Author Topic: Monte Carlo Simulation  (Read 1884 times)

clutch

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Re: Monte Carlo Simulation
« Reply #10 on: November 28, 2018, 12:35:28 PM »
Seriously now, does anyone have a recommendation for a software or a website to run some Monte Carlo simulations?  Please tell me that I don't have to be a Computer Science major in order to make it work.  I would prefer it to be easy enough for a dumb American from Virginia to operate.

Thanks in advance!

You can do it in Excel:
https://support.office.com/en-us/article/introduction-to-monte-carlo-simulation-in-excel-64c0ba99-752a-4fa8-bbd3-4450d8db16f1


rb

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Re: Monte Carlo Simulation
« Reply #11 on: November 28, 2018, 12:38:17 PM »
You can build one in Excel pretty easily. I'd recommend you lean how to do it. Once you do it'll be easy to make do anything you want. It'll be powerful knowledge.

Just because you're an American from Virginia doesn't mean you should abandon hope. People overcame bigger obstacles than that.  ;).

If you're really looking for software, one of the best I've seen is the Decision Tools suite from Palisade Software. No idea how much it costs though.

cameronfen

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Re: Monte Carlo Simulation
« Reply #12 on: November 28, 2018, 01:28:01 PM »
if you are anywhere decent in coding, you can use python or another language, gives you more flexibility than an excel add on.  It sounds fancy but coding on you own well enough for these simulations basically requires teaching yourself a coding language for one month or so and is less daunting than it seems.  Granted with the amount of effort allow myself to put in now on research, I dont have the time to build simulations. 

LC

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Re: Monte Carlo Simulation
« Reply #13 on: November 28, 2018, 03:08:20 PM »
Ditto on learning to code it yourself in python or R
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StubbleJumper

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Re: Monte Carlo Simulation
« Reply #14 on: November 28, 2018, 03:29:57 PM »
I disagree heartily about programming it yourself.  You can set up a basic Monte Carlo simulation model in Excel in less than 30 minutes.  You can easily set it up such that every row in the spreadsheet can be a trial and then drag down 1,000 rows to run 1,000 simulations.  IIRC, you can hit F9 to recalc to re-run your 1,000 simulations as often as you want, which gives you an idea of the range of outcomes you might expect.

In my opinion, whenever you are doing Monte Carlo (or any stochastics) you should spend 90% of your time worrying about whether you have your model parameterized properly and only 10% of your time worrying about whether its appearance is elegant or whether you've run enough trials.  Your biggest fuck-up is likely to be caused by choosing the wrong mean/standard deviation if those are the two principal parameters that you use.  You can fuss and fuss about your model, but it's likely that your choice of parameters will be your most significant failing (ie, you've selected a standard deviation of a security's return based on data from year 2010-2017, but those years no longer reflect reality for the company today).  Go ahead and parameterize your model the best you can, and then spend lots of time asking yourself what the impact will be if your parameters are not valid (ie, run it many time with different parameters to get a notion of sensitivity).  Then after you've done this, toss your model out the window and just spend your time thinking.


SJ

SHDL

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Re: Monte Carlo Simulation
« Reply #15 on: November 28, 2018, 05:55:52 PM »
I personally use Python, but I would urge you to pay special attention to what SJ just said about model specification.  That is exactly what I meant when I said above that this is “GIGO.”  This type of modeling is very tricky stuff, dangerous even, because if your model is wrong and you don’t notice it and you push it too hard you can blow yourself up spectacularly a la LTCM and so many others.

Dynamic

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Re: Monte Carlo Simulation
« Reply #16 on: December 03, 2018, 05:29:43 AM »
I'd agree that you have to be very careful about the garbage in garbage out problem when using it to make financial decisions such as valuations. The assumptions you build into your model are important and it's worth checking the sensitivity of your model to changes in various inputs to see what inputs are most at risk of producing flawed results, either in terms of expected value or in terms of risk of loss. If in doubt, perhaps it's safest to err on the pessimistic side, especially if the sensitivity is very high.

Personally, I wouldn't even want to cut it close, so in practice I've never used Monte Carlo simulations for investing. The most I've done yet is more like scenario-based modelling, and the specific situation where I invested offered such attractive returns from the typical situation that it far outweighed the potential loss from the lower probability fringe case scenarios. I then simply tied my exposure to the amount I felt I could afford to lose in the worst case and still meet my long-term goals via my safer investments.

Where I found MC simulation in Excel to be very useful was in product engineering in my previous career, combining different kinds of probability distributions other than Normal Distributions to prove that a product would remain within its relatively narrow output power specification window throughout the full design life with very high certainty given the product screens we had implemented. For example, bipolar probability distributions, box-car distributions and truncated normal distributions, or Poisson distributions for different variables can be combined by Monte Carlo simulation to generate the overall output distribution.

If you're only combining Normal Distributions of a few variables by addition and subtraction there are some simple rules to combine the standard deviations (or variances), which negate the need for a Monte Carlo simulation.

writser

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Re: Monte Carlo Simulation
« Reply #17 on: December 03, 2018, 06:07:18 AM »
Agreed. Also, if you need Monte Carlo simulation to determine whether an investment is worthwhile I'd say you should look another opportunities anyway. Keep it simple.
When you are dead, you do not know you are dead. It's only painful and difficult for others. The same applies when you are stupid.

Hielko

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Re: Monte Carlo Simulation
« Reply #18 on: December 03, 2018, 06:27:50 AM »
It sounds sort of reasonable, but I think there are plenty of cases were you aren't totally aware of the potential variance in outcomes before doing the simulation. You take some quick and easy mental short cuts and you decide it's a low risk thing that should work out in most cases. No Monte Carlo simulation needed. Right?

writser

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Re: Monte Carlo Simulation
« Reply #19 on: December 03, 2018, 07:11:24 AM »
You take some quick and easy mental short cuts and you decide it's a low risk thing that should work out in most cases. No Monte Carlo simulation needed. Right?

Those are my preferred investments :) .

Sure, there are some use cases for Monte Carlo simulation in investing, I'll give you that. Especially if you work with derivatives. However, unless you know specifically what process you want to model, why that process should be modelled specifically using Monte Carlo simulation and what parameters to use I'd say the vast majority of times you are better off doing something else. If you want to get a feel for the variance of a model why not tinker with a few key variables manually to see what happens? That way you can get a much better feel for what is happening under the hood.
When you are dead, you do not know you are dead. It's only painful and difficult for others. The same applies when you are stupid.