Statistics for Finance

Katalog książek
anglojęzycznych
statystyka finansowa
i ekonometria
Amerykańskie Towarzystwo Statystyczne ogłosiło rok 2013
Międzynarodowym Rokiem Statystyki. Ogólnoświatowa akcja
ma na celu uczczenie i docenienie osiągnięć nauk statystycznych.
Przyłączyliśmy się do akcji promując najważniejsze książki z tej
dziedziny.

Przeglądaj katalog z nowościami i najciekawszymi publikacjami.

Dowiedz się więcej na www.abe.pl/statystyka2013

Statystyka finansowa i ekonometria

A Concise Introduction to Business A Course on Statistics for Finance
Research Methods
D. Israel Stanley L. Sclove
Taylor & Francis Taylor & Francis

9781439861097 9781439892541
16.12.2013 03.01.2013
Oprawa: twarda Oprawa: twarda
£ 49,99 £ 57,99
Introductory in its approach, this text covers essential aspects of research methods. Taking a data-driven approach, A Course on Statistics for Finance presents
The author emphasizes major topics, such as experimental design, scale statistical methods for financial investment analysis. The author introduces
construction techniques, testing reliability and validity, as well as the application of regression analysis, time series analysis, and multivariate analysis step by step using
univariate, bivariate, and multivariate tools in data analysis. Step-by-step details of models and methods from finance. The book begins with a review of basic
the application of the SPSS, along with screenshots, are included to illustrate the statistics, including descriptive statistics, kinds of variables, and types of data sets. It
application of tools to analyze and interpret research data. The book covers pre-, then discusses regression analysis in general terms and in terms of financial
quasi-, true-, and complex experimental design forms. Each chapter contains investment models, such as the capital asset pricing model and the Fama/French
descriptive questions, multiple-choice questions, true/false statements, and model. It also describes mean-variance portfolio analysis and concludes with a
exercises. focus on time series analysis. Providing the connection between elementary
statistics courses and quantitative finance courses, this text helps both existing and
future quants improve their data analysis skills and better understand the modeling
process.

A Modern Theory of Random Variation A Practitioner's Guide to Resampling
for Data Analysis, Data Mining, and
Patrick Muldowney Phillip I. Good
Wiley Taylor & Francis

9781118166406 9781439855508
16.11.2012 19.08.2011
£ 76,95 £ 59,99
This book presents a self-contained study of the Riemann approach to the theory of Distribution-free resampling methods-permutation tests, decision trees, and the
random variation and assumes only some familiarity with probability or statistical bootstrap-are used today in virtually every research area. A Practitioner's Guide to
analysis, basic Riemann integration, and mathematical proofs. The author focuses Resampling for Data Analysis, Data Mining, and Modeling explains how to use the
on non-absolute convergence in conjunction with random variation. Any conception bootstrap to estimate the precision of sample-based estimates and to determine
or understanding of the random variation phenomenon hinges on the notions of sample size, data permutations to test hypotheses, and the readily-interpreted
probability and its mathematical representation in the form of probability distribution decision tree to replace arcane regression methods. Highlights Each chapter
functions. The central and recurring theme throughout this book is that, provided contains dozens of thought provoking questions, along with applicable R and Stata
the use a non-absolute method of summation, every finitely additive, function of code Methods are illustrated with examples from agriculture, audits, bird migration,
disjoint intervals is integrable. In contrast, more traditional methods in probability clinical trials, epidemiology, image processing, immunology, medicine, microarrays
theory exclude significant classes of such functions whose integrability cannot be and gene selection Lists of commercially available software for the bootstrap,
established whenever only absolute convergence is considered. An examples decision trees, and permutation tests are incorporated in the text Access to APL,
includes the Feynman "measure-which-is-not-a-measure" - the so-called probability MATLAB, and SC code for many of the routines is provided on the author's website
amplitudes used in the Feynman path integrals of quantum mechanics.

Active Risk Management An Introduction to Analysis of Financial
Data with R
Lai Ruey S. Tsay
Taylor & Francis Wiley

9781439839485 9780470890813
05.11.2013 07.12.2012
£ 57,99 £ 86,95
Following the recent financial crisis, risk management in financial institutions, This book provides a systematic and mathematically accessible introduction to
particularly in banks, has attracted widespread attention and discussion. Novel financial econometric models and their applications in modeling and predicting
modeling approaches and courses to educate future professionals in industry, financial time series data. It emphasizes empirical financial data and focuses on real-
government, and academia are of timely relevance. This book introduces an world examples. Following this approach, readers will master key aspects of
innovative concept and methodology developed by the authors: active risk financial time series, including volatility modeling, neural network applications,
management. It is suitable for graduate students in mathematical finance/financial market microstructure, and high-frequency financial data. S-Plus(r) commands and
engineering, economics, and statistics as well as for practitioners in the fields of illustrations are used extensively throughout the book in order to highlight accurate
finance and insurance. The book’s website features the data sets used in the interpretations and graphical representations of financial data. Exercises are
examples along with various exercises. included in order to provide readers with more opportunities to put the models and
Following the recent financial crisis, risk management in financial institutions, methods into everyday practice. The tools provided in the text aid readers in
particularly in banks, has attracted widespread attention and discussion. Novel developing a deeper understanding of financial markets through firsthand
modeling approaches and courses to educate future professionals in industry, experience in working with financial data, most importantly without needless
government, and academia are of timely relevance. computation.
This book introduces an innovative concept and methodology developed by the
authors: active risk management. It is suitable for graduate students in mathematical

