Monte carlo simulations in excel for financial modeling

so , i am learning how to model financial statements in excel and how to introduce some macroecnomic and/or market factors as well as general uncertainty inside the model (i mean assigning a confidence interval for some estimates). i am mainly concerned with the accuracy of the DCF model (you don't say? ;) ) and i want to run a monte carlo simulation to test all the possibilities and get an idea of how the different % match the DCF prices that come out of the model.

problem: this is an absolute nightmare in excel. i mean i can examine manually the different cases with 2 variables moving while everything else is still (and also i can build a 3d graph - a surface- to help me understand the price changes) but when you have 10+ things that are moving i need something more powerful.

in conclusion, how to get it done? are there some plugins to do it (yes i've already tried to google them but all the good ones are very costly)? or do i have to resign myself to some specific software?

 
CrazyAnalyst122:

evidently i lost something in the way because i thought that accuracy was a key element in the dcf!

Honestly, it really isn't. The key element in the DCF is the quality of your assumptions. You will never, ever, ever use monte carlo when doing a DCF. You don't have a large enough data set. Now get back to your stats homework.

"For I am a sinner in the hands of an angry God. Bloody Mary full of vodka, blessed are you among cocktails. Pray for me now and at the hour of my death, which I hope is soon. Amen."
 

Do you know what Monte Carlo is? Do you know mean, stddev, and type of distribution? If not, do you have historical data to analyze? If not, again, can you find data? Are you comfortable with stats? Meaning, you know which tail to look at for this situation... Do you know PDF vs CDF?

Hard to give tips without knowing where you're at. I have not used "Quantum XL", only @Risk and Crystal Ball...

I'll do what I can to help ya'll. But, the game's out there, and it's play or get played.
 
pplstuff:
Do you know what Monte Carlo is? Do you know mean, stddev, and type of distribution? If not, do you have historical data to analyze? If not, again, can you find data?

Are you comfortable with stats? Meaning, you know which tail to look at for this situation... Do you know PDF vs CDF?

Hard to give tips without knowing where you're at. I have not used "Quantum XL", only @Risk and Crystal Ball...

Yes to all except knowing which tail to look at. But if I successfully run the simulation, I'll have help analyzing it. I'm using Morningstar data.

 
pplstuff:
Do you know what Monte Carlo is? Do you know mean, stddev, and type of distribution? If not, do you have historical data to analyze? If not, again, can you find data? Are you comfortable with stats? Meaning, you know which tail to look at for this situation... Do you know PDF vs CDF?

Hard to give tips without knowing where you're at. I have not used "Quantum XL", only @Risk and Crystal Ball...

I really just need help knowing what data is important and what isn't important. I have the basics down.

 
Best Response

First, you next to know which of your inputs are random variables. Perhaps you're making widgets, and the expected cost of raw materials is x1_bar. Since x1_bar is a random variable, it must have an underlying distribution and std.dev. Your job would be to find the shape of the distribution and std.dev. (common dist. types would be uniform, triangular, normal, poisson, etc.)

Once you've determined these parameters, you'll develop a model where your program will randomly input values based on the mean, dist. shape, and std.dev.. Usually, 10k iterations is will give you a good indication of which variables play a greater impact (read: greater variance) in determining your portfolio value. In Crystal Ball, it generates 'tornado charts' which are useful for visualizing these variances.

I'm not sure what your analysis could include, but continuing the widget example for manufacturing facility above... they might have the following [somewhat] random variable in their model. -cost of raw materials -selling price -marketing expenses -economic conditions (inflation?)

Hope this gives you some fuel. Good luck!

I'll do what I can to help ya'll. But, the game's out there, and it's play or get played.
 

See if you can find a piece of software called Crystal Ball.

It is an Excel add-in and it does Monte Carlo Simulations automatically for you, and you can choose any probability distribution functions you want.

btw, you can always use the random number generator in Excel 2007: Data - Data Analysis - Random Number Generation.

 
Murders_n_Executions:
See if you can find a piece of software called Crystal Ball.

It is an Excel add-in and it does Monte Carlo Simulations automatically for you, and you can choose any probability distribution functions you want.

btw, you can always use the random number generator in Excel 2007: Data - Data Analysis - Random Number Generation.

Crystal Ball is awesome – very user friendly and lets you alter distributions. Excel may be good enough as is. For a dcf, you can build rand functions into the model. You can build an array with 10000 (or whatever) iterations of the value, and calculate the basic statistics.

 

To my knowledge there is no "software" per se, well I'm sure there are companies who have their proprietary software, but I haven't heard of freeware.

You could write your own (I guess not since you are asking for a pre-made thing) code, or you can try googling a monte carlo code for your particular need. Something along the lines "c++ monte carlo"... But most likely you will not find anything that matches your needs exactly, so some tweaks will have to be done (you better know someone else who can code, if you are not able to).

 

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