December 2018
GET THIS BOOKStatistical Inference for Copula and Tail Copula Models with Applications to Finance and Insurance

This book will cover statistical inference for copula and tail copula models with applications in finance, insurance and risk management. After giving a quick introduction to copula and tail copula models, it will focus on various up-to-date statistical inference procedures, including point and interval estimation and goodness-of- t tests, for both copulas and tail copulas based on either independent data or dependent data. A chapter on applications in nance, insurance and risk management will be provided with R code.

Computation and Modelling in Insurance and Finance

Computation and Modelling in Insurance and Finance
  • Author : Erik Bølviken
  • Publisher : Cambridge University Press
  • Release : 10 April 2014
GET THIS BOOKComputation and Modelling in Insurance and Finance

This practical introduction outlines methods for analysing actuarial and financial risk at a fairly elementary mathematical level suitable for graduate students, actuaries and other analysts in the industry who could use simulation as a problem solver. Numerous exercises with R-code illustrate the text.

Stochastic Calculus for Quantitative Finance

Stochastic Calculus for Quantitative Finance
  • Author : Alexander A Gushchin
  • Publisher : Elsevier
  • Release : 26 August 2015
GET THIS BOOKStochastic Calculus for Quantitative Finance

In 1994 and 1998 F. Delbaen and W. Schachermayer published two breakthrough papers where they proved continuous-time versions of the Fundamental Theorem of Asset Pricing. This is one of the most remarkable achievements in modern Mathematical Finance which led to intensive investigations in many applications of the arbitrage theory on a mathematically rigorous basis of stochastic calculus. Mathematical Basis for Finance: Stochastic Calculus for Finance provides detailed knowledge of all necessary attributes in stochastic calculus that are required for applications of the

Financial Risk Modelling and Portfolio Optimization with R

Financial Risk Modelling and Portfolio Optimization with R
  • Author : Bernhard Pfaff
  • Publisher : John Wiley & Sons
  • Release : 05 November 2012
GET THIS BOOKFinancial Risk Modelling and Portfolio Optimization with R

Introduces the latest techniques advocated for measuringfinancial market risk and portfolio optimization, and provides aplethora of R code examples that enable the reader to replicate theresults featured throughout the book. Financial Risk Modelling and Portfolio Optimization withR: Demonstrates techniques in modelling financial risks andapplying portfolio optimization techniques as well as recentadvances in the field. Introduces stylized facts, loss function and risk measures,conditional and unconditional modelling of risk; extreme valuetheory, generalized hyperbolic distribution, volatility modellingand concepts for capturing dependencies. Explores

Dynamic Copula Methods in Finance

Dynamic Copula Methods in Finance
  • Author : Umberto Cherubini,Sabrina Mulinacci,Fabio Gobbi,Silvia Romagnoli
  • Publisher : John Wiley & Sons
  • Release : 21 November 2011
GET THIS BOOKDynamic Copula Methods in Finance

The latest tools and techniques for pricing and risk management This book introduces readers to the use of copula functions to represent the dynamics of financial assets and risk factors, integrated temporal and cross-section applications. The first part of the book will briefly introduce the standard the theory of copula functions, before examining the link between copulas and Markov processes. It will then introduce new techniques to design Markov processes that are suited to represent the dynamics of market risk

Extreme Events in Finance

Extreme Events in Finance
  • Author : Francois Longin
  • Publisher : John Wiley & Sons
  • Release : 21 September 2016
GET THIS BOOKExtreme Events in Finance

A guide to the growing importance of extreme value risk theory, methods, and applications in the financial sector Presenting a uniquely accessible guide, Extreme Events in Finance: A Handbook of Extreme Value Theory and Its Applications features a combination of the theory, methods, and applications of extreme value theory (EVT) in finance and a practical understanding of market behavior including both ordinary and extraordinary conditions. Beginning with a fascinating history of EVTs and financial modeling, the handbook introduces the historical

Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics

Statistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics
  • Author : Jianchang Lin,Bushi Wang,Xiaowen Hu,Kun Chen,Ray Liu
  • Publisher : Springer
  • Release : 13 November 2016
GET THIS BOOKStatistical Applications from Clinical Trials and Personalized Medicine to Finance and Business Analytics

The papers in this volume represent a broad, applied swath of advanced contributions to the 2015 ICSA/Graybill Applied Statistics Symposium of the International Chinese Statistical Association, held at Colorado State University in Fort Collins. The contributions cover topics that range from statistical applications in business and finance to applications in clinical trials and biomarker analysis. Each papers was peer-reviewed by at least two referees and also by an editor. The conference was attended by over 400 participants from academia, industry, and

