Abstract

The main purpose of this paper is to expand real option analysis out of the realm of pure financial option pricing techniques. To overcome many of the well-known concerns by adopting the financial option pricing techniques for modeling real options problems such as replicating portfolio concept, geometric Brownian motion as underlying stochastic process, and estimating project volatility, we propose an alternative real option valuation based on the loss function approach. The option value determined by the loss function approach is equivalent to the expected value of perfect information (EVPI) in decision analysis. It basically sets the upper bound of risk premium to pay in retaining the options. In practice, many firms utilize the concept of Value at Risk to manage their portfolio risk. If a firm sets a target VAR, then we may be able to link this VAR in refining the actual risk premium to pay in hedging the risk embedded in the investment. With this practice in mind, we present a logic to figure out an appropriate amount of real option premium to pay for a given level of risk tolerance. A comprehensive example is presented to demonstrate the computational procedures as well as economic interpretations on the outcomes.

摘要

本文的主要目的是将实物期权分析扩展到纯金融期权定价技术领域之外。为了通过采用金融期权定价技术来建模诸如复制投资组合概念，作为潜在随机过程的几何布朗运动以及估计项目波动性等实物期权问题的方法来克服许多众所周知的担忧，我们提出了一种基于实物期权估值的替代实物期权估值方法。损失函数法。由损失函数方法确定的期权价值等于决策分析中理想信息（EVPI）的期望值。它基本上设定了保留期权的风险溢价上限。实际上，许多公司都采用“风险价值”的概念管理他们的投资组合风险。如果一家公司设定了一个目标VAR，那么我们可以将这个VAR联系起来，以细化实际风险溢价，以对冲投资中隐含的风险。考虑到这种做法，我们提出一种逻辑，以找出适当数量的实物期权溢价，以支付给定水平的风险承受能力。给出了一个综合的例子来说明计算程序以及对结果的经济解释。