Quantitative Corporate Finance

This textbook presents a comprehensive treatment of the legal arrangement of the corporation, the instruments and institutions through which capital can be raised, the management of the flow of funds through the individual firm, and the methods of dividing the risks and returns among the various contributors of funds. Now in its second edition, the book covers a wide range of topics in corporate finance, from time series modeling and regression analysis to multi-factor risk models and the Capital Asset Pricing Model. Guerard, Gultekin and Saxena build significantly on the first edition of the text, but retain the core chapters on cornerstone topics such as mergers and acquisitions, regulatory environments, bankruptcy and various other foundational concepts of corporate finance. New to the second edition are examinations of APT portfolio selection and time series modeling and forecasting through SAS, SCA and OxMetrics programming, FactSet fundamental data templates. This is intended to be a graduate-level textbook, and could be used as a primary text in upper level MBA and Financial Engineering courses, as well as a supplementary text for graduate courses in financial data analysis and financial investments.

The book addresses several problems in contemporary corporate finance: optimal capital structure, both in the US and in the G7 economies; the Capital Asset Pricing Model (CAPM) and the Arbitrage Pricing Model (APT) and the implications for the cost of capital; dividend policy; sales forecasting and pro forma statement analysis; leverage and bankruptcy; and mergers and acquisitions. It is designed to be used as an advanced graduate corporate financial management textbook.

An essential guide to corporate finance Understanding corporate finance is a necessity for financial practitioners who struggle every day to find the right balance between maximizing corporate value and reducing a firm's financial risk. Divided into two comprehensive parts, Mastering Corporate Finance Essentials presents the material by example, using an extended scenario involving a new business formation. In Part One, present and future value mathematics are introduced followed by a number of applications using the tools. In Part Two, statistics as applied to finance are examined, with detailed discussions of standard deviations, correlations, and how they impact diversification. Through theory and real-world examples this book provides a solid grounding in corporate finance Other titles by Stuart McCrary include: Mastering Financial Accounting Essentials, How to Create and Manage a Hedge Fund, and Hedge Fund Course Covers the essential elements of this field, from traditional capital budgeting concepts and methods of valuing investment projects under uncertainty to the importance of "real-options" in the decision-making process This reliable resource offers a hands-on approach to corporate finance that will allow you to gain a solid understanding of this discipline.

Quantitative Methods for Finance and Investments ensures that readers come away from reading it with a reasonable degree of comfort and proficiency in applying elementary mathematics to several types of financial analysis. All of the methodology in this book is geared toward the development, implementation, and analysis of financial models to solve financial problems.

An introduction to modern finance designed for students with strong quantitative skills.

This book draws readers’ attention to the financial aspects of daily life at a corporation by combining a robust mathematical setting and the explanation and derivation of the most popular models of the firm. Intended for third-year undergraduate students of business finance, quantitative finance, and financial mathematics, as well as first-year postgraduate students, it is based on the twin pillars of theory and analytics, which merge in a way that makes it easy for students to understand the exact meaning of the concepts and their representation and applicability in real-world contexts. Examples are given throughout the chapters in order to clarify the most intricate aspects; where needed, there are appendices at the end of chapters, offering additional mathematical insights into specific topics. Due to the recent growth in knowledge demand in the private sector, practitioners can also profit from the book as a bridge-builder between university and industry. Lastly, the book provides useful information for managers who want to deepen their understanding of risk management and come to recognize what may have been lacking in their own systems.

This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.

Presents a multitude of topics relevant to the quantitative finance community by combining the best of the theory with the usefulness of applications Written by accomplished teachers and researchers in the field, this book presents quantitative finance theory through applications to specific practical problems and comes with accompanying coding techniques in R and MATLAB, and some generic pseudo-algorithms to modern finance. It also offers over 300 examples and exercises that are appropriate for the beginning student as well as the practitioner in the field. The Quantitative Finance book is divided into four parts. Part One begins by providing readers with the theoretical backdrop needed from probability and stochastic processes. We also present some useful finance concepts used throughout the book. In part two of the book we present the classical Black-Scholes-Merton model in a uniquely accessible and understandable way. Implied volatility as well as local volatility surfaces are also discussed. Next, solutions to Partial Differential Equations (PDE), wavelets and Fourier transforms are presented. Several methodologies for pricing options namely, tree methods, finite difference method and Monte Carlo simulation methods are also discussed. We conclude this part with a discussion on stochastic differential equations (SDE’s). In the third part of this book, several new and advanced models from current literature such as general Lvy processes, nonlinear PDE's for stochastic volatility models in a transaction fee market, PDE's in a jump-diffusion with stochastic volatility models and factor and copulas models are discussed. In part four of the book, we conclude with a solid presentation of the typical topics in fixed income securities and derivatives. We discuss models for pricing bonds market, marketable securities, credit default swaps (CDS) and securitizations. Classroom-tested over a three-year period with the input of students and experienced practitioners Emphasizes the volatility of financial analyses and interpretations Weaves theory with application throughout the book Utilizes R and MATLAB software programs Presents pseudo-algorithms for readers who do not have access to any particular programming system Supplemented with extensive author-maintained web site that includes helpful teaching hints, data sets, software programs, and additional content Quantitative Finance is an ideal textbook for upper-undergraduate and beginning graduate students in statistics, financial engineering, quantitative finance, and mathematical finance programs. It will also appeal to practitioners in the same fields.