2 www.abe.pl


An Introduction to Exotic Option Pricing Analysis of Financial Time Series

Peter Buchen Ruey S. Tsay

9781420091007 9780470414354
02.03.2012 10.09.2010
£ 49,99 £ 90,95
In an easy-to-understand, nontechnical yet mathematically elegant manner, An This book provides a broad, mature, and systematic introduction to current financial
Introduction to Exotic Option Pricing shows how to price exotic options, including econometric models and their applications to modeling and prediction of financial
complex ones, without performing complicated integrations or formally solving time series data. It utilizes real-world examples and real financial data throughout the
partial differential equations (PDEs). The author incorporates much of his own book to apply the models and methods described.
unpublished work, including ideas and techniques new to the general quantitative The author begins with basic characteristics of financial time series data before
finance community. The first part of the text presents the necessary financial, covering three main topics:
mathematical, and statistical background, covering both standard and specialized
topics. Using no-arbitrage concepts, the Black-Scholes model, and the fundamental
 Analysis and application of univariate financial time series
theorem of asset pricing, the author develops such specialized methods as the  The return series of multiple assets
principle of static replication, the Gaussian shift theorem, and the method of images.  Bayesian inference in finance methods
A key feature is the application of the Gaussian shift theorem and its multivariate Key features of the new edition include additional coverage of modern day topics
extension to price exotic options without needing a single integration. The second such as arbitrage, pair trading, realized volatility, and credit risk modeling; a smooth
part focuses on applications to exotic option pricing, including dual-expiry, multi- transition from S-Plus to R; and expanded empirical financial data sets.
asset rainbow, barrier, lookback, and Asian options.

Applied Business Statistics: Making Applied Statistics for Business and
Better Business Decisions Economics
Ken Black Robert M. Leekley

9781118092293 9781439805688
03.02.2012 19.03.2010
Oprawa: miękka Oprawa: twarda
£ 54,99 £ 56,99
Black's latest outstanding pedagogy of Business Statistics includes the use of extra Designed for a one-semester course, Applied Statistics for Business and Economics
problems called "Demonstration Problems" to provide additional insight and offers students in business and the social sciences an effective introduction to some
explanation to working problems, and presents concepts, topics, formulas, and of the most basic and powerful techniques available for understanding their world.
application in a manner that is palatable to a vast audience and minimizes the use of Numerous interesting and important examples reflect real-life situations, stimulating
"scary" formulas. Every chapter opens up with a vignette called a "Decision students to think realistically in tackling these problems. Calculations can be
Dilemma" about real companies, data, and business issues. Solutions to these performed using any standard spreadsheet package. To help with the examples, the
dilemmas are presented as a feature called "Decision Dilemma Solved." In this author offers both actual and hypothetical databases on his website http://iwu.edu/
edition all cases and "Decision Dilemmas" are updated and revised and 1/3 have ~bleekley The text explores ways to describe data and the relationships found in
been replaced for currency. There is also a significant number of additional problems data. It covers basic probability tools, Bayes' theorem, sampling, estimation, and
and an extremely competitive collection of databases (containing real data) on: confidence intervals. The text also discusses hypothesis testing for one and two
international stock markets, consumer food, international labor, financial, energy, samples, contingency tables, goodness-of-fit, analysis of variance, and population
agribusiness, 12-year gasoline, manufacturing, and hospital. variances. In addition, the author develops the concepts behind the linear
relationship between two numeric variables (simple regression) as well as the
potentially nonlinear relationships among more than two variables (multiple
regression).

Applied Stochastic Finance: v. 1 ARCH Models for Financial Applications

P-C.G. Vassiliou Evdokia Xekalaki
Wiley Wiley

9781848211582 9780470066300
19.01.2010 09.04.2010
£ 99,95 £ 65,95
Stochastic finance and financial engineering have been rapidly expanding fields of ARCH Models for Financial Applications provides background on the theory of
science over the past four decades, mainly due to the success of sophisticated ARCH models, with a focus on practical implementation via applications to real data
quantitative methodologies in helping professionals manage financial risks. In recent and examples worked with econometrics packages. The interactional exposition of
years, we have witnessed a tremendous acceleration in research efforts aimed at the ARCH theory, and its implementation in practice that the authors adopt, helps
better comprehending, modeling and hedging this kind of risk. readers get a deeper understanding of the models and their use as tools in applied
These two volumes aim to provide a foundation course on applied stochastic financial contexts. Intended for readers seeking an aptitude in the applications of
finance. They are designed for three groups of readers: firstly, students of various financial econometric modeling, this book requires only a basic knowledge of
backgrounds seeking a core knowledge on the subject of stochastic finance; econometrics and basic undergraduate-level statistics.
secondly financial analysts and practitioners in the investment, banking and
insurance industries; and finally other professionals who are interested in learning
advanced mathematical and stochastic methods, which are basic knowledge in
many areas, through finance.
Volume 1 starts with the introduction of the basic financial instruments and the
fundamental principles of financial modeling and arbitrage valuation of derivatives.
Next, we use the discrete-time binomial model to introduce all relevant concepts.

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Bayesian Methods in Insurance and Black-Scholes Model
Actuarial Science
Yanwei Zhang Marek Capinski
Taylor & Francis Cambridge University Press

9781466510616 9780521173001
05.12.2013 13.09.2012
Oprawa: twarda Oprawa: miękka
£ 57,99 £ 24,00
There has been a rapidly growing interest in Bayesian methods among insurance The Black-Scholes option pricing model is the first and by far the best-known
practitioners in recent years, mainly because of their ability to generate predictive continuous-time mathematical model used in mathematical finance. Here, it
distributions and to rigorously incorporate expert opinion through prior probabilities. provides a sufficiently complex, yet tractable, testbed for exploring the basic
This book introduces modern Bayesian modeling techniques for actuarial and methodology of option pricing. The discussion of extended markets, the careful
insurance applications. It first provides the necessary background in current attention paid to the requirements for admissible trading strategies, the development
actuarial practice and then presents Bayesian methods and MCMC. It includes of pricing formulae for many widely traded instruments and the additional
advanced techniques, such as nonlinear modeling, as well as three chapters on complications offered by multi-stock models will appeal to a wide class of
model selection and averaging. The text features case studies using real actuarial instructors. Students, practitioners and researchers alike will benefit from the book's
and insurance data with computations in R and WinBUGS. rigorous, but unfussy, approach to technical issues. It highlights potential pitfalls,
gives clear motivation for results and techniques and includes carefully chosen
examples and exercises, all of which make it suitable for self-study.

