Quantitative Finance: Back to Basic Principles

The series of recent financial crises has thrown open the world of quantitative finance and financial modeling. The era of stochastic calculus is over and the time of Ito derivation as a unique tool of modelling is at an end. Today, quants need a broad modeling skill set – one that transcends mathematics to price and hedge financial products safely and effectively, but that also takes into account that we now live in a world of more frequent crises, fatter tail risk and the optimized search for alpha.

Quantitative Finance: Back to Basic Principles brings together new and proven methodologies from finance, physics and engineering, along with years of industry and academic experience to provide a cookbook of models for dealing with the challenges of today's markets. It begins by looking at approaches to vanilla and exotic options – including barrier, binary and American options. It then addresses the Black–Scholes conundrum – is it effective? The book then progresses to look at other pricing and valuation models commonly used in the industry, including terminal smile, stochastic volatility and more before confronting all the key challenges in model calibration and implementation.

The book also provides an original perspective on quantitative investment, providing recipes to help practitioners avoid the overfitting problem. It illustrates how risk neutral models can be effective tools for measuring the toxicity of investment strategies, and bridges the gap between stochastic calculus and statistics to illustrate an efficient framework for practical model development.

Written for quantitative practitioners in banks and asset managers, Quantitative Finance: Back to Basic Principles provides a toolkit and robust methodology which will enable practitioners to confront new and unforeseen pricing and valuation challenges. It offers new insights and methodologies for building models and enabling them to evolve over time, with a framework that adapts to different market regimes and different regulation.

About the Author

Adil Reghai (Paris, France) is head of Quantitative Research on Equity and Commodity Derivatives and Quantitative Investments at Natixis, a leading asset management company and one of the largest in the world. A graduate from Ecole Polytechnique (X92) and Ecole des Mines (P94), Paris, Adil was formerly in charge of quantitative research at Merrill Lynch, BNP Paribas and Calyon. He has participated in numerous quantitative finance conferences including Mathfinance and IQPC events, and lectures on the Financial Mathematics MSc in Nice. Adil's main research interests are local volatility, stochastic volatility, local correlation and hybrids, numerical techniques and applied finance.