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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.

Financial engineering --- Probabilities. --- Calculus. --- R (Computer program language) --- Mathematical models.

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This book provides the first practical guide to the function and implementation of algorithmic differentiation in finance. Written in a highly accessible way, Algorithmic Differentiation Explained will take readers through all the major applications of AD in the derivatives setting with a focus on implementation.  Algorithmic Differentiation (AD) has been popular in engineering and computer science, in areas such as fluid dynamics and data assimilation for many years.  Over the last decade, it has been increasingly (and successfully) applied to financial risk management, where it provides an efficient way to obtain financial instrument price derivatives with respect to the data inputs. Calculating derivatives exposure across a portfolio is no simple task.  It requires many complex calculations and a large amount of computer power, which in prohibitively expensive and can be time consuming.  Algorithmic differentiation techniques can be very successfully in computing Greeks and sensitivities of a portfolio with machine precision. Written by a leading practitioner who works and programmes AD, it offers a practical analysis of all the major applications of AD in the derivatives setting and guides the reader towards implementation.  Open source code of the examples is provided with the book, with which readers can experiment and perform their own test scenarios without writing the related code themselves.

Finance --- Mathematical models. --- Finance. --- Financial engineering. --- Economics, Mathematical. --- Financial Engineering. --- Quantitative Finance. --- Funding --- Funds --- Economics --- Currency question --- Computational finance --- Engineering, Financial --- Economics, Mathematical . --- Mathematical economics --- Econometrics --- Mathematics --- Methodology

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This book provides two important contributions to existing theories in the financial innovation literature. First, it extends the existing literature of innovation orientation to a completely new field and construct that is based on a religious imperative as a framework within which financial innovation is constrained. It explains how an innovation orientation in IFIs can be directed within religious rules, which indicates that innovation orientation in IFIs is a learning philosophy. Second, the book introduces and examines the plasticity of Shariah as a shared boundary object and its dynamic role in managing tension and conflicting values in the financial innovation process. Furthermore, building on the empirical results, the study illustrates the insights that each theoretical lens affords into practices of collaboration and develops a novel analytical framework for understanding religious orientation towards financial innovation. This practical contribution, of the developed framework, could form the basis for a standardised framework for the Islamic finance industry. The book concludes by noting the policy and managerial implications of its findings and provides directions for further research.

Finance. --- Business enterprises --- Banks and banking. --- Finance--History. --- Financial engineering. --- Financial Engineering. --- Business Finance. --- Banking. --- Financial History. --- Finance --- Religious aspects --- Islam. --- Business enterprises-Finance. --- History. --- Agricultural banks --- Banking --- Banking industry --- Commercial banks --- Depository institutions --- Financial institutions --- Money --- Computational finance --- Engineering, Financial --- Business enterprises—Finance. --- Finance—History.

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Analytical Finance is a comprehensive introduction to the financial engineering of equity and interest rate instruments for financial markets. Developed from notes from the author’s many years in quantitative risk management and modeling roles, and then for the Financial Engineering course at Malardalen University, it provides exhaustive coverage of vanilla and exotic mathematical finance applications for trading and risk management, combining rigorous theory with real market application. Volume I – Equity Derivatives Markets, Valuation and Risk Management. Coverage includes: The fundamentals of stochastic processes used in finance including the change of measure with Girsanov transformation and the fundamentals of probability throry. Discrete time models, such as various binomial models and numerical solutions to Partial Differential Equations (PDEs) Monte-Carlo simulations and Value-at-Risk (VaR) Continuous time models, such as Black–Scholes-Merton and similar with extensions Arbitrage theory in discrete and continuous time models Volume II – Interest Rate Derivative Markets, Valuation and Risk Management Coverage includes: Interest Rates including negative interest rates Valuation and model most kinds of IR instruments and their definitions. Bootstrapping; how to create an interest curve from prices of traded instruments. The multi curve framework and collateral discounting Difference of bootstrapping for trading and IR Risk Models and risk with positive and negative interest rates. Risk measures of IR instruments Option Adjusted Spread and embedded optionality. Pricing theory, calibration and stochastic processes of interest rates Numerical methods; Binomial and trinomial trees, PDEs (Crank–Nicholson), Newton–Raphson in 2 dimension. Black models, Normal models and Market models Pricing before and after the credit crises and the multiple curve framework. Valuation with collateral agreements, CVA, DVA and FVA.

Finance. --- Risk management. --- Capital market. --- Financial engineering. --- Economics, Mathematical. --- Financial Engineering. --- Quantitative Finance. --- Capital Markets. --- Risk Management. --- Derivative securities --- Interest rates --- Mathematical models. --- Insurance --- Management --- Capital markets --- Market, Capital --- Finance --- Financial institutions --- Loans --- Money market --- Securities --- Crowding out (Economics) --- Efficient market theory --- Funding --- Funds --- Economics --- Currency question --- Computational finance --- Engineering, Financial --- Economics, Mathematical . --- Mathematical economics --- Econometrics --- Mathematics --- Methodology

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This book aims to explore if and how securitisation changed financial intermediation and lending behaviour by reviewing the pre- and post-financial crisis theoretical and empirical literature. The book’s distinctive feature is bringing the growing post-crisis empirical evidence to the attention of a wider audience by critically appraising it against pre-crisis arguments. With its thought-provoking insights, this book is of particular interest for students, practitioners and academics.

Asset-backed financing. --- Asset-backed securities --- Asset-based financing --- Asset securitization --- Securitization, Asset --- Finance. --- Finance, Public. --- Investment banking. --- Securities. --- Risk management. --- Financial engineering. --- Investments and Securities. --- Risk Management. --- Financial Engineering. --- Public Finance. --- Corporations --- Covered bonds --- Finance --- Computational finance --- Engineering, Financial --- Insurance --- Management --- Cameralistics --- Public finance --- Currency question --- Banks and banking, Investment --- Investment banks --- Financial institutions --- Securities --- Blue sky laws --- Capitalization (Finance) --- Investment securities --- Portfolio --- Scrip --- Securities law --- Underwriting --- Investments --- Investment banking --- Law and legislation --- Public finances