Business Statistics for Competitive Choice-based Conjoint Analysis:
Advantage with Excel 2010 Models and Designs
Cynthia Fraser Damaraju Raghavarao
Springer Taylor & Francis

9781441998569 9781420099966
27.03.2012 11.08.2010
€ 74,95 £ 62,99
Exceptional managers know that they can create competitive advantages by basing Disseminating information from researchers in various fields, this compilation
decisions on performance response under alternative scenarios. To create these presents the research themes, methods, and findings, making it a significant
advantages, managers need to understand how to use statistics to provide reference for design researchers and design practitioners interested in furthering
information on performance response under alternative scenarios. This updated understanding of design activity in real-world settings. It presents an analysis of
edition of the popular text helps business students develop competitive advantages digital video recordings of a series of design meetings on the conceptual stages of a
for use in their future careers as decision makers. Students learn to build models design project. The data were gathered from design meetings taking place as part
using logic and experience, produce statistics using Excel 2010 with shortcuts, and of naturally occurring design practice, rather than being gathered through a staged
translate results into implications for decision makers. The author emphasizes experiment in which the conditions are highly controlled.
communicating results effectively in plain English and with compelling graphics in the
form of memos and PowerPoints. Statistics, from basics to sophisticated models,
are illustrated with examples using real data such as students will encounter in their
roles as managers. A number of examples focus on business in emerging global
markets with particular emphasis on China and India. Results are linked to
implications for decision making with sensitivity analyses to illustrate how alternate
scenarios can be compared.

Clustering: A Data Recovery Approach Computation and Modelling in
Insurance and Finance: An Introduction
Boris Mirkin Eric Bolviken
Taylor & Francis Cambridge University Press

9781439838419 9780521830485
15.11.2012 01.10.2013
£ 63,99 £ 65,00
Often considered more of an art than a science, books on clustering have been Focusing on what actuaries need in practice, this introductory account provides
dominated by learning through example with techniques chosen almost through trial readers with essential tools for handling complex problems and explains how
and error. Even the two most popular, and most related, clustering methods-K- simulation models can be created, used and re-used (with modifications) in related
Means for partitioning and Ward's method for hierarchical clustering-have lacked the situations. The book begins by outlining the basic tools of modelling and simulation,
theoretical underpinning required to establish a firm relationship between the two including a discussion of the Monte Carlo method and its use. Part II deals with
methods and relevant interpretation aids. Other approaches, such as spectral general insurance and Part III with life insurance and financial risk. Algorithms that
clustering or consensus clustering, are considered absolutely unrelated to each can be implemented on any programming platform are spread throughout and a
other or to the two above mentioned methods. Clustering: A Data Recovery program library written in R is included. Numerous figures and experiments with R-
Approach, Second Edition presents a unified modeling approach for the most code illustrate the text. The author's non-technical approach is ideal for graduate
popular clustering methods: the K-Means and hierarchical techniques, especially for students, the only prerequisites being introductory courses in calculus and linear
divisive clustering. It significantly expands coverage of the mathematics of data algebra, probability and statistics. The book will also be of value to actuaries and
recovery, and includes a new chapter covering more recent popular network other analysts in the industry looking to update their skills.
clustering approaches-spectral, modularity and uniform, additive, and consensus-
treated within the same data recovery approach.

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Customer and Business Analytics Data Driven Business Decisions

Robert E. Krider Chris J. Lloyd

9781466503960 9780470619605
06.06.2012 04.11.2011
£ 44,99 £ 83,50
Customer and Business Analytics: Applied Data Mining for Business Decision A hands-on guide to the use of quantitative methods and software for making
Making Using R explains and demonstrates, via the accompanying open-source successful business decisions The appropriate use of quantitative methods lies at
software, how advanced analytical tools can address various business problems. It the core of successful decisions made by managers, researchers, and students in
also gives insight into some of the challenges faced when deploying these tools. the field of business. Providing a framework for the development of sound judgment
Extensively classroom-tested, the text is ideal for students in customer and business and the ability to utilize quantitative and qualitative approaches, Data Driven
analytics or applied data mining as well as professionals in small- to medium-sized Business Decisions introduces readers to the important role that data plays in
organizations. The book offers an intuitive understanding of how different analytics understanding business outcomes, addressing four general areas that managers
algorithms work. Where necessary, the authors explain the underlying mathematics need to know about: data handling and Microsoft Excel(r), uncertainty, the
in an accessible manner. Each technique presented includes a detailed tutorial that relationship between inputs and outputs, and complex decisions with trade-offs and
enables hands-on experience with real data. The authors also discuss issues often uncertainty. Grounded in the author's own classroom approach to business
encountered in applied data mining projects and present the CRISP-DM process statistics, the book reveals how to use data to understand the drivers of business
model as a practical framework for organizing these projects. Showing how data outcomes, which in turn allows for data-driven business decisions.
mining can improve the performance of organizations, this book and its R-based
software provide the skills and tools needed to successfully develop advanced
analytics capabilities.

Data Mining Mobile Devices Developing Econometrics

Jesus Mena Hengqing Tong

9781466555952 9780470681770
25.06.2013 25.11.2011
£ 44,99 £ 55,00
Data Mining Mobile Devices, also known as "Reality Mining," defines the collection Statistical Theories and Methods with Applications to Economics and Business
of machine-sensed environmental data pertaining to human social behavior. This highlights recent advances in statistical theory and methods that benefit
new paradigm of data mining makes possible the modeling of conversation context, econometric practice. It deals with exploratory data analysis, a prerequisite to
proximity sensing, and temporospatial location throughout large communities of statistical modelling and part of data mining. It provides recently developed
individuals. Mobile phones (and similarly innocuous devices) are used for data computational tools useful for data mining, analysing the reasons to do data mining
collection, opening behavior analysis to new methods of empirical stochastic and the best techniques to use in a given situation.
modeling. The book explains how the combination of data mining and machine
learning makes this possible, and details how to integrate the various technologies.
 Provides a detailed description of computer algorithms.
 Provides recently developed computational tools useful for data mining
 Highlights recent advances in statistical theory and methods that benefit
econometric practice.
 Features examples with real life data.
 Accompanying software featuring DASC (Data Analysis and Statistical
Computing).

