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Real Options: Finding Comfort in a "Learn and Adapt" World

Article Synopsys:

This article, published in Valuation Strategies (January/February, 2004), concludes that learn and adapt behaviour usually increases value and reduces risk, above and beyond that which emerges from traditional Cash Flow analysis. It is worth emphasizing that these gains, while they would exist independently of the approach used to value an initial investment decision, would remain hidden to the decision maker if that approach were not one that identified, measured and incorporated into the valuation all available Real Options.

Whether using transplanted orthodox financial options methodologies or the more transparent and easier to communicate, non-naïve Decision Tree Analysis, techniques do exist for ensuring that valuations reflect actual, activist management behaviour.

Using only traditional techniques will leave users with a competitive disadvantage since they will not ever fully understand the value of their investments. This is particularly true for competitive M&A activities and for cases where capital rationing may misallocate resources to lower value endeavours.

Also, whatever the Real Options approach used, there are some basic information requirements in order to survive and prosper in a Learn and Adapt world. These include:

  • An initial portrait of the investor's world over the investment horizon, including all identified uncertainties, the time at which their outcomes will be known and all available options to manage those uncertainties,
  • A relative ranking, by impact, of all the identified uncertainties so that resources need not be allocated to modelling those with relatively low impacts,
  • An overall Risk Profile of the investment opportunity, to provide a base case portrait of the investment's value and risk and a reference point for valuing their available options,
  • The value added to overall investment returns by management's available Real Options,
  • A dynamic road map, showing the optimal strategy, at each downstream decision point, for any combination of uncertainty outcomes.