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Estimating project volatility and developing decision support system in real options analysis.

机译:在实物期权分析中估算项目波动性并开发决策支持系统。

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摘要

Today's uncertain world requires firms to have a system in place that can analyze the flexibility of their projects. Real options are utilized frequently to quantify the benefits of taking a particular risk. The real options valuation process provides a methodology to measure the value of flexibility, and it assists the decision makers in making the optimal investment decision. The goal of this research is to develop the methodology for improving the real options application in actual capital investment decision making.; The Reverse Monte Carlo Simulation model (RMCS), which combines Monte Carlo simulation and the stochastic processes, is developed as a new volatility estimation method for risky projects. Compared to previous simulation methods, RMCS results in more accurate volatility. Then a volatility revision processes based on the previous volatility estimation processes are proposed. A Bayesian revision process is suggested to estimate the new volatility when the initial volatility has been estimated by Monte Carlo simulation. Since specific cases that use typical types of Bayesian conjugate processes are hard to find in the real world, a Dirichlet conjugate process is applied to estimate posterior distributions of the future cash flows. After estimating the new distributions of the cash flows, the revised volatility can be computed using the RMCS approach.; Finally, a new early decision rule is developed in order to make real options more useful. This rule concentrates on maximizing the expected future project value. Under the new decision rule, an expected future value of the currently exercised option and the expected future option value are compared in order to determine the best exercise timing. An early decision map for "waiting," "early exercise," and "early divest" over the entire option life is developed to automate the decision in case some variables are revised in the future. The map indicates that increasing volatility enlarges the "waiting" area while decreasing volatility shrinks the "waiting" area. A simulation is applied to validate the newly developed decision rule by comparing the benefit of the early exercise rule and the volatility revision during the option life. The new decision rule is found to be useful in maximizing the expected profit of the delayed investment because the proposed decision model results in better than or equal to the current decisions model.
机译:当今充满不确定性的世界要求公司建立一个可以分析其项目灵活性的系统。经常使用实物期权来量化承担特定风险的收益。实物期权评估过程提供了一种衡量灵活性价值的方法,并且可以帮助决策者做出最佳投资决策。本研究的目的是开发一种在实际资本投资决策中改善实物期权应用的方法。反向蒙特卡洛模拟模型(RMCS)结合了蒙特卡洛模拟和随机过程,是开发用于风险项目的新的波动率估计方法。与以前的模拟方法相比,RMCS导致更准确的波动率。然后提出了基于先前的波动率估计过程的波动率修正过程。当通过蒙特卡洛模拟法估算初始波动率时,建议采用贝叶斯修正过程来估算新的波动率。由于在现实世界中很难找到使用贝叶斯共轭过程的典型类型的特定案例,因此将Dirichlet共轭过程应用于估计未来现金流量的后验分布。在估计了现金流量的新分布之后,可以使用RMCS方法计算修订后的波动率。最后,开发了新的早期决策规则,以使实际选择更为有用。该规则专注于最大化预期的未来项目价值。在新的决策规则下,将当前行使的期权的预期未来价值与预期的未来期权价值进行比较,以确定最佳的行使时机。开发了整个期权生命周期中“等待”,“提前行使”和“提前撤资”的早期决策图,以在将来某些变量被修改时使决策自动化。该图表明,增加的波动率会扩大“等待”区域,而降低的波动率会缩小“等待”区域。通过比较期权选择期内的早期行使规则和波动率修订的收益,通过仿真来验证新制定的决策规则。发现新的决策规则在最大化延迟投资的预期利润方面很有用,因为建议的决策模型产生的结果优于或等于当前决策模型。

著录项

  • 作者

    Han, Hyun Jin.;

  • 作者单位

    Auburn University.;

  • 授予单位 Auburn University.;
  • 学科 Engineering Industrial.
  • 学位 Ph.D.
  • 年度 2007
  • 页码 148 p.
  • 总页数 148
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 一般工业技术;
  • 关键词

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