Developing, Validating and Using Discrete Models of Financial Markets
Internal Ratings
Giacomo de Laurentis Ekkehard Kopp
Wiley Cambridge University Press

9780470711491 9780521175722
24.09.2010 23.02.2012
£ 62,50 £ 24,00
This book provides a thorough analysis of internal rating systems. Two case studies This book explains in simple settings the fundamental ideas of financial market
are devoted to building and validating statistical-based models for borrowers' modelling and derivative pricing, using the no-arbitrage principle. Relatively
ratings, using SPSS-PASW and SAS statistical packages. Mainstream approaches elementary mathematics leads to powerful notions and techniques - such as
to building and validating models for assigning counterpart ratings to small and viability, completeness, self-financing and replicating strategies, arbitrage and
medium enterprises are discussed, together with their implications on lending equivalent martingale measures - which are directly applicable in practice. The
strategy. Key Features: * Presents an accessible framework for bank managers, general methods are applied in detail to pricing and hedging European and
students and quantitative analysts, combining strategic issues, management needs, American options within the Cox-Ross-Rubinstein (CRR) binomial tree model. A
regulatory requirements and statistical bases. * Discusses available methodologies simple approach to discrete interest rate models is included, which, though
to build, validate and use internal rate models. * Demonstrates how to use statistical elementary, has some novel features. All proofs are written in a user-friendly manner,
packages for building statistical-based credit rating systems. * Evaluates sources of with each step carefully explained and following a natural flow of thought. In this way
model risks and strategic risks when using statistical-based rating systems in the student learns how to tackle new problems.
lending. This book will prove to be of great value to bank managers, credit and loan
officers, quantitative analysts and advanced students on credit risk management
courses.

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Discrete Models of Financial Markets Economic Time Series: Modeling and
Seasonality
Ekkehard Kopp William R. Bell
Cambridge University Press Taylor & Francis

9781107002630 9781439846575
23.02.2012 18.04.2012
£ 50,00 £ 63,99
This book explains in simple settings the fundamental ideas of financial market Economic Time Series: Modeling and Seasonality is a focused resource on analysis
modelling and derivative pricing, using the no-arbitrage principle. Relatively of economic time series as pertains to modeling and seasonality, presenting cutting-
elementary mathematics leads to powerful notions and techniques - such as edge research that would otherwise be scattered throughout diverse peer-reviewed
viability, completeness, self-financing and replicating strategies, arbitrage and journals. This compilation of 21 chapters showcases the cross-fertilization between
equivalent martingale measures - which are directly applicable in practice. The the fields of time series modeling and seasonal adjustment, as is reflected both in
general methods are applied in detail to pricing and hedging European and the contents of the chapters and in their authorship, with contributors coming from
American options within the Cox-Ross-Rubinstein (CRR) binomial tree model. A academia and government statistical agencies. For easier perusal and absorption,
simple approach to discrete interest rate models is included, which, though the contents have been grouped into seven topical sections: Section I deals with
elementary, has some novel features. All proofs are written in a user-friendly manner, periodic modeling of time series, introducing, applying, and comparing various
with each step carefully explained and following a natural flow of thought. In this way seasonally periodic models Section II examines the estimation of time series
the student learns how to tackle new problems. components when models for series are misspecified in some sense, and the
broader implications this has for seasonal adjustment and business cycle estimation
Section III examines the quantification of error in X-11 seasonal adjustments, with
comparisons to error in model-based seasonal adjustments

Extreme Value Methods with Financial and Actuarial Statistics: An
Applications to Finance Introduction
Serguei Y. Novak Dale S. Borowiak

9781439835746 9781420085808
21.12.2011 15.10.2013
£ 66,99 £ 57,99
Extreme value theory (EVT) deals with extreme (rare) events, which are sometimes Presenting a unique interface between statistics and financial/actuarial topics, this
reported as outliers. Certain textbooks encourage readers to remove outliers-in second edition provides a solid background for students preparing for a career in
other words, to correct reality if it does not fit the model. Recognizing that any actuarial science. It explores novel research areas and adds more problems, along
model is only an approximation of reality, statisticians are eager to extract with a new solutions section. This edition also includes a new chapter on Markov
information about unknown distribution making as few assumptions as possible. chain theory with applications to mortality and multiple decrement mortality table
Extreme Value Methods with Applications to Finance concentrates on modern modeling, a presentation of model checking diagnostics that covers diagnostics for
topics in EVT, such as processes of exceedances, compound Poisson mortality tables, and an expanded discussion on option pricing with examples.
approximation, Poisson cluster approximation, and nonparametric estimation
methods. These topics have not been fully focused on in other books on extremes.
In addition, the book covers: Extremes in samples of random size Methods of
estimating extreme quantiles and tail probabilities Self-normalized sums of random
variables Measures of market risk Along with examples from finance and insurance
to illustrate the methods, Extreme Value Methods with Applications to Finance
includes over 200 exercises, making it useful as a reference book, self-study tool, or
comprehensive course text.

Financial Mathematics: A Financial Risk Modelling and Portfolio
Comprehensive Treatment Optimization with R
Giuseppe Campolieti Bernhard Pfaff

9781439892428 9780470978702
17.10.2013 07.12.2012
£ 57,99 £ 60,00
This text offers a comprehensive, self-contained, and unified treatment of the theory Introduces the latest techniques advocated for measuring financial market risk and
and application of mathematical methods behind modern-day financial portfolio optimization, and provides a plethora of R code examples that enable the
mathematics. It introduces the financial theory and the relevant mathematical reader to replicate the results featured throughout the book.
methods in a mathematically rigorous yet student-friendly and engaging style. The Financial Risk Modelling and Portfolio Optimization with R:
text provides complete and in-depth coverage of both discrete- and continuous-
time financial models and pricing theory. It also includes numerous examples,
 Demonstrates techniques in modelling financial risks and applying portfolio
optimization techniques as well as recent advances in the field.
exercises, fully worked out solutions, and multiple problem-solving approaches. A
solutions manual is available upon qualifying course adoption.  Introduces stylized facts, loss function and risk measures, conditional and
unconditional modelling of risk; extreme value theory, generalized
hyperbolic distribution, volatility modelling and concepts for capturing
dependencies.
 Explores portfolio risk concepts and optimization with risk constraints.
 Enables the reader to replicate the results in the book using R code.

