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Hub AI
Project finance model AI simulator
(@Project finance model_simulator)
Hub AI
Project finance model AI simulator
(@Project finance model_simulator)
Project finance model
A project finance model is a specialized financial model, the purpose of which is to assess the economic feasibility of the project in question. The model's output can also be used in structuring, or "sculpting", the project finance deal.
Project finance is the long-term financing of infrastructure and industrial projects based upon the projected cash flows of the project - rather than the balance sheets of its sponsors. The project is therefore only feasible when the project is capable of producing enough cash to cover all operating and debt-servicing expenses over the whole tenor of the debt.
Most importantly, therefore, the model is used to determine the maximum amount of debt the project company (Special-purpose entity) can maintain - and the corresponding debt repayment profile; there are several related metrics here, the most important of which is arguably the Debt Service Coverage Ratio (DSCR) - the financial metric that measures the ability of a project to generate enough cash flow to cover principal and interest payments.
The general structure of any financial model is standard: (i) input (ii) calculation algorithm (iii) output; see Financial forecast. While the output for a project finance model is more or less uniform, and the calculation is predetermined by accounting rules, the input is highly project-specific. Generally, the model can be subdivided into the following categories:
A model is usually built for a most probable (or base) case. Then, a model sensitivity analysis is conducted to determine effects of changes in input variables on key outputs, such as internal rate of return (IRR), net present value (NPV) and payback period.
For discussion (a) re cash-flow modelling, see Valuation using discounted cash flows § Determine cash flow for each forecast period; and (b) re model "calibration", and sensitivity- and scenario analysis, see § Determine equity value there.
Practically, these are usually built as Excel spreadsheets and then consist of the following interlinked sheets (see Outline of finance § Financial modeling for further model-build items), with broad groupings:
As stated above, the model is used to determine the most appropriate amount of debt the project company should take: in any year the debt service coverage ratio (DSCR) should not exceed a predetermined level. DSCR is also used as a measure of riskiness of the project and, therefore, as a determinant of interest rate on debt. Minimal DSCR set for a project depends on riskiness of the project, i.e. on predictability and stability of cash flow generated by it.
Project finance model
A project finance model is a specialized financial model, the purpose of which is to assess the economic feasibility of the project in question. The model's output can also be used in structuring, or "sculpting", the project finance deal.
Project finance is the long-term financing of infrastructure and industrial projects based upon the projected cash flows of the project - rather than the balance sheets of its sponsors. The project is therefore only feasible when the project is capable of producing enough cash to cover all operating and debt-servicing expenses over the whole tenor of the debt.
Most importantly, therefore, the model is used to determine the maximum amount of debt the project company (Special-purpose entity) can maintain - and the corresponding debt repayment profile; there are several related metrics here, the most important of which is arguably the Debt Service Coverage Ratio (DSCR) - the financial metric that measures the ability of a project to generate enough cash flow to cover principal and interest payments.
The general structure of any financial model is standard: (i) input (ii) calculation algorithm (iii) output; see Financial forecast. While the output for a project finance model is more or less uniform, and the calculation is predetermined by accounting rules, the input is highly project-specific. Generally, the model can be subdivided into the following categories:
A model is usually built for a most probable (or base) case. Then, a model sensitivity analysis is conducted to determine effects of changes in input variables on key outputs, such as internal rate of return (IRR), net present value (NPV) and payback period.
For discussion (a) re cash-flow modelling, see Valuation using discounted cash flows § Determine cash flow for each forecast period; and (b) re model "calibration", and sensitivity- and scenario analysis, see § Determine equity value there.
Practically, these are usually built as Excel spreadsheets and then consist of the following interlinked sheets (see Outline of finance § Financial modeling for further model-build items), with broad groupings:
As stated above, the model is used to determine the most appropriate amount of debt the project company should take: in any year the debt service coverage ratio (DSCR) should not exceed a predetermined level. DSCR is also used as a measure of riskiness of the project and, therefore, as a determinant of interest rate on debt. Minimal DSCR set for a project depends on riskiness of the project, i.e. on predictability and stability of cash flow generated by it.