|
Showing 1 - 7 of
7 matches in All Departments
The definitive guide to fixed income securities-updated and revised
with everything you need to succeed in today's market For nearly 40
years, The Handbook of Fixed Income Securities has been providing
comprehensive, current, reliable information on everything
investors like you need to stay on top of the market and ahead of
the curve. The fixed income market has changed dramatically in the
past decade. This updated classic brings you fully up to date for a
much-changed world of finance, where central banks play a bigger
role, interest is low (and sometimes even in negative territory),
regulations are more complex, and new types of securities have been
created. Brand-new chapters cover: Relative value trades Muni
analytics Financial data science Building and maintaining a bond
portfolio Factor investing Relative value trades Smart beta fixed
income Infrastructure and green bonds Sovereign bond markets One of
the world's leading experts on fixed income securities, Frank
Fabozzi has gathered a peerless team of global experts who provide
the newest and best techniques for winning in today's markets.
Fixed Income Securities, Ninth Edition is a matchless, one-stop
resource for all your professional needs.
This book covers the method of metric distances and its application
in probability theory and other fields. The method is fundamental
in the study of limit theorems and generally in assessing the
quality of approximations to a given probabilistic model. The
method of metric distances is developed to study stability problems
and reduces to the selection of an ideal or the most appropriate
metric for the problem under consideration and a comparison of
probability metrics. After describing the basic structure of
probability metrics and providing an analysis of the topologies in
the space of probability measures generated by different types of
probability metrics, the authors study stability problems by
providing a characterization of the ideal metrics for a given
problem and investigating the main relationships between different
types of probability metrics. The presentation is provided in a
general form, although specific cases are considered as they arise
in the process of finding supplementary bounds or in applications
to important special cases. Svetlozar T. Rachev is the Frey Family
Foundation Chair of Quantitative Finance, Department of Applied
Mathematics and Statistics, SUNY-Stony Brook and Chief Scientist of
Finanlytica, USA. Lev B. Klebanov is a Professor in the Department
of Probability and Mathematical Statistics, Charles University,
Prague, Czech Republic. Stoyan V. Stoyanov is a Professor at EDHEC
Business School and Head of Research, EDHEC-Risk Institute-Asia
(Singapore). Frank J. Fabozzi is a Professor at EDHEC Business
School. (USA)
A core text for one semester courses in Financial Institutions and
Markets. A comprehensive exploration of the world's financial
markets and institutions. Foundations of Financial Markets and
Institutions, offers a comprehensive exploration of the
revolutionary developments occurring in the world's financial
markets and institutions -i.e., innovation, globalization, and
deregulation-with a focus on the actual practices of financial
institutions, investors, and financial instruments. This edition
incorporates and addresses the vast amount of changes that have
recently occurred in financial institutions and markets around the
world.
A contributed handbook on the complexities of portfolio management
that includes the most up-to-date findings from leading
practitioners in the fixed income securities market.
Fractional Calculus and Fractional Processes with Applications to
Financial Economics presents the theory and application of
fractional calculus and fractional processes to financial data.
Fractional calculus dates back to 1695 when Gottfried Wilhelm
Leibniz first suggested the possibility of fractional derivatives.
Research on fractional calculus started in full earnest in the
second half of the twentieth century. The fractional paradigm
applies not only to calculus, but also to stochastic processes,
used in many applications in financial economics such as modelling
volatility, interest rates, and modelling high-frequency data. The
key features of fractional processes that make them interesting are
long-range memory, path-dependence, non-Markovian properties,
self-similarity, fractal paths, and anomalous diffusion behaviour.
In this book, the authors discuss how fractional calculus and
fractional processes are used in financial modelling and finance
economic theory. It provides a practical guide that can be useful
for students, researchers, and quantitative asset and risk managers
interested in applying fractional calculus and fractional processes
to asset pricing, financial time-series analysis, stochastic
volatility modelling, and portfolio optimization.
This book covers the method of metric distances and its application
in probability theory and other fields. The method is fundamental
in the study of limit theorems and generally in assessing the
quality of approximations to a given probabilistic model. The
method of metric distances is developed to study stability problems
and reduces to the selection of an ideal or the most appropriate
metric for the problem under consideration and a comparison of
probability metrics. After describing the basic structure of
probability metrics and providing an analysis of the topologies in
the space of probability measures generated by different types of
probability metrics, the authors study stability problems by
providing a characterization of the ideal metrics for a given
problem and investigating the main relationships between different
types of probability metrics. The presentation is provided in a
general form, although specific cases are considered as they arise
in the process of finding supplementary bounds or in applications
to important special cases. Svetlozar T. Rachev is the Frey Family
Foundation Chair of Quantitative Finance, Department of Applied
Mathematics and Statistics, SUNY-Stony Brook and Chief Scientist of
Finanlytica, USA. Lev B. Klebanov is a Professor in the Department
of Probability and Mathematical Statistics, Charles University,
Prague, Czech Republic. Stoyan V. Stoyanov is a Professor at EDHEC
Business School and Head of Research, EDHEC-Risk Institute-Asia
(Singapore). Frank J. Fabozzi is a Professor at EDHEC Business
School. (USA)
The brand-new edition of this classic guide for high-level
investors covers the latest tools and techniques for dealing with
all aspects of fixed-income portfolio management Fixed Income
Mathematics is known around the world as the leading guide to
understanding the concepts and evaluative methodologies for bonds,
mortgage-backed securities, asset-backed securities, and other
fixed income instruments-and the fifth edition gets you up to date
on the newest analytical frameworks. Fixed Income Mathematics
begins with basic concepts of the mathematics of finance, then
systematically builds on them to reveal state-of-the-art
methodologies for evaluating them and managing fixed-income
portfolios. Concepts are illustrated with numerical examples and
graphs, and you need only a basic knowledge of elementary algebra
to understand them. This new edition includes numerous entirely new
chapters-Risk-Adjusted Returns, Empirical Duration, Analysis of
Floating-Rate Securities, Holdings-Based Return Attribution
Analysis, Returns-Based Style Attribution Analysis, Measuring Bond
Liquidity, Descriptive Measures, and Machine Learning-and provides
substantially revised chapters on: Interest rate modeling
Probability theory Optimization models and applications to bond
portfolio management Historical return measures Measuring
historical return volatility The concepts and methodologies for
evaluating fixed income securities have changed dramatically over
the past 15 years. This edition explains the numbers behind these
changes and provides the knowledge you need to consistently control
both the cost and risk of investing in debt.
|
You may like...
Loot
Nadine Gordimer
Paperback
(2)
R205
R168
Discovery Miles 1 680
|