When I create a report assuming conservative spending (zero real investment return), my Monte Carlo results (at page 128) show that the "Zero Real Return" and the "Specified Mean Real Return" are the same. That makes sense because my specified mean real return (with conservative spending) was zero. However, when I change to cautious spending (half of the mean real return), the results seem puzzling.
No update since Feb and this issue seems unanswered.Last advice was use the old monte carlo formula" It feels like the focus is on Maxifi which is fine but I'm wondering why I spent money to renew this in February if it was being dropped. As Larry says above ' Please tell him to run the old MC for now and that we are fixing some issues in the new MC now and hope to have a new version ready in a few weeks, at least in MaxiFiPlanner". Please advise as to a few weeks from when? Thanks, Jody
I am interested in understanding how the MC function uses data and does its calculations. Namely, is the historical range used to establish a range of possible returns for the specific asset class (ie -40% to +30%) and to randomly pick a figure from within the historical range to apply to the asset amount from the prior year, independently of the prior years returns.
Or, does is the range of possible returns for a given year, influenced by the prior years returns?
I'm hoping this is something simple I am overlooking. With the profile I have setup I just noticed something I can't explain. I can run an analysis with just Economic-Based Planning. I then activate the Monte Carlo option, with no other changes, and run another analysis. The Suggested Consumption Table is noticeably different between these two runs. The Current and Suggested Consumptions are lower by about 10% for the Monte Carlo active run. The Suggested Savings is lower by about 10% as well. I was expecting these to be identical between runs. I am missing something here?
After reading through the release notes in 2.36 and 2.37 and looking at my Monte Carlo reports after recently installing 2.37.2 I have the following questions I hope you can answer:
1. Looks like the Distribution and Range reports were eliminated as they do not appear on a report run and the User manual no longer describes them. The release notes say reports were simplified, but not eliminated. Why were they eliminated?
My Standard of Living results have previously made sense, or at least I didn't notice that they didn't.
The recent Monte Carlo change has my standard of living often better with a Very Low Return vs. a Low Return. Every now and then, a High Return has a better standard of living than a Very High Return. I do have a significant bond allocation, if that matters.
It makes it difficult to root for an outcome :-)
I've specified conservative spending in my Monte Carlo setup. Everything looks fine in the non-MC report. Everything seemingly looks great in the MC report - all graphs go from something fairly horizontal at the Specified Mean Real Return to sloping dramatically upward for the 95th percentile. EXCEPT for the MC reports regarding Regular Assets.
What does the Living Standard values in the monte carlo analysis represent, compared to the baseline reports? Specifically, two questions:
1) do they represent all spending or just discretionary spending?
2) do they represent 'per adult' or 'total household' living standard?
I don't understand what this Monte Carlo report is trying to tell me. It has columns that go all the way to 200%. Not sure how there can be a 200% probability of anything.
Every time I run the monte carlo simulation I get different results - I assume this is expected since the random numbers used to generate the results are different on each run. However I find the differences are significant enough that I cant rely on the results for future retirement planning. After 20 years one run generates a 50th percentile living standard of 114K per year, a second rerun of the same inputs generates a 50th percentile living standard of 122K per year. I can imagine that this is not a bug, but is just the way monte carlo simulations work.