The reader is given: key concepts and methods to implement quantitatively-driven portfolio construction; knowledge of satellite investing, estimation error heuristics, scenario optimisation, mean variance investing, Bayesian methods, budgeting active risk, non- normality and multiple manager allocation; practical applications and accessible problem-solving skills; and quantitative analysis that is supported by extensive examples, tables and charts to help practitioners adopt the subject matter in their day-to-day work. The new chapters provide up-to-date information on portfolio optimisation, with differentiation of alpha and beta testing, covariance estimation, showing estimation error vs. model error and fundamental vs. statistical models. This book is recommended for practitioners including portfolio managers, consultants, strategists, marketers and quantitative analysts. It would also benefit final year undergraduates and MBAs looking to expand their knowledge beyond the mean-variance based solutions commonly taught in business schools.