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Financial Simulation Modeling in Excel, + Website: A Step-by-Step Guide (Wiley Finance)

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Regardless of where I work, simulation has crept into my financial career. After nearly a decade of working with it in many capacities I’ve found it to be a mixed blessing. In many investment companies when the term simulation is simply brought up there are a variety of reactions. The two most visible camps of thought seem to be the utilizers, who think the results of a simulation have value and the skeptics, who think simulation overcomplicates analyses.

The utilizers believe that when a concept or instrument is researched correctly, information parsed and calculated properly, and a simulation constructed in a statistically correct manner, the results can be used to make decisions. I tend to fall into this camp, with a few caveats I will mention later, because I have seen its utility in a variety of settings. Infrastructure deals that I saw early in my career that involved vehicular traffic, trade, or passenger flows, made more sense through simulation results given the wide variety of scenarios that could play out over time. A commodity company investment that I worked on at Citigroup involving soybeans seemed more appropriate after seeing the historic volatility of soybean prices and how their expected evolution might affect our exposure. In my structured finance career, the value of simulation on a very granular level for distressed mortgage-backed securities provided insight into obligor delinquency, default, and eventually expected security value loss. More recently, as I moved into private equity, simulating pools of corporate exposures and fund performance has become an important tool in assessing portfolio risk.

With all of these positives, there are some valid criticisms of simulation that are espoused by the skeptics. Relating to the overcomplication arguments is the thought that simulation is complex and that many mistakes can be made. I agree with this criticism, and one of the caveats that I alluded to earlier is that simulation must be implemented correctly for it to be useful and productive. I have seen simulations fail for a number of reasons, but most relate to poor implementation. In one transaction that I saw taken to a credit committee, the simulation implemented was purely derived from Excel’s random number generator creating numbers based on a uniform distribution. No analysis was done around the appropriate distribution, and the CEO, who had an actuary background, instantly criticized the presentation.
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