Financial Risk Management | Financial Risk Management, LLC

Building Quantitative Finance Applications with R

Tue, 09 Jan 2024 00:00:00 +0000

Building Quantitative Finance Applications with R, is offered with two goals: First, assist financial analysts in developing their own unique quantitative financial models. Second, aid in tooling these analysts to express their models with the R computer language. Both goals are now easily within reach of the aspiring financial analyst. Every effort is made here to keep the R programming elementary .

Thus Building Quantitative Finance Applications with R is written to assist financial analysts to quickly learn to express their ideas in the R computer language.

Also quantitative finance is now widely applied in a variety of career fields. Quantitative financial analysts are now needed in a variety of different arenas. The ability for these analysts to express their own ideas in R is a highly valued skill.

Finance is a social science. Thus, as ideas about how certain financial products should be valued and managed evolve, the actual value and risk properties also change. Therefore, there will never be a “theory of everything” in finance. More likely, we should be surprised if there ever appears a “theory of anything” that endures for very long.

Because of the dynamic nature of financial markets, financial analysts need to be able to rapidly adapt their valuation and risk management models to changing times. Rather than rely on faulty communication between analysts and professional programmers, financial analysts can express their ideas in prototype R code. This ability dramatically reduces errors and allows financial analysts greater precision in expressing their ideas.

Building Quantitative Finance Applications with R is written for college students and entry-level financial analysts. No prior knowledge of programming is assumed. As with any language, having access to multiple sources when learning technical material is highly recommended. Therefore, it is assumed that you have access to several introductory R books or similar web-based materials.

There are several other books linking quantitative finance with computer programming. The approach taken here is distinctly different. Rather than present state-of-the-art programming techniques, we use only elementary R. Rarely do financial analysts want to become professional programmers. Rather, they want to rapidly learn how to express their unique analytical ideas in a form that the computer can run. Therefore, we focus on the minimal set of computer programming tools necessary to perform this task.

Although the book form is undecided, the expected publication date is early 2024. A draft version of each chapter, complete with R code, is freely available at http://robertebrooks.org/project/buildiingqfawr/. Further, there is a YouTube Channel dedicated to presenting this material even though the book is not finished. Please consider subscribing (and liking) @FRMHelpForYou. Channel direct link: https://www.youtube.com/@FRMHelpForYou

Foundations of Pricing Financial Derivatives

Mon, 08 Jan 2024 00:00:00 +0000

Foundations of Pricing Financial Derivatives is being written as a PhD-level book focusing on one of the most technical subjects in finance—derivative pricing theory. While the majority of finance faculty and PhD students will not specialize in derivatives, there is no doubt that a solid understanding of derivative pricing theory is an important element of doctoral level education in finance.

Derivative pricing theory, in particular the Black–Scholes–Merton (1973) model, has had a tremendous impact on finance. It has provided a framework for understanding not only standard derivatives, such as options, forwards, futures, and swaps, but it has also shown us that derivatives can explain many other topics and relationships in finance, such as callable bonds, convertible bonds, credit risk, and corporate capital structure. The impact of derivative pricing theory has been so great that Nobel Prizes were awarded in 1995 to Myron Scholes and Robert Merton with special recognition to the late Fischer Black for work on this subject. Yet, with the increasing need for students to take so many courses in econometrics and statistics, there is often little room in a doctoral program for such a course.

Foundations of Pricing Financial Derivatives will introduce the vast financial derivatives markets to PhD students in hopes that it will stimulate your interest in research related to financial derivatives as well as aid in your future research agenda, even if your agenda is not explicitly financial derivatives.

The expected publication date is in early 2021.

Introduction to Derivatives and Risk Management

Fri, 05 Jan 2024 00:00:02 +0000

The book delivers detailed coverage of options, futures, forwards, swaps, and risk management as well as a balanced introduction to pricing, trading, and strategy. New “Taking Risk in Life” features illustrate the application of risk management in real-world financial decisions. In addition, the financial information throughout the Tenth Edition reflects the most recent changes in the derivatives market–one of the most volatile sectors in the financial world.

Building Financial Risk Management Applications with C++

Mon, 01 May 2023 00:00:00 +0000

The purpose of this book is not to provide state-of-the-art C++ programming techniques. The purpose of this book is also not to provide state-of-the-art financial risk management techniques. Financial quantitative analysts (Quants) often lack the foundational understanding of financial risk management as well as basic C++ programming. Many quants have studied the graduate level financial derivatives textbooks and passed various financial risk management-type examinations. They have not, however, seen how to actually deploy these ideas in practice. Thus, I seek to fill this void by providing a launching pad where quantitative finance professionals can connect the dots between abstract theoretical finance concepts and prototype code that could be used to implement various financial risk management ideas.

The purpose here is to provide as simple an approach as possible to enable financial analysts to develop prototype implementation C++ code of their financial risk management ideas. Dynamic memory allocation, abstract data types, container classes, and so forth are left to the computer programming professionals. The objective of this book is to provide assistance for quantitative finance professionals who wish to implement their emerging financial risk management ideas with C++. We focus on introducing financial risk management with C++ because many of the modern financial risk management concepts require some form of computer program to successfully implement.

Computer programming is a unique, disciplined implementation of ideas. In this chapter, several reasons why financial analysts should learn a computer language are reviewed. In particular, the case will be made for C++ and it will be briefly introduced. Finally, the autonomous (compiler independent) and heteronomous (compiler dependent) approaches to teaching C++ are explored. This material takes the atypical heteronomous approach while remaining sympathetic to those learners who prefer the more popular autonomous approach.