The material below comprises excerpts from books by Dr. Johnathan Mun, our CEO and founder, such as Readings in Certified Quantitative Risk Management, 3rd Edition, and Quantitative Research Methods Using Risk Simulator and ROV BizStats Software Applying Econometrics, Multivariate Regression, Parametric and Nonparametric Hypothesis Testing, Monte Carlo Risk Simulation, Predictive Modeling, and Optimization, 4th Edition ( All screenshots and analytical models are run using the ROV Risk Simulator and ROV BizStats software applications. Statistical results shown are computed using Risk Simulator or BizStats. Online Training Videos are also available on these topics as well as the Certified in Quantitative Risk Management (CQRM) certification program. All materials are copyrighted as well as patent protected under international law, with all rights reserved.

This part of the book presents several actual cases and real-life applications of real options, financial options, and employee stock options, with particular emphasis on framing the options or framing the problems. You can use the ROV Strategy Trees module available on the main Real Options SLS user interface to create visually appealing representations of strategic real options. This module is used to simplify the drawing and creation of strategy trees but is not used for the actual real options valuation modeling. Use the other Real Options SLS software modules such as Single Asset or Multiple Asset SLS for actual modeling purposes.

In the Integrated Risk Management process, after modeling the decision and quantifying risks using Monte Carlo simulation, the question that should be asked is, what’s next? The risk information obtained somehow needs to be converted into actionable intelligence. So what if the risk has been quantified to be such and such using Monte Carlo simulation? What do we do about it? The answer is to use real options analysis to hedge these risks, to value these risks, and to position yourself to take advantage of the risks. The first step in real options is to generate a strategy tree through the process of framing the problem. Based on the overall problem identification occurring during the initial qualitative management screening process, certain strategic optionalities would have become apparent for each particular project. The strategic optionalities may include, among other things, the option to expand, contract, abandon, switch, choose, and so forth. Based on the identification of strategic optionalities that exist for each project or at each stage of the project, the analyst can then choose from a list of options to analyze in more detail. Real options are added to the projects to hedge downside risks and to take advantage of upside swings.

One major misunderstanding that analysts tend to have about real options is that they can be solved using decision trees alone. Instead, decision trees are a great way of depicting strategic pathways that a firm can take, showing graphically a decision road map of management’s strategic initiatives and opportunities over time. However, to solve a real options problem, it is better to combine decision tree analytics with real options analytics, rather than solely relying on decision trees. When used in framing real options, these trees should be more appropriately called strategy trees (used to define optimal strategic pathways).

In summary, decision tree analysis is incomplete as a stand-alone analysis in complex situations. Both the decision tree and real options methodologies discussed approach the same problem from different perspectives. However, a common ground could be reached. Taking the advantages of both approaches and melding them into an overall valuation strategy, decision trees should be used to frame the problem, real options analytics should be used to solve any existing strategic optionalities (either by pruning the decision tree into subtrees or solving the entire strategy tree at once), and the results should be presented back on a decision tree. These so-called option strategy trees are useful for determining the optimal decision paths the firm should take.


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