Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
759
result(s) for
"Financial engineering Mathematical models."
Sort by:
Applied probabilistic calculus for financial engineering : an introduction using R
Illustrates how R may be used successfully to solve problems in quantitative finance
Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R provides R recipes for asset allocation and portfolio optimization problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related to asset allocation and portfolio optimization with R codes illustrated for various examples. This clear and concise book covers financial engineering, using R in data analysis, and univariate, bivariate, and multivariate data analysis. It examines probabilistic calculus for modeling financial engineering—walking the reader through building an effective financial model from the Geometric Brownian Motion (GBM) Model via probabilistic calculus, while also covering Ito Calculus. Classical mathematical models in financial engineering and modern portfolio theory are discussed—along with the Two Mutual Fund Theorem and The Sharpe Ratio. The book also looks at R as a calculator and using R in data analysis in financial engineering. Additionally, it covers asset allocation using R, financial risk modeling and portfolio optimization using R, global and local optimal values, locating functional maxima and minima, and portfolio optimization by performance analytics in CRAN.
* Covers optimization methodologies in probabilistic calculus for financial engineering
* Answers the question: What does a \"Random Walk\" Financial Theory look like?
* Covers the GBM Model and the Random Walk Model
* Examines modern theories of portfolio optimization, including The Markowitz Model of Modern Portfolio Theory (MPT), The Black-Litterman Model, and The Black-Scholes Option Pricing Model
Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R s an ideal reference for professionals and students in economics, econometrics, and finance, as well as for financial investment quants and financial engineers.
eBook
Applied Probabilistic Calculus for Assets Allocation and Portfolio Optimization in Financial Engineering Using R
Illustrates how R may be used successfully to solve problems in quantitative finance Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R provides R recipes for asset allocation and portfolio optimization problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related to asset allocation and portfolio optimization with R codes illustrated for various examples. This clear and concise book covers financial engineering, using R in data analysis, and univariate, bivariate, and multivariate data analysis. It examines probabilistic calculus for modeling financial engineering-walking the reader through building an effective financial model from GBM via probabilistic calculus, while also covering Ito Calculus. Classical mathematical models in financial engineering and modern portfolio theory are discussed-along with the Two Mutual Fund Theorem and The Sharpe Ratio. The book also looks at R as a calculator and using R in data analysis in financial engineering. Additionally, it covers asset allocation using R, financial risk modeling and portfolio optimization using R, global and local optimal values, locating functional maxima and minima, and portfolio optimization by performance analytics in CRAN. Covers optimization methodologies in probabilistic calculus for financial engineering Answers the question: What does a \"Random Walk\" Financial Theory look like? Covers The Geometric Brownian Motion (GBM) Model and the Random Walk Model Examines modern theories of portfolio optimization, including The Markowitz Model of Modern Portfolio Theory (MPT), The Black-Litterman Model, and The Black-Scholes Option Pricing Model Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R is an ideal reference for professionals and students in economics, econometrics, and finance, as well as for financial investment quants and financial engineers.
eBook
New Trends in Financial Engineering
Financial engineering is defined as the application of mathematical methods to the solution of problems in finance. The recent financial crisis raised many challenges for financial engineers: not only were financially engineered products such as collateralized debt obligations and credit default swaps implicated in causing the crisis, but the risk management techniques developed by financial engineers appeared to fail when they were most desperately needed. This book is the first in a series describing research by a multidisciplinary team of economists, mathematicians and control theorists exploring new research directions in financial engineering. It is broadly divided into three parts. The first part of the book reviews recent developments of real options; an application of the theory of financial options to capital investments with the emphasis on flexibility. Topics covered include the technique of variational inequalities, the use of forward and backward stochastic differential equations and the application of a real option approach to a consumption and portfolio selection problem. The second part of the book presents new topics, including simultaneous control of dividend payments and risk management, risk measures and non-linear probability models and a survey of recent studies on market microstructure. The last part of the volume proposes a new perspective. The availability and success of mathematical tools has attracted many talented people to the financial services industry. This examination of the way in which they are approaching current and future challenges will be of interest to all those working in the field of financial engineering.
eBook
Financial Engineering and Computation
Students and professionals intending to work in any area of finance must master not only advanced concepts and mathematical models but also learn how to implement these models computationally. This comprehensive text, first published in 2002, combines the theory and mathematics behind financial engineering with an emphasis on computation, in keeping with the way financial engineering is practised in capital markets. Unlike most books on investments, financial engineering, or derivative securities, the book starts from very basic ideas in finance and gradually builds up the theory. It offers a thorough grounding in the subject for MBAs in finance, students of engineering and sciences who are pursuing a career in finance, researchers in computational finance, system analysts, and financial engineers. Along with the theory, the author presents numerous algorithms for pricing, risk management, and portfolio management. The emphasis is on pricing financial and derivative securities: bonds, options, futures, forwards, interest rate derivatives, mortgage-backed securities, bonds with embedded options, and more.
eBook
Indifference pricing
This is the first book about the emerging field of utility indifference pricing for valuing derivatives in incomplete markets. René Carmona brings together a who's who of leading experts in the field to provide the definitive introduction for students, scholars, and researchers. Until recently, financial mathematicians and engineers developed pricing and hedging procedures that assumed complete markets. But markets are generally incomplete, and it may be impossible to hedge against all sources of randomness.Indifference Pricingoffers cutting-edge procedures developed under more realistic market assumptions.
The book begins by introducing the concept of indifference pricing in the simplest possible models of discrete time and finite state spaces where duality theory can be exploited readily. It moves into a more technical discussion of utility indifference pricing for diffusion models, and then addresses problems of optimal design of derivatives by extending the indifference pricing paradigm beyond the realm of utility functions into the realm of dynamic risk measures. Focus then turns to the applications, including portfolio optimization, the pricing of defaultable securities, and weather and commodity derivatives. The book features original mathematical results and an extensive bibliography and indexes.
In addition to the editor, the contributors are Pauline Barrieu, Tomasz R. Bielecki, Nicole El Karoui, Robert J. Elliott, Said Hamadène, Vicky Henderson, David Hobson, Aytac Ilhan, Monique Jeanblanc, Mattias Jonsson, Anis Matoussi, Marek Musiela, Ronnie Sircar, John van der Hoek, and Thaleia Zariphopoulou.
The first book on utility indifference pricingExplains the fundamentals of indifference pricing, from simple models to the most technical onesGoes beyond utility functions to analyze optimal risk transfer and the theory of dynamic risk measuresCovers non-Markovian and partially observed models and applications to portfolio optimization, defaultable securities, static and quadratic hedging, weather derivatives, and commoditiesIncludes extensive bibliography and indexesProvides essential reading for PhD students, researchers, and professionals
eBook
Zero lower bound term structure modeling : a practitioner's guide
Nominal yields on government debt in several countries have fallen very near their zero lower bound (ZLB), causing a liquidity trap and limiting the capacity to stimulate economic growth. This book provides a comprehensive reference to ZLB structure modeling in an applied setting.
eBook