FINANCIAL ENGINEERING Financial engineering is poised for a great shift in the years ahead. Everyone from investors and borrowers to regulators and legislators will need to determine what works, what doesn't, and where to go from here. Financial Engineering —part of the Robert W. Kolb Series in Finance—has been designed to help you do just this. Comprised of contributed chapters by distinguished experts from industry and academia, this reliable resource will help you focus on established activities in the field, developing trends and changes, as well as areas of opportunity. Divided into five comprehensive parts, Financial Engineering begins with an informative overview of the discipline, chronicling its complete history and profiling potential career paths. From here, Part II quickly moves on to discuss the evolution of financial engineering in major markets—fixed income, foreign exchange, equities, commodities and credit—and offers important commentary on what has worked and what will change. Part III then examines a number of recent innovative applications of financial engineering that have made news over the past decade—such as the advent of securitized and structured products and highly quantitative trading strategies for both equities and fixed income. Thoughts on how risk management might be retooled to reflect what has been learned as a result of the recent financial crisis are also included. Part IV of the book is devoted entirely to case studies that present valuable lessons for active practitioners and academics. Several of the cases explore the risk that has instigated losses across multiple markets, including the global credit crisis. You'll gain in-depth insights from cases such as Countrywide, Société Générale, Barings, Long-Term Capital Management, the Florida Local Government Investment Pool, AIG, Merrill Lynch, and many more. The demand for specific and enterprise risk managers who can think outside the box will be substantial during this decade. Much of Part V presents new ways to be successful in an era that demands innovation on both sides of the balance sheet. Chapters that touch upon this essential topic include Musings About Hedging; Operational Risk; and The No-Arbitrage Condition in Financial Its Use and Mis-Use. This book is complemented by a companion website that includes details from the editors' survey of financial engineering programs around the globe, along with a glossary of key terms from the book. This practical guide puts financial engineering in perspective, and will give you a better idea of how it can be effectively utilized in real- world situations.
One of the critics of financial engineering is Nassim Taleb, a professor of financial engineering at Polytechnic Institute of New York University who argues that it replaces common sense and leads to disaster. A series of economic collapses have led many governments to argue a return to "real" engineering from financial engineering.
Many other authors have identified specific problems in financial engineering that caused catastrophes: Aaron Brown named confusion between quants and regulators over the meaning of "capital", Felix Salmon gently pointed to the Gaussian copula, Ian Stewart criticized the Black-Scholes formula, Pablo Triana dislikes value at risk and Scott Patterson accused quantitative traders and later high-frequency traders.
A gentler criticism came from Emanuel Derman who heads a financial engineering degree program at Columbia University. He blames over-reliance on models for financial problems.
The financial innovation often associated with financial engineers was mocked by former chairman of the Federal Reserve Paul Volcker in 2009 when he said it was a code word for risky securities, that brought no benefits to society. For most people, he said, the advent of the ATM was more crucial than any asset-backed bond.
A bit uneven, as might be expected from a book of chapters from a variety of authors. Good overview, but you'll need other resources to actually understand and work with a topic.
The first appendix, which focuses on using Excel for complex analytics, struck me as a bit odd. As someone who works in finance, Excel is useful for ad hoc analyses, but if you were actually implementing a model to use in a production environment, use a real programming language, or a specialized math/stat environment (e.g., Mathematica, MatLab, R)...anything you can do actual testing/QA on. Stories of Excel issues leading to very public and erroneous model conclusions are not uncommon. Cells and VB macros are nooks and crannies in which errors can hide.
A global world in transition creates both opportunities and challenges for financial engineers to adapt theoretical and financial constructs into profitable and innovative opportunities by creating innovative, custom-designed instruments in the marketplace. This book explains how sophisticated modelling and information technology now dominate the financial world.
It sums up why so many theories and the practice of finance are challenged today by complex financial and global systems and by dynamically changing regulatory environments and politics.