Constructing Insurable Risk Portfolios offers a data-driven approach to devising risk retention programs that safeguard firms from a multitude of risks. Because firms face many risks, including fire damage to their buildings, liability from management misconduct, and external threats like cyber attacks, this book treats these potential liabilities as a "portfolio." Drawing inspiration from Markowitz portfolio theory, it leverages techniques from probability, statistics, and optimization to build algorithms that construct optimal risk insurable portfolios under budget constraints.

Features:

? Through engaging case studies and supporting statistical (R) code, readers will learn how to build optimal insurable risk portfolios.

? The book illustrates a frontier that depicts the trade-off between the uncertainty of a portfolio and the cost of risk transfer. This visual representation, mirroring familiar Markowitz investment tools, enables informed decision-making and easy adoption by risk advisors.

? The book lays the mathematical groundwork for constructing optimal insurable risk portfolios in an effective and aesthetically pleasing manner.

? For those interested in the detailed mathematical aspects of insurable risk portfolio optimization, comprehensive proofs and derivations are available in an online supplement.

This book equips students, academics, and practitioners with quantitative tools to analyze real-world risk portfolios. Additionally, it empowers financial analysts to provide data-driven insights that enhance their advisory roles for risk managers.