Cash Flow Forecasting With Risk Consideration Using Bayesian Belief Networks (Bbns)

Abstract

Cash-flow management is very important for contractors given that inadequate cash resources typically are the main causes for bankruptcy of construction companies. In comparison to most other industries, the construction industry is severely plagued by risk, and the success of construction projects usually depends on valuating all risks. However, conventional methods suggested by extant research on cash flow forecasting do not consider comprehensive identifica­tion of risk factors, interactions between the factors, and simultaneous occurrences of the factors. This study introduced a simple and appropriate probabilistic cash flow forecasting model using Bayesian Belief Networks (BBNs) to avoid bankruptcy of contractors by considering influence diagrams and risk factors that affect a project. Workability and reli­ability of the proposed approach was tested on an important building construction project in Iran as a real case study, and the results indicated that the model performed well.

Foreign Infrastructure Investment in Developing Countries: A Dynamic Panel Data Model of Political Risk Impacts

“…Research shows that FDI is affected by the context of the host country (Méon & Sekkat, 2012). And, political risk stands out as a significant determinant (Khanzadi, Eshtehardian, & Mokhlespour Esfahani, 2017). That is, political risk in developing countries, such as violent conflicts, expropriation of foreign assets and corruption, is characteristically higher than in developed countries, while foreign investors favour stable political environments (Hosseini et al, 2018).…”

Assessment of Performance of Holding in the Context of Cash Flow Concept

“…The proposed methodological toolkit, which, according to the authors, prerequisites for the provision of subsequent effective managerial impact, is not full and it presupposes its addition with the indicators whose focus is to evaluate such criteria for identifying the performance of the holding as ensuring liquidity and solvency, as well as cash inflow including that one from the main activity of the Russian Railways holding. Justification of their composition, when the study of the results of research in the field of efficiency assessment issues [6,7] and cash flow management [8,9], evaluation of stochastic cash flow factors [10,11,12], issues of the relationship between marketing and business value [13], the use of mathematical methods in the evaluation of cash flows [14,15] being the base of the process, is the subject of another independent study.…”

Probabilistic life cycle cash flow forecasting with price uncertainty following a geometric Brownian motion

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