
#21




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I then decided to use mean+(c*s.d.), "c" being a constant. Obviously, lowest metric would be best. The portfolio with the lowest metric wound up having bonds take up a bulk of the portfolio with treasuries and equities evenly splitting the remaining portion. My coworkers were more accepting of this strategy, and said I should be able to pass Task 2 assuming I explain it effectively. We'll see if I pass; I'm still waiting on my result. Hopefully this can be a oneanddone thing (this is my first attempt). 
#22




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#24




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For example, let's assume you set the price at CTE (90). If in the worst 100 scenarios, one scenario has a tax amount of 1000 and the other 99 scenarios have a tax amount of 2000, CTE(90) would be 1990. However, setting the tax at 1990 would mean that CTE(90) would only be sufficient for 90.1% of scenarios. On the other hand, if 99 scenarios have a tax amount of 1000 and 1 scenario has a tax amount of 2000, CTE(90) is 1010. Setting tax at CTE(90) in this case would be sufficient for 99.9% of scenarios. Obviously, these two examples are pretty extreme but it illustrates the point that setting the tax at CTE would lead to a degree of confidence that can't be quantified. CTE is still useful though and should probably be one of your risk/return requirements (ex: CTE is within X% of the Var to prove that the portfolio does not have a huge tail risk). 
#25




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#26




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A fixed margin also helps in justifying why I chose to use one of 75, 90, or 95 over the other two. I would be able to explain that the percentile I chose gave me a known degree of confidence which provides a sufficient margin for adverse deviation without being overly conservative. With CTE, since the margin can vary, I personally believe it is harder to justify my choice between the 75th, 90th and 95th percentiles. Just my two cents, so if you personally feel more confident with setting the price at CTE then that is what you should do. 
#27




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