Every financial professional wants and needs an advantage. A firm foundation in advanced mathematics can translate into dramatic advantages to professionals willing to obtain it. Many are not-and that is the advantage these books offer the astute reader.
Every financial professional wants and needs an advantage. A firm foundation in advanced mathematics can translate into dramatic advantages to professionals willing to obtain it. Many are not-and that is the advantage these books offer the astute reader.
Robert R. Reitano is Professor of the Practice in Finance at the Brandeis International Business School where he specializes in risk management and quantitative finance. He previously served as MSF Program Director, and Senior Academic Director. He has a Ph.D. in Mathematics from MIT, is a Fellow of the Society of Actuaries, and a Chartered Enterprise Risk Analyst. Dr. Reitano consults in investment strategy and asset/liability risk management, and previously had a 29-year career at John Hancock/Manulife in investment strategy and asset/liability management, advancing to Executive Vice President & Chief Investment Strategist. His research papers have appeared in a number of journals and have won an Annual Prize of the Society of Actuaries and two F.M. Redington Prizes of the Investment Section of the Society of the Actuaries. Dr. Reitano serves on various not-for-profit boards and investment committees.
Inhaltsangabe
Preface. Introduction. 1. Probability Spaces. 2. Limit Theorems on Measurable Sets. 3. Random Variables and Distribution Functions. 4. Samples of Random Variables. 5. Limit Theorems for Random Variable Sequences. 6. Distribution Functions and Borel Measures. 7. Copulas and Sklar's Theorem. 8. Weak Convergence of Distribution Functions. 9. Estimating Tail Events. References. Index.
Preface. Introduction. 1. Probability Spaces. 2. Limit Theorems on Measurable Sets. 3. Random Variables and Distribution Functions. 4. Samples of Random Variables. 5. Limit Theorems for Random Variable Sequences. 6. Distribution Functions and Borel Measures. 7. Copulas and Sklar's Theorem. 8. Weak Convergence of Distribution Functions. 9. Estimating Tail Events. References. Index.
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