Financial modelling with multiple criteria decision making: A systematic literature review

Filho, Adiel Teixeira de Almeida; Silva, Diogo Ferreira de Lima; Ferreira, Luciano Vaz

doi:10.1080/01605682.2020.1772021

Cited by 39 publications

(22 citation statements)

References 61 publications

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“…As metaheurísticas mostram-se como uma alternativa viável para lidar com o aumento de tempo necessitado por um solver exato devido ao aumento da complexidade do problema ao adicionar essas restric ¸ões. Uma revisão da literatura mostra que algoritmos evolucionários (nos quais estão incluídos algoritmos genéticos) são uma das principais estratégias para a otimizac ¸ão de portfólio [2], [5]- [7], [9], [11]- [13]. Esses algoritmos se mostram essenciais para portfólios com restric ¸ão de cardinalidade, problema de natureza combinatorial e com complexidade crescente à medida em que a quantidade de ativos presente no índice a ser perseguido aumenta.…”

Section: Trabalhos Relacionadosunclassified

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Avaliação de Algorítmos Genéticos Puros e Híbridos para Index Tracking

Amorim¹,

Silva²,

Filho³

2021

Anais Do 15. Congresso Brasileiro De Inteligência Computacional

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O problema de index tracking estuda a reprodução da performance de um índice com um portfólio formado por um número restrito de ativos. Esta abordagem é especialmente importante em situações reais, onde custos de transação estão associados à compra e venda de ativos, impossibilitando uma replicação fiel do benchmark. No entanto, essa restrição de cardinalidade do portfólio acrescenta uma complexidade adicional, por isso, sua solução pode levar muito tempo. Para contornar este problema, metaheurísticas foram propostas com o objetivo de alcançar boas soluções em um tempo razoável. Este trabalho analisa a performance de cinco algortimos genéticos aplicados a duas formulações de modelos para a otimização deste problema de seleção portfólio: um linear e outro quadrático, em termos de tempo de execução e qualidade da solução. Os resultados mostram que a abordagem híbrida dos GAs foi capaz de retornar soluções competitivas em menos tempo do que um solver genérico, tanto em períodos de otimização simples quanto em estratégias de rebalanceamento do portfólio, de forma a ser uma alternativa confiável à um gestor de fundos para ajudar em seu processo de tomada de decisão, permitindo diversos experimentos em um curto período de tempo antes da formação do portfólio.

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Section: Trabalhos Relacionadosunclassified

“…Este trabalho apresenta 5 variac ¸ões de algoritmos genéticos (GAs), uma das heurísticas mais populares no campo de index tracking [2], [3], [9], e introduz uma comparac ¸ão entre as soluc ¸ões por elas apresentadas e o pacote IBM ILOG CPLEX, solver exato comumente utilizado para a soluc ¸ão de problemas de otimizac ¸ão.…”

Section: Introduc ¸ãOunclassified

Avaliação de Algorítmos Genéticos Puros e Híbridos para Index Tracking

Amorim¹,

Silva²,

Filho³

2021

Anais Do 15. Congresso Brasileiro De Inteligência Computacional

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“…A variety of optimization methods have been applied to financial problems such as investment portfolio selection (Markowitz, 1952; Mulvey, 2001; Pardalos et al., 1994), asset‐liability management (Kouwenberg & Zenios, 2008; Sodhi, 2005), and cash flow management (Baumol, 1952; da Costa Moraes et al., 2015; Miller & Orr, 1966). As in water resources systems analysis, some researchers have attempted to provide more realistic decision support using multi‐objective formulations (de Almeida‐Filho et al., 2020; Marqués et al., 2020; Salas‐Molina et al., 2018; Zopounidis et al., 2015), model‐free information (Sun et al., 2011), heuristic solution methods (Aguilar‐Rivera et al., 2015; da Costa Moraes & Nagano, 2013; Ponsich et al., 2013; Tapia & Coello Coello, 2007), and visual analytics (Flood et al., 2016; Savikhin et al., 2011). Beyond the academic literature, the use of quantitative decision support tools by financial firms (e.g., banks, hedge funds, insurers) has proliferated in recent years, driven by growth in computing power, big data, algorithms, and visualization software (Fabozzi et al., 2007; Rundo et al., 2019; Zopounidis et al., 2018).…”