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Financial Statistics and Mathematical GARCH Models
Finance
Ansgar Steland Christian Francq
Wiley Wiley

9780470710586 9780470683910
20.07.2012 16.07.2010
£ 55,00 £ 60,00
Mathematical finance has grown into a huge area of research which requires a lot of This book provides a comprehensive and systematic approach to understanding
care and a large number of sophisticated mathematical tools. Mathematically GARCH time series models and their applications whilst presenting the most
rigorous and yet accessible to advanced level practitioners and mathematicians advanced results concerning the theory and practical aspects of GARCH. The
alike, it considers various aspects of the application of statistical methods in finance probability structure of standard GARCH models is studied in detail as well as
and illustrates some of the many ways that statistical tools are used in financial statistical inference such as identification, estimation and tests. The book also
applications. Financial Statistics and Mathematical Finance: Provides an introduction provides coverage of several extensions such as asymmetric and multivariate
to the basics of financial statistics and mathematical finance. Explains the use and models and looks at financial applications. Key features: Provides up-to-date
importance of statistical methods in econometrics and financial engineering. coverage of the current research in the probability, statistics and econometric theory
Illustrates the importance of derivatives and calculus to aid understanding in of GARCH models. Numerous illustrations and applications to real financial series
methods and results. Looks at advanced topics such as martingale theory, are provided. Supporting website featuring R codes, Fortran programs and data
stochastic processes and stochastic integration. Features examples throughout to sets. Presents a large collection of problems and exercises. This authoritative, state
illustrate applications in mathematical and statistical finance. Is supported by an -of-the-art reference is ideal for graduate students, researchers and practitioners in
accompanying website featuring R code and data sets. business and finance seeking to broaden their skills of understanding of
econometric time series models.

Handbook of Empirical Economics and Handbook of Exchange Rates
Finance
Aman Ullah Jessica James

9781420070354 9780470768839
16.12.2010 24.07.2012
£ 101,00 £ 100,00
Handbook of Empirical Economics and Finance explores the latest developments in Handbook of Exchange Rates is an impressive compilation of research from more
the analysis and modeling of economic and financial data. Well-recognized than thirty-five leading researchers and experts on the topic. The book is clearly
econometric experts discuss the rapidly growing research in economics and finance organized into five succinct sections that explore the foreign exchange (FX) market,
and offer insight on the future direction of these fields. Focusing on micro models, from its background and economic foundation to current practices, obstacles, and
the first group of chapters describes the statistical issues involved in the analysis of policies in the modern foreign exchange market. Part I presents an overview of the
econometric models with cross-sectional data often arising in microeconomics. The history of the FX market and exchange rate regimes, the key instruments/players in
book then illustrates time series models that are extensively used in empirical the FX trading environment, and both macro and micro approaches to FX
macroeconomics and finance. The last set of chapters explores the types of panel determination. Next, Part II focuses on forecasting exchange rates, featuring
data and spatial models that are becoming increasingly significant in analyzing methodological contributions on the sstatistical methods for evaluating forecast
complex economic behavior and policy evaluations. This handbook brings together performance, parity relationships, fair value models, and flow-based models. Part III
both background material and new methodological and applied results that are treats FX as an asset class, outlining active currency management, currency
extremely important to the current and future frontiers in empirical economics and hedging, hedge accounting, high frequency and algorithmic trading in FX, and FX
finance. It emphasizes inferential issues that transpire in the analysis of cross- strategy-based products. Part IV discusses products and pricing in FX, the FX
sectional, time series, and panel data-based empirical models in economics, options market, and volatility derivatives.
finance, and related disciplines.

Handbook of Modeling High-Frequency Handbook of Solvency for Actuaries
Data in Finance and Risk Managers
Frederi G. Viens Arne Sandstrom

9780470876886 9781439821305
06.01.2012 12.11.2010
£ 100,50 £ 97,00
CUTTING-EDGE DEVELOPMENTS IN HIGH-FREQUENCY FINANCIAL Reflecting the author's wealth of experience in this field, Handbook of Solvency for
ECONOMETRICS In recent years, the availability of high-frequency data and Actuaries and Risk Managers: Theory and Practice focuses on the valuation of
advances in computing have allowed financial practitioners to design systems that assets and liabilities, the calculation of capital requirement, and the calculation of the
can handle and analyze this information. Handbook of Modeling High-Frequency standard formula for the European Solvency II project. The first three sections of the
Data in Finance addresses the many theoretical and practical questions raised by book examine the solvency concept, historical development, and the role of
the nature and intrinsic properties of this data. A one-stop compilation of empirical solvency in an enterprise risk management approach. The text provides a general
and analytical research, this handbook explores data sampled with high-frequency discussion on valuation, investment, and capital, along with modeling and
finance in financial engineering, statistics, and the modern financial business arena. measuring. It also covers dependence, risk measures, capital requirements,
Every chapter uses real-world examples to present new, original, and relevant topics subrisks, aggregation, the main risks market, and credit, operational, liquidity, and
that relate to newly evolving discoveries in high-frequency finance, such as: underwriting risks. The last three sections focus on the European Solvency II
Designing new methodology to discover elasticity and plasticity of price evolution project. Basing the material on CEIOPS final advice, the author presents the general
Constructing microstructure simulation models Calculation of option prices in the ideas, valuation, investments, and funds of this project as well as the standard
presence of jumps and transaction costs Using boosting for financial analysis and formula framework. He also includes all calibrations from previous quantitative
trading. impact studies and discusses the political progress of the project.

