This book provides both practitioners and academics with a scientific approach to portfolio selection using Goal Programming, an approach which is capable as far as is possible of achieving a required set of preferences deemed appropriate by a decision maker. Goal Programming is perhaps the most widely-used approach in the field of multiple criteria decision-making that enables the decision maker to incorporate numerous variations of constraints and goals. The original portfolio selection problem, with risk and return optimisation, can be viewed as a case of Goal Programming with two objectives. Additional objectives representing other factors, such as liquidity, can be introduced for a more realistic approach to portfolio selection problems. This book comes in a time where scientific frameworks for investment decision-making are absolutely necessary, that is after the recent financial and economic crisis; where irrational decisions and a misuse of mathematical models had equally fed into the spiral of the financial crisis. The real-world decision problems are usually changeable, complex and resist treatment with conventional approaches. Therefore, the optimisation of a single objective subject to a set of rigid constraints is in most cases unrealistic, and that is why Goal Programming was introduced, in an attempt to eliminate or at least mitigate this shortcoming. Most mathematical models are based on very strong theoretical assumptions which are not entirely respected by markets in practice. In contrast, Goal Programming models are based on real-world cases where the most feasible solution is sought as opposed to an ideal simplified solution. Therefore, this book provides practitioners with a new and superior scientific framework for investment decision-making, while aiming to stimulate further research and development. Moreover, the book provides scientific approaches for portfolio selection with Goal Programming, which will provide added value for practitioners in complementing their financial expertise with a sound scientific decision-making framework.
This book provides both practitioners and academics with a scientific approach to portfolio selection using Goal Programming, an approach which is capable as far as is possible of achieving a required set of preferences deemed appropriate by a decision maker. Goal Programming is perhaps the most widely-used approach in the field of multiple criteria decision-making that enables the decision maker to incorporate numerous variations of constraints and goals. The original portfolio selection problem, with risk and return optimisation, can be viewed as a case of Goal Programming with two objectives. Additional objectives representing other factors, such as liquidity, can be introduced for a more realistic approach to portfolio selection problems. This book comes in a time where scientific frameworks for investment decision-making are absolutely necessary, that is after the recent financial and economic crisis; where irrational decisions and a misuse of mathematical models had equally fed into the spiral of the financial crisis. The real-world decision problems are usually changeable, complex and resist treatment with conventional approaches. Therefore, the optimisation of a single objective subject to a set of rigid constraints is in most cases unrealistic, and that is why Goal Programming was introduced, in an attempt to eliminate or at least mitigate this shortcoming. Most mathematical models are based on very strong theoretical assumptions which are not entirely respected by markets in practice. In contrast, Goal Programming models are based on real-world cases where the most feasible solution is sought as opposed to an ideal simplified solution. Therefore, this book provides practitioners with a new and superior scientific framework for investment decision-making, while aiming to stimulate further research and development. Moreover, the book provides scientific approaches for portfolio selection with Goal Programming, which will provide added value for practitioners in complementing their financial expertise with a sound scientific decision-making framework.
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