The most common method for solving sequential decision problems is to run a 300-year-old Net Present Value (NPV) model on updated late-1970s spreadsheet technology.
This and other traditional methods – including decision trees and Monte Carlo simulations – often fail in two key areas:
- Traditional methods do not recognize that individuals have the ability to change course when economic, market, or business conditions change. In particular, they ignore what are known as “real options,” such as the option to delay an investment, increase an investment, conduct additional research before investing, or to abandon a failing investment.Experienced managers often rely upon their own judgement, rules of thumb, excessively cautious or aggressive policies, or a simplistic weighting of different scenarios to compensate for this failure.
- Traditional methods rely on a single discount rate to capture both the time value of money and the inherent risk in an investment. A typical, and often implicit, assumption is that the possible distribution of outcomes is a smooth “bell curve” around the expected scenario.In some limited cases (such as well-diversified investment portfolios in liquid markets with an extensive set of trading parameters), this is a reasonable assumption/ For nearly all other cases, however, asymmetric risk exists that are ignored, and the discount rate chosen does not properly take into account both the inherent risks, and the potential to change course if conditions change.
The failure of these traditional methods forces smart investors and managers to fall back on various adjustments, modifications, and shorthand methods. The consequences of these adjustments and deficiencies in traditional methods often include missed business opportunities, lost money, ignored risks, and over payments for investments.
The Recursive Solution
The ethos of the recursive method is to break large and complex problems into a series of smaller, two-step problems. When incorporated into our Rapid Recursive® Toolbox, it evaluates risks and opportunities in the same manner as people do: step by step, considering what decisions make sense today, and what opportunities exist to change course in the future.
The recursive model captures much more information about options, market conditions, and risks than traditional methods. As a result of both capturing more information, and using it in a better fashion, recursive models provide a demonstrably superior approach.
The Guide to Recursive Models provides further information on the comparisons of traditional and recursive methods and is available at our Books and Other Resources page, .
You may also be interested in technical papers that demonstrate the practical application of recursive methods.