專案融資計畫案財務可行性及風險評估模式之建構-以台灣高鐵計畫為例

Abstract

近期國內重大的民間參與國家建設案，如台灣高鐵案、高雄捷運案，因資金無法到位、工程逾期完成等種種問題，使得計畫面臨失敗的可能性。對國內BOT案最大融資者之國內聯貸銀行而言，聯貸銀行將受到因操作不當致使機構承受鉅額損失。BOT案是屬於專案融資（Project Finance），專案融資案計畫複雜度高、計畫期長，不同於一般傳統借貸，銀行所承受風險之可能性及複雜度均變高，因此完整的風險分析及管理是專案融資案重要研究課題。 所以如何建立一套財務評估模型、評估指標量化機制及找出各關鍵財務影響因子，加以控制與修正，使的BOT專案計畫更形穩健，讓政府、投資者與銀行團之間形成三贏。所以降低BOT專案風險，使專案更具可行性，勢必為重要之研究課題。本研究利用工程經濟學公式建立一套專案財務分析模型，並藉由Excel、SAS、@Risk、Lingo等軟體，進行實證分析研究以模擬高鐵計畫財務特性，建立七大財務可行性指標之迴歸方程式，並從政府、投資者與銀行團等不同角度，利用線性規劃求解求得最佳出資比，以供銀行團與投資者於借貸前，能做最佳之融資決策。並可做為後續風險分析之標準組(Base Case)數據。 利用標準組數據，針對專家訪談而得之風險因子，進行敏感度分析（Sensitivity Analysis），求出第一階段之關鍵財務影響因子並加以排序。再進行第二階段之情境模擬（Scenario Analysis）與加入機率條件進行蒙地卡羅模擬（Monte Carlo Simulation）。 以文獻之高鐵BOT專案財務為例，經工程經濟模式及線性規劃模式分析，考慮投資者及銀行團之角色，各以IRR值及DSCR為線性方程式之目標函數，求得 op=20%(股東最佳出資比)及 max=23.22%(股東最大出資比)，供雙方決定貸款比率時之依據。 本模式分析出高鐵BOT案關鍵財務影響因子，對七大財務可行性指標影響，排列出關鍵財務影響因子影響順序及影響程度，結果可以做為BOT專案執行時風險管理之重點，期能降低BOT案風險，使BOT計畫更具可行性。

The BOT mechanism does not go well in Taiwan. The Taiwan High Speed rail project as well as Kaohsung subway project encountered many problems, such as cost overrun, time delay, funding misplace etc.. These problems may result in the failure of the BOT project. As the major financing participants, banks face the highly potentials of the huge financial loss. BOT posses the project financing mechanism. Project finance is different to conventional loan due to the long terms and complexity of the project. Hence, a complete financial analysis is crucial to the BOT projects. This thesis is aimed to build financial analysis model and risk analysis model. These models can calculate the project financial feasibility, project financial characteristics and the best capital structure of the project. As well as the critical factors of the BOT project can be identified. The models is based on the theory of engineering economics with the softwares, such as Excel, SAS, @Risk, Lingo etc.. The Taiwan high speed rail project is used to serve as the case study of the application of model analysis.The risk analysis includes the sensitivity analysis, scenario analysis, and Monte Carlo simulation. The results show that the optimum capital structure is 20% of the private funding from the investors. Maximum private funding ratio is 23.22%. These models identify the critical factors of the project which can provide as a reference for the management authority. With careful tackle of the critical factors could smooth out the problems of the project. And, therefore enhance the feasibility of the project.