Section: Introductionmentioning

confidence: 99%

From Stream Flows to Cash Flows: Leveraging Evolutionary Multi‐Objective Direct Policy Search to Manage Hydrologic Financial Risks

Hamilton

Characklis

Reed

2022

Water Resources Research

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Reservoir control and financial risk management share strong similarities. The principal task in each is to reduce the risk of negative impacts from variable inflows (either hydrologic flows or cash flows), through the use of a buffer stock (either a reservoir or a reserve fund) that is filled in times of abundance and drawn down in times of scarcity (Figure 1). Other risk management tools may also be used to limit the impact of low-flow periods, but at a cost (e.g., water desalination or demand management for streamflow deficits, and borrowing or financial hedging for cash flow deficits). In both cases, the manager must make decisions under an array of uncertainties, and may need to navigate tradeoffs between conflicting objectives (e.g., flood control vs. water supply for reservoir control, risk vs. cost for financial risk management). And in both cases, as systems dynamically evolve, managers will have to adapt to new information as it becomes available. In other words, reservoir control and financial risk management can be formulated as very similar Markov Decision Processes (MDPs) (Bertsekas, 2019;Powell, 2019), whether managers attempt to solve this problem explicitly, using programmatic approaches such as stochastic dynamic programming, or implicitly, relying on expert specified rules. Additionally, reservoir control and financial risk management are strongly interdependent activities for water-reliant organizations in the Food-Energy-Water Nexus, such as hydropower producers, municipal water utilities, and irrigation districts (Cai et al., 2018;D'Odorico et al., 2018;Scanlon et al., 2017). Such organizations rely on water for the provision of services, and as a result, their revenues and/or costs can be highly dependent on hydrologic inflows (Blomfield & Plummer, 2014;Larson et al., 2012). This suggests that an understanding of complex water resource system dynamics can be used to better characterize and adaptively manage financial risks borne by water-reliant organizations.

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“…Small and medium-sized enterprises, initially designed to operatewithin their domestic markets, at some point of their growth process, might have to decide whether to expand into foreign markets or to remain local (Luo & Zhang, 2016). In many cases, this decision is so critically important to smallsized enterprises (SME), that an erroneous decision can ruin the entire operation (Almeida-Filho et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A MCDA-based Approach on Corporate’s Investment Decision Process: A case study of a Small-sized Firm’s decision on Foreign Direct Investment

Ribeiro

Vieira

Nakano

2022

IJSMS

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Small and medium-sized enterprises have frequently been facing great troubles in capital budgeting and investment decisions. Part of these troubles comes from the very nature of the modern financial decision problems. While well-known classic optimization methods can properly solve traditional financial decision problems with a single objective, they fail at solving real-world complex problems, which involves the interplay of multiple concurrent decision factors, against a backdrop of financial constraints. As a result, the corporate finance field has been demanding more sophisticated approaches, which integrate traditional quantitative methods with Multi-Criteria Decision Analysis techniques (MCDA), probabilistic models, simulations and optimization methods. This paper combines Corporate Finance theory with a MCDA approach based on the von Neumann-Morgenstern’s Utility Theory and presents a case study within a small-sized firm that needs to decide whether or not to expand into international operations, given a set of decision factors and financing constraints. The results deliver a structured decision framework to assist the firm’s managers, increasing impartiality in the investment decision process and help the decision makers (DM) reach a rightful, well-substantiated decision to their investment decision problem.

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Financial modelling with multiple criteria decision making: A systematic literature review

Cited by 39 publications

References 61 publications

Avaliação de Algorítmos Genéticos Puros e Híbridos para Index Tracking

Avaliação de Algorítmos Genéticos Puros e Híbridos para Index Tracking

From Stream Flows to Cash Flows: Leveraging Evolutionary Multi‐Objective Direct Policy Search to Manage Hydrologic Financial Risks

A MCDA-based Approach on Corporate’s Investment Decision Process: A case study of a Small-sized Firm’s decision on Foreign Direct Investment

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