Abstract
Project managers normally are facing with difficulties behind management of project cash flow, which requires distinguished methods and appropriate tools to manage negative cash flows. Cash-Flow-at-Risk (CFaR) model is an efficient approach to predict cash flow trend. In this study, all risk factors affecting project management environment have incorporated to predict an accurate project cash flow. Then, a response surface method (RSM) is applied to determine optimal level of risk. The results have successfully implemented through a case study to demonstrate the applicability of the proposed method.
Highlights
The heart of a project is cash flow especially when the project is going to hand over or at the middle of execution phase
To cope with existing risk factors, for first time, we propose cash flow at risk (CFaR) model in project management
We propose a novel approach for prediction of delay by Gaussian mixture models (GMM)
Summary
The heart of a project is cash flow especially when the project is going to hand over or at the middle of execution phase. Two types of data or information can be considered as input including objective and subjective data, different terminology may be utilized The risks such as raw material price fluctuation, inflation rate and exchange are estimated by time series models and for these types of data; variance-covariance matrix should be developed due to interaction between factors. By considering all previous steps, cash flow is simulated for considered periods In this step, CFaR can be specified in determined confidence level but sometimes this CFaR is not acceptable for project manager, in this situation they can use risk management tools to reduce risk exposure and achieve a better condition to optimize profitability index and trend analysis.
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