Supercharge options analytics and hedging using the power ofPython

Derivatives Analytics with Python shows you how toimplement market-consistent valuation and hedging approaches usingadvanced financial models, efficient numerical techniques, and thepowerful capabilities of the Python programming language. Thisunique...

About ten years ago we had the idea to begin a course in probability for students of electrical engineering. Prior to that electrical engineering graduate students at the Naval Postgraduate School specializing in communication, control, and signal processing were given a basic course in probability in another department and then began a course in...

Evolutionary Algorithms (EAs) are population-based, stochastic search algorithms that mimic natural evolution. Due to their ability to find excellent solutions for conventionally hard and dynamic problems within acceptable time, EAs have attracted interest from many researchers and practitioners in recent years. This book...

Neural networks have been a mainstay of artificial intelligence since its earliest days. Now, exciting new technologies such as deep learning and convolution are taking neural networks in bold new directions. In this book, we will demonstrate the neural networks in a variety of real-world tasks such as image recognition and data science. We...

This book provides a complete and comprehensive reference/guide to Pyomo (Python Optimization Modeling Objects) for both beginning and advanced modelers, including students at the undergraduate and graduate levels, academic researchers, and practitioners. The text illustrates the breadth of the modeling and analysis capabilities that are...

Student-Friendly Coverage of Probability, Statistical Methods, Simulation, and Modeling Tools
Incorporating feedback from instructors and researchers who used the previous edition, Probability and Statistics for Computer Scientists, Second Edition helps students understand general methods of stochastic...

Risk control, capital allocation, and realistic derivative pricing and hedging are critical concerns for major financial institutions and individual traders alike. Events from the collapse of Lehman Brothers to the Greek sovereign debt crisis demonstrate the urgent and abiding need for statistical tools...

The economic crisis of 2008 has shown that the capital markets need new theoretical and mathematical concepts to describe and price financial instruments. Focusing almost exclusively on interest rates and coupon bonds, this book does not employ stochastic calculus - the bedrock of the present day mathematical finance - for any of the derivations....

Scaling is a mathematical transformation that enlarges or diminishes objects. The technique is used in a variety of areas, including finance and image processing. This book is organized around the notions of scaling phenomena and scale invariance. The various stochastic models commonly used to describe scaling ? self-similarity, long-range...

Suitable for a first year graduate course, this textbook unites the applications of numerical mathematics and scientific computing to the practice of chemical engineering. Written in a pedagogic style, the book describes basic linear and nonlinear algebric systems all the way through to stochastic methods, Bayesian statistics and parameter...

"Professional Financial Computing Using Excel and VBA is an admirable exposition that bridges the theoretical underpinnings of financial engineering and its application which usually appears as a "black-box" software application. The book opens the black-box and reveals the architecture of risk-modeling and financial...

Can machines think like people? This question is the driving force behind Artificial Intelligence, but it is only the starting point of this ever-evolving, exciting discipline. AI uses different strategies to solve the complex problems that arise wherever computer technology is applied, from those areas pertaining to perception and adaptation...