Information Security Science: Measuring the Vulnerability to Data Compromises provides the scientific background and analytic techniques to understand and measure the risk associated with information security threats. This is not a traditional IT security book since it includes methods of information compromise that are not typically...

• Describes the key mathematical models used for price equity, currency, interest rates, and credit derivatives
• The complex models are explained step-by-step along with a flow chart of every...

Driven by concrete computational problems in quantitative finance, this book provides aspiring quant developers with the numerical techniques and programming skills they need. The authors start from scratch, so the reader does not need any previous experience of C++. Beginning with straightforward option pricing on binomial trees, the book...

This is the first book to show the capabilities of Microsoft Excel in teaching marketing statistics effectively. It is a step-by-step exercise-driven guide for students and practitioners who need to master Excel to solve practical marketing problems. If understanding statistics isn’t your strongest suit, you are not especially...

• Harness the ability to build algorithms for unsupervised data using deep learning concepts with R
• Master the common problems faced such as overfitting of data, anomalous datasets, image recognition, and performance tuning while building the models
• Build models relating to neural...

Financial engineers have access to enormous quantities of data but need powerful methods for extracting quantitative information, particularly about volatility and risks. Key features of this textbook are: illustration of concepts with financial markets and economic data, R Labs with real-data exercises, and integration of graphical and...