Post-Modern Portfolio Theory Comes of Age

Rom, Brian M.; Ferguson, Kathleen W.

doi:10.3905/joi.2.4.27

Cited by 31 publications

(14 citation statements)

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“…The problem discussed in this paper differs from the ones in Markowitz's (Markovitz, 1952) modern portfolio theory based on mean-variance analysis, and also from those discussed in post-modern portfolio theory (Rom and Ferguson, 1993). It has the form of the decision-making multi-objective optimization problem, specifically, the two-criterion 0-1 knapsack optimization problem with constraints.…”

Section: Introductionmentioning

confidence: 96%

Multi-objective Optimization Algorithms with the Island Metaheuristic for Effective Project Management Problem Solving

Brester¹,

Ryzhikov²,

Semenkin³

2017

Organizacija

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Background and Purpose:In every organization, project management raises many different decision-making problems, a large proportion of which can be efficiently solved using specific decision-making support systems. Yet such kinds of problems are always a challenge since there is no time-efficient or computationally efficient algorithm to solve them as a result of their complexity. In this study, we consider the problem of optimal financial investment. In our solution, we take into account the following organizational resource and project characteristics: profits, costs and risks. Design/Methodology/Approach: The decision-making problem is reduced to a multi-criteria 0-1 knapsack problem. This implies that we need to find a non-dominated set of alternative solutions, which are a trade-off between maximizing incomes and minimizing risks. At the same time, alternatives must satisfy constraints. This leads to a constrained two-criterion optimization problem in the Boolean space. To cope with the peculiarities and high complexity of the problem, evolution-based algorithms with an island meta-heuristic are applied as an alternative to conventional techniques. Results: The problem in hand was reduced to a two-criterion unconstrained extreme problem and solved with different evolution-based multi-objective optimization heuristics. Next, we applied a proposed meta-heuristic combining the particular algorithms and causing their interaction in a cooperative and collaborative way. The obtained results showed that the island heuristic outperformed the original ones based on the values of a specific metric, thus showing the representativeness of Pareto front approximations. Having more representative approximations, decision-makers have more alternative project portfolios corresponding to different risk and profit estimations. Since these criteria are conflicting, when choosing an alternative with an estimated high profit, decision-makers follow a strategy with an estimated high risk and vice versa. Conclusion: In the present paper, the project portfolio decision-making problem was reduced to a 0-1 knapsack constrained multi-objective optimization problem. The algorithm investigation confirms that the use of the island meta-heuristic significantly improves the performance of genetic algorithms, thereby providing an efficient tool for Financial Responsibility Centres Management.Keywords: 0-1 multi-objective constrained knapsack problem; project management portfolio problem; multi-objective evolution-based optimization algorithms; collaborative and cooperative meta-heuristics

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Section: Introductionmentioning

confidence: 96%

Multi-objective Optimization Algorithms with the Island Metaheuristic for Effective Project Management Problem Solving

Brester¹,

Ryzhikov²,

Semenkin³

2017

Organizacija

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“…Nesta metodologia, o alvo de estudo passa a ser as caudas de perdas (ou tails) das distribuições dos retornos. Esses novos estudos também são chamados de Pós-Moderna Teoria do Portfólio (sigla PMPT, em inglês), considerada uma extensão da MPT (Rom & Ferguson, 1994).…”

Section: Introductionunclassified

Análise comparativa de distintas métricas de risco na composição de um fundo de fundos de investimento imobiliário

Lovatto¹,

Henrique

Lima

2017

Rev. contab. organ.

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O propósito central deste estudo é analisar a complementaridade dos resultados de diferentes métricas de risco na composição de um Fundo de FIIs. A partir da revisão de literatura, optou-se pela adoção das métricas de risco variância e Conditional Value-at-Risk, desenvolvidas nos estudos de Markowitz (1952) e Rockafellar e Uryasev (2000, 2002), respectivamente. O estudo abrangeu uma amostra de 30 FIIs listados em bolsa de valores no âmbito da BMF&BOVESPA com retornos diários entre Julho de 2013 e Julho de 2015. Como metodologia, empregou-se modelagem e simulação computacional de carteiras teóricas para minimização do risco não-sistemático, submetendo-as a restrições de acordo com perfis de risco e instruções regulatórias. A principal constatação é de que as diferentes métricas produziram diferentes resultados nos portfólios de menor nível de risco. Observou-se, adicionalmente, que a métrica variância subestimou a probabilidade de perdas extremas.

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“…Sorbonne -2014.94 3 Most of the proposed refinements fit in either of the following two categories:  Replacing variance by more sophisticated risk measures (Rockafellar and Uryasev [2000], Sornette & al. [2000], Rom and Ferguson [1994]). …”

Section: Introductionmentioning

confidence: 99%

Extreme Risk, Excess Return and Leverage: The LP Formula

Marois¹,

Mikhalevsky²,

Douady

2014

SSRN Journal

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The LP formula is based upon the substitution of the exogenous risk aversion hypothesis by a credit equilibrium hypothesis. This leads to a trade-off between expected blue-sky return -the expected return excluding default scenarios -and extreme risk estimated from scenarios leading to default. An empirical study on the past 90 years shows that this trade-off curve is almost identical across asset classes. In equilibrium, an asset expected blue-sky return is proportional to its contribution to extreme risk. Assuming normal returns, we obtain CAPM as a sub-case of the LP relation. This relationship makes extreme risk underestimation a strong driver of asset price bubbles.

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Post-Modern Portfolio Theory Comes of Age

Cited by 31 publications

References 0 publications

Multi-objective Optimization Algorithms with the Island Metaheuristic for Effective Project Management Problem Solving

Multi-objective Optimization Algorithms with the Island Metaheuristic for Effective Project Management Problem Solving

Análise comparativa de distintas métricas de risco na composição de um fundo de fundos de investimento imobiliário

Extreme Risk, Excess Return and Leverage: The LP Formula

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