[R-SIG-Finance] alternative to Crystal Ball ?

Liviu Andronic landronimirc at gmail.com
Mon Oct 27 11:58:06 CET 2008


Hello Brian,

On Sun, Oct 26, 2008 at 2:28 PM, Brian G. Peterson <brian at braverock.com> wrote:
> See the recent thread on R-SIG-finance about R in finance.  There is
>
Thanks for the pointer. I overlooked this discussion, informative indeed.


> Perhaps if you are a bit more clear about specifically what type of analysis
> you are trying to accomplish, this list can help you select a package that
> may meet your needs.
>
What we did in class with Excel, and that I would like to replicate in
R and subsequently use for our project, was fairly basic. We were
given a quantitative model [1] for a simulation. Questions to be
answered:
1. Using the monthly mean reversion model presented in Appendix A,
   develop the distribution of average aluminum price (US$ per ton) and
   US$/CAD$ exchange rate (US$ per CAD$) for one year.
2. Considering only aluminum price and currency risks, develop the distri-
   butions of EBITDA ($ per ton), Operating Cash Flow (OCF, $ per ton),
   and EVA ($ per ton) for a year when the smelter is fully operational.
   A minimum of two hundred thousand simulations is required.


The random part was given by Eta alone, so in Crystal Ball [2] this
was the defined normal random variable (in green); the blue coloured
cells was, in CB terminology, the "defined forecast" (the excel file
contains two or three distinct simulations; only one "defined
forecast" per simulation was used, I think). Then using Monte Carlo
simulations (assigning random values to Eta, around 100,000 attempts)
we estimated the modelled variable on a monthly basis and obtained an
estimated distribution (unfortunately I did not save any graphics, and
currently not on Windows). With this distribution (estimated mean,
std) we could determine the probability that the firms could end up
with negative cash flows. The goal of the game was to quantify the
price and currency risks (first individually, then together with their
correlation taken into account), and determine the firm's exposure to
these.

I feel I went into too many details, but if there is something
unclear, feel free to ask.
Regards,
Liviu

[1] http://s000.tinyupload.com/index.php?file_id=82303267004924284490
[2] http://s000.tinyupload.com/index.php?file_id=01823496393275663340



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