Analyzing Event Statistics in Corporate Finance

Analyzing Event Statistics in Corporate Finance
  • Author : Jau-Lian Jeng
  • Publisher : Springer
  • Release : 04 February 2015
GET THIS BOOKAnalyzing Event Statistics in Corporate Finance

Analyzing Event Statistics in Corporate Finance provides new alternative methodologies to increase accuracy when performing statistical tests for event studies within corporate finance. In contrast to conventional surveys or literature reviews, Jeng focuses on various methodological defects or deficiencies that lead to inaccurate empirical results, which ultimately produce bad corporate policies. This work discusses the issues of data collection and structure, the recursive smoothing for systematic components in excess returns, the choices of event windows, different time horizons for the

Financial Engineering with Copulas Explained

Financial Engineering with Copulas Explained
  • Author : J. Mai,M. Scherer
  • Publisher : Springer
  • Release : 02 October 2014
GET THIS BOOKFinancial Engineering with Copulas Explained

This is a succinct guide to the application and modelling of dependence models or copulas in the financial markets. First applied to credit risk modelling, copulas are now widely used across a range of derivatives transactions, asset pricing techniques and risk models and are a core part of the financial engineer's toolkit.

Risk And Stochastics: Ragnar Norberg

Risk And Stochastics: Ragnar Norberg
  • Author : Barrieu Pauline
  • Publisher : World Scientific
  • Release : 18 April 2019
GET THIS BOOKRisk And Stochastics: Ragnar Norberg

with an autobiography from Ragnar NorbergThe Risk and Stochastics Conference, held at the Royal Statistical Society in April 2015, brought together academics from the worlds of actuarial science, stochastic calculus, finance and statistics to celebrate the achievements of Professor Ragnar Norberg as he turned 70. After the conference, Ragnar Norberg suddenly fell very ill and passed away; this book honours his life and work.This collection of articles is written by speakers of the conference, themselves respected academics who have influenced and

Model Risk in Financial Markets

Model Risk in Financial Markets
  • Author : Radu Tunaru
  • Publisher : World Scientific
  • Release : 08 June 2015
GET THIS BOOKModel Risk in Financial Markets

The financial systems in most developed countries today build up a large amount of model risk on a daily basis. However, this is not particularly visible as the financial risk management agenda is still dominated by the subprime-liquidity crisis, the sovereign crises, and other major political events. Losses caused by model risk are hard to identify and even when they are internally identified, as such, they are most likely to be classified as normal losses due to market evolution. Model

Counting Statistics for Dependent Random Events

Counting Statistics for Dependent Random Events
  • Author : Enrico Bernardi,Silvia Romagnoli
  • Publisher : Springer Nature
  • Release : 22 March 2021
GET THIS BOOKCounting Statistics for Dependent Random Events

This book on counting statistics presents a novel copula-based approach to counting dependent random events. It combines clustering, combinatorics-based algorithms and dependence structure in order to tackle and simplify complex problems, without disregarding the hierarchy of or interconnections between the relevant variables. These problems typically arise in real-world applications and computations involving big data in finance, insurance and banking, where experts are confronted with counting variables in monitoring random events. In this new approach, combinatorial distributions of random events are

Risk - A Multidisciplinary Introduction

Risk - A Multidisciplinary Introduction
  • Author : Claudia Klüppelberg,Daniel Straub,Isabell M. Welpe
  • Publisher : Springer
  • Release : 10 June 2014
GET THIS BOOKRisk - A Multidisciplinary Introduction

This is a unique book addressing the integration of risk methodology from various fields. It will stimulate intellectual debate and communication across disciplines, promote better risk management practices and contribute to the development of risk management methodologies. Individual chapters explain fundamental risk models and measurement, and address risk and security issues from diverse areas such as finance and insurance, the health sciences, life sciences, engineering and information science. Integrated Risk Sciences is an emerging discipline that considers risks in different

R Programming for Actuarial Science

R Programming for Actuarial Science
  • Author : Peter McQuire,Alfred Kume
  • Publisher : Wiley
  • Release : 28 December 2021
GET THIS BOOKR Programming for Actuarial Science

R Programming for Actuarial Science and Financial Mathematics provides a grounding in R programming applied to the mathematical and statistical methods that are of relevance for actuarial work. It equips the student with knowledge of statistical distributions and methods to summarize data. This book provides coding at a basic to intermediate level in respect of numerous actuarial applications, and real-life examples are included with every topic. Whilst each chapter includes a certain amount of theory, the length of which will