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Insurance Risk and Ruin Introduction to Credit Risk Modeling

David C. M. Dickson Christian Bluhm

9780521176750 9781584889922
16.09.2010 02.06.2010
£ 31,99 £ 56,99
Based on the author's experience of teaching final-year actuarial students in Britain Illustrating mathematical models for structured credit with practical examples,
and Australia, and suitable for a first course in insurance risk theory, this book "Introduction to Credit Risk Modeling" provides an accessible introduction to the
focuses on the two major areas of risk theory - aggregate claims distributions and foundations of structured credit portfolio modeling. Updated and expanded, this
ruin theory. For aggregate claims distributions, detailed descriptions are given of second edition features additional material on estimation of asset correlations,
recursive techniques that can be used in the individual and collective risk models. benchmark correlations based on securitizations of benchmark portfolios in the
For the collective model, different classes of counting distribution are discussed, and market, risk contributions and spectral risk measures, non homogeneous Markov
recursion schemes for probability functions and moments presented. For the chain approaches, multi-year models, current agency models, single-tranche CDOs,
individual model, the three most commonly applied techniques are discussed and index tranches, as well as new developments in synthetics. The text also includes
illustrated. Care has been taken to make the book accessible to readers who have a new exercises and a supporting website.
solid understanding of the basic tools of probability theory.

Introduction to Stochastic Finance Introduction to the Practice of Statistics

Privault David S. Moore
Taylor & Francis Palgrave MacMillan

9781466594029 9781429286640
05.11.2013 08.04.2011
£ 49,99 £ 53,99
This comprehensive text presents an introduction to pricing and hedging in financial With a focus on data analysis, statistical reasoning, and the way statisticians actually
models, with an emphasis on analytical and probabilistic methods. It demonstrates work, IPS has helped to revolutionize the way statistics are taught and brings critical
both the power and limitations of mathematical models in finance. The book starts thinking and practical applications to your course.Revised for more learner-friendly
with the basics of finance and stochastic calculus and builds up to special topics, progression, the 7th edition includes 30% new exercises, including international
such as options, derivatives, and credit default and jump processes. Many real examples such as Facebook usage trends outside the USA. What this book offers
examples illustrate the topics and classroom-tested exercises are included in each students: * Focuses on data analysis and practical applications, showing the way
chapter, with selected solutions at the back of the book. statisticians actually work. * Fosters statistical reasoning and decision-making skills,
not just calculation drills, through a focus on problem-solving practice. * Presents
contemporary real data in real contexts, making the numbers and why we analyse
them meaningful. * Includes examples from many interesting disciplines (from
psychology to medicine and business) to give relevance to the material covered.

Life Contingencies Logit Models from Economics and
Other Fields
E. F. Spurgeon J. S. Cramer
Cambridge University Press Cambridge University Press

9781107648098 9780521188036
09.06.2011 03.03.2011
Oprawa: miękka Oprawa: miękka
£ 26,99 £ 25,99
Published in 1932, this is the third edition of an original 1922 volume. The 1922 Logistic models are widely used in economics and other disciplines and are easily
volume was, in turn, created as the replacement for the Institute of Actuaries available as part of many statistical software packages. This text for graduates,
Textbook, Part Three, which was the foremost source of knowledge on the subject practitioners and researchers in economics, medicine and statistics, which was
of life contingencies for over 35 years. Assuming a high level of mathematical originally published in 2003, explains the theory underlying logit analysis and gives a
knowledge on the part of the reader, it was aimed chiefly at actuarial students and thorough explanation of the technique of estimation. The author has provided many
those with a professional interest in the relationship between statistics and mortality. empirical applications as illustrations and worked examples. A large data set - drawn
Highly organised and containing numerous mathematical formulae, this book will from Dutch car ownership statistics - is provided online for readers to practise the
remain of value to anyone with an interest in risk calculation and the development of techniques they have learned. Several varieties of logit model have been developed
the insurance industry. independently in various branches of biology, medicine and other disciplines. This
book takes its inspiration from logit analysis as it is practised in economics, but it
also pays due attention to developments in these other fields.

8 www.abe.pl


Loss Models: from Data to Decisions Making It Happen: Using Causal Models
Student Solutions Manual for Business Analysis
Stuart A. Klugman Aaron L Bramson

9781118315316 9780415657600
15.10.2012 15.09.2013
Oprawa: miękka Oprawa: miękka
£ 23,50 £ 31,99
An update of one of the most trusted books on constructing and analyzing actuarial Ryall and Bramson's Inference and Intervention is the first textbook on causal
models for the C/4 actuarial exam This new, abridged edition has been thoroughly modeling with Bayesian networks for business applications. In a world of resource
revised and updated to include the essential material related to Exam C of the scarcity, a decision about which business elements to control or change – as the
Society of Actuaries' and Casualty Actuarial Society's accreditation programs. The authors put it, a managerial intervention – must precede any decision on how to
book maintains an approach to modeling and forecasting that utilizes tools related control or change them, and understanding causality is crucial to making effective
to risk theory, loss distributions, and survival models. Random variables, basic interventions.
distributional quantities, the recursive method, and techniques for classifying and
creating distributions are also discussed. Both parametric and non-parametric The authors cover the full spectrum of causal modeling techniques useful for the
estimation methods are thoroughly covered along with advice for choosing an managerial role, whether for intervention, situational assessment, strategic decision-
appropriate model. The book continues to distinguish itself by providing over 400 making, or forecasting. From the basic concepts and nomenclature of causal
exercises that have appeared on previous examinations.The emphasis throughout is modeling to decision tree analysis, qualitative methods, and quantitative modeling
now placed on calculations and spreadsheet implementation. tools, this book offers a toolbox for MBA students and business professionals to
make successful decisions in a managerial setting.

