Won the game? Where to set AA?

Lsbcal will have to confirm this, but I thought that his high WR was temporary until the SS kicks in. In other words, his number is case specific.
 
Lsbcal will have to confirm this, but I thought that his high WR was temporary until the SS kicks in. In other words, his number is case specific.
Yes, I set our SS to 2013 since we are now taking it, and thus the SS is in the full simulation. The WR %'s are what was taken from the portfolio and includes SS. It says on the simulation results: "