Mathematical Statistics for Economics Methods and Applications of Statistics in
and Business Business, Finance, and Management Science

Ron C. Mittelhammer N. Balakrishnan
Springer Wiley

9781461450214 9780470405109
31.03.2013 20.07.2010
€ 79,95 £ 150,00
Mathematical Statistics for Economics and Business, Second Edition, provides a Inspired by the Encyclopedia of Statistical Sciences, Second Edition , this volume
comprehensive introduction to the principles of mathematical statistics which presents the tools and techniques that are essential for carrying out best practices in
underpin statistical analyses in the fields of economics, business, and econometrics. the modern business world The collection and analysis of quantitative data drives
The selection of topics in this textbook is designed to provide students with a some of the most important conclusions that are drawn in today's business world,
conceptual foundation that will facilitate a substantial understanding of statistical such as the preferences of a customer base, the quality of manufactured products,
applications in these subjects. This new edition has been updated throughout and the marketing of products, and the availability of financial resources. As a result, it is
now also includes a downloadable Student Answer Manual containing detailed essential for individuals working in this environment to have the knowledge and skills
solutions to half of the over 300 end-of-chapter problems. After introducing the to interpret and use statistical techniques in various scenarios. Addressing this need,
concepts of probability, random variables, and probability density functions, the Methods and Applications of Statistics in Business, Finance, and Management
author develops the key concepts of mathematical statistics, most notably: Science serves as a single, one-of-a-kind resource that guides readers through the
expectation, sampling, asymptotics, and the main families of distributions. The latter use of common statistical practices by presenting real-world applications from the
half of the book is then devoted to the theories of estimation and hypothesis testing fields of business, economics, finance, operations research, and management
with associated examples and problems that indicate their wide applicability in science.
economics and business.

Methods for Estimation and Inference in Microeconometrics Using Stata
Modern Econometrics
Stanislav Anatolyev A. Colin Cameron

9781439838242 9781597180733
01.06.2011 08.04.2010
£ 59,99 £ 57,99
Methods for Estimation and Inference in Modern Econometrics provides a A complete and up-to-date survey of microeconometric methods available in Stata,
comprehensive introduction to a wide range of emerging topics, such as generalized "Microeconometrics Using Stata, Revised Edition" is an outstanding introduction to
empirical likelihood estimation and alternative asymptotics under drifting microeconometrics and how to execute microeconometric research using Stata. It
parameterizations, which have not been discussed in detail outside of highly covers topics left out of most microeconometrics textbooks and omitted from basic
technical research papers. The book also addresses several problems often arising introductions to Stata. This revised edition has been updated to reflect the new
in the analysis of economic data, including weak identification, model features available in Stata 11 that are useful to microeconomists. Instead of using
misspecification, and possible nonstationarity. The book's appendix provides a mfx and the user-written margeff commands, the authors employ the new margins
review of some basic concepts and results from linear algebra, probability theory, command, emphasizing both marginal effects at the means and average marginal
and statistics that are used throughout the book. Topics covered include: Well- effects. They also replace the xi command with factor variables, which allow you to
established nonparametric and parametric approaches to estimation and specify indicator variables and interaction effects. Along with several new examples,
conventional (asymptotic and bootstrap) frameworks for statistical inference this edition presents the new gmm command for generalized method of moments
Estimation of models based on moment restrictions implied by economic theory, and nonlinear instrumental-variables estimation. In addition, the chapter on
including various method-of-moments estimators for unconditional and conditional maximum likelihood estimation incorporates enhancements made to ml in Stata 11.
moment restriction models, and asymptotic theory for correctly specified and
misspecified models.

www.abe.pl 9


Misconceptions of Risk: Common Modeling Online Auctions: Statistics in
Errors and Misconceptions Practice
Terje Aven Wolfgang Jank
Wiley Wiley

9780470683880 9780470475652
08.01.2010 19.08.2010
£ 70,00 £ 72,95
The risk discipline is young and there are a number of ideas, perspectives and Explore cutting-edge statistical methodologies for collecting, analyzing, and
conceptions of risk out there. A number of such common conceptions of risk are modeling online auction data Online auctions are an increasingly important
examined in the book, related to the risk concept, risk assessments, uncertainty marketplace, as the new mechanisms and formats underlying these auctions have
analyses, risk perception, the precautionary principle, risk management and decision enabled the capturing and recording of large amounts of bidding data that are used
making under uncertainty. The Author discusses these concepts, their strengths and to make important business decisions. As a result, new statistical ideas and
weaknesses, and concludes that they are often better judged as misconceptions of innovation are needed to understand bidders, sellers, and prices. Combining
risk than conceptions of risk. methodologies from the fields of statistics, data mining, information systems, and
economics, Modeling Online Auctions introduces a new approach to identifying
obstacles and asking new questions using online auction data. The authors draw
upon their extensive experience to introduce the latest methods for extracting new
knowledge from online auction data. Rather than approach the topic from the
traditional game-theoretic perspective, the book treats the online auction
mechanism as a data generator, outlining methods to collect, explore, model, and
forecast data.

Monte Carlo Methods and Models in Monte Carlo Simulation with
Finance and Insurance Applications to Finance
Ralf Korn Hui Wang

9781420076189 9781439858240
01.03.2010 20.06.2012
£ 62,99 £ 49,99
Offering a unique balance between applications and calculations, Monte Carlo Developed from the author's course on Monte Carlo simulation at Brown University,
Methods and Models in Finance and Insurance incorporates the application Monte Carlo Simulation with Applications to Finance provides a self-contained
background of finance and insurance with the theory and applications of Monte introduction to Monte Carlo methods in financial engineering. It is suitable for
Carlo methods. It presents recent methods and algorithms, including the multilevel advanced undergraduate and graduate students taking a one-semester course or
Monte Carlo method, the statistical Romberg method, and the Heath-Platen for practitioners in the financial industry. The author first presents the necessary
estimator, as well as recent financial and actuarial models, such as the Cheyette and mathematical tools for simulation, arbitrary free option pricing, and the basic
dynamic mortality models. The authors separately discuss Monte Carlo techniques, implementation of Monte Carlo schemes. He then describes variance reduction
stochastic process basics, and the theoretical background and intuition behind techniques, including control variates, stratification, conditioning, importance
financial and actuarial mathematics, before bringing the topics together to apply the sampling, and cross-entropy. The text concludes with stochastic calculus and the
Monte Carlo methods to areas of finance and insurance. This allows for the easy simulation of diffusion processes. Only requiring some familiarity with probability and
identification of standard Monte Carlo tools and for a detailed focus on the main statistics, the book keeps much of the mathematics at an informal level and avoids
principles of financial and insurance mathematics. The book describes high-level technical measure-theoretic jargon to provide a practical understanding of the
Monte Carlo methods for standard simulation and the simulation of stochastic basics. It includes a large number of examples as well as MATLAB(R) coding
processes with continuous and discontinuous paths. exercises that are designed in a progressive manner so that no prior experience with
MATLAB is needed.

Navigating Strategic Decisions Nonlinear Pricing Methods in
Quantitative Finance
John E. Triantis Julien Guyon

9781466585980 9781466570337
25.06.2013 16.08.2013
£ 63,99 £ 49,99
Based on forty years of experience and research, this book provides guidance on Collecting many methods that have previously been scattered in the literature, this
forecasting for strategic decision making. It includes methodology, tools, and book presents advanced techniques for solving high-dimensional nonlinear
models. It also explains how to apply sanity checks to existing forecasts to rankproblems. Designed for practitioners, it is one of the first books to discuss nonlinear
project valuations, identify project risks, and select the higher value creation Black-Scholes partial differential equations (PDEs). The authors explain regression
projects. The author discusses how to assess the feasibility of large projects, and dual methods for chooser options, the Monte Carlo approach for pricing the
analyze forecasting models to determine controllable levers, and create the uncertain volatility model and the uncertain lapse and mortality model, the Markovian
conditions needed for forecasts to materialize. projection/particle method to calibrate local stochastic volatility, hybrid models to
 Provides the most complete treatment of how to create the organization,
market vanilla options, and stochastic representations based on marked branching
diffusions.
processes, methods, and techniques required for analyzing and
forecasting for strategic decisions
 Serves as an essential reference book to strategic planning, new product
development, portfolio management, and business development groups

10 www.abe.pl


Numerical Methods in Finance with C++ Operational Risk Modelling and
Management
Maciej J. Capinski Claudio Franzetti

9780521177160 9781439844762
02.08.2012 18.10.2010
£ 24,00 £ 69,99
Driven by concrete computational problems in quantitative finance, this book In banking regulation, tools are needed to quantify risk and calculate the amount of
provides aspiring quant developers with the numerical techniques and programming capital reserve required to mitigate such risk. This book offers a complete model for
skills they need. The authors start from scratch, so the reader does not need any the quantification of so-called operational risks. It offers a detailed discussion on the
previous experience of C++. Beginning with straightforward option pricing on link between modeling approaches and management, which has been neglected in
binomial trees, the book gradually progresses towards more advanced topics, the literature, as well as the mathematical modeling of the loss distribution
including nonlinear solvers, Monte Carlo techniques for path-dependent derivative approach. With an emphasis on risk management and management fundamentals,
securities, finite difference methods for partial differential equations, and American the text presents a complete simulation model along with tested examples that can
option pricing by solving a linear complementarity problem. Further material, be replicated using R software. The author provides a broad view on managing risk
including solutions to all exercises and C++ code, is available online. The book is using this mathematical model.
ideal preparation for work as an entry-level quant programmer and it gives readers
the confidence to progress to more advanced skill sets involving C++ design
patterns as applied in finance.

Option Pricing and Estimation of Option Valuation: A First Course in
Financial Models with R Financial Mathematics
Stefano M. Iacus H. D. Junghenn

9780470745847 9781439889114
11.03.2011 13.01.2012
£ 62,50 £ 38,99
Presents inference and simulation of stochastic process in the field of model Option Valuation: A First Course in Financial Mathematics provides a straightforward
calibration for financial times series modelled by continuous time processes and introduction to the mathematics and models used in the valuation of financial
numerical option pricing. Introduces the bases of probability theory and goes on to derivatives. It examines the principles of option pricing in detail via standard binomial
explain how to model financial times series with continuous models, how to calibrate and stochastic calculus models. Developing the requisite mathematical background
them from discrete data and further covers option pricing with one or more as needed, the text presents an introduction to probability theory and stochastic
underlying assets based on these models. calculus suitable for undergraduate students in mathematics, economics, and
Analysis and implementation of models goes beyond the standard Black and finance. The first nine chapters of the book describe option valuation techniques in
Scholes framework and includes Markov switching models, Lévy models and other discrete time, focusing on the binomial model. The author shows how the binomial
models with jumps (e.g. the telegraph process); Topics other than option pricing model offers a practical method for pricing options using relatively elementary
include: volatility and covariation estimation, change point analysis, asymptotic mathematical tools. The binomial model also enables a clear, concrete exposition of
expansion and classification of financial time series from a statistical viewpoint. fundamental principles of finance, such as arbitrage and hedging, without the
The book features problems with solutions and examples. All the examples and R distraction of complex mathematical constructs. The remaining chapters illustrate
code are available as an additional R package, therefore all the examples can be the theory in continuous time, with an emphasis on the more mathematically
reproduced. sophisticated Black-Scholes-Merton model.

Quantitative Finance: A Simuation- Quantitative Finance: Object-Oriented
Based Introduction Using Excel Approach in C++
Matt Davison Erik Schlogl

9781439871683 9781584884798
16.11.2013 16.09.2013
£ 49,99 £ 49,99
Providing readers with more quantitative insight into markets and a better overview A textbook for students and a reference guide for professionals, this text builds a
of market structures, this book explains how the mathematical objects of finance foundation in the key methods and models of quantitative finance from the
relate to the business needs of markets. It takes a simulation approach to financial perspective of their implementation in C++. It introduces computational finance in a
market problems, which allows readers to understand concepts without becoming pragmatic manner, focusing on practical implementation. The author takes an object
bogged down by excessive equations. Each section describes the relevant financial -oriented approach that starts from simple building blocks for assembling more
or mathematical theory, an application of the theory in practice, and a spreadsheet complex and powerful models. The author expresses models and algorithms of the
to illustrate it. The text also includes a set of exercises, ranging from simple to industry-standard C++ language and includes working C++ source code on a CD-
complex. ROM that accompanies the book.

www.abe.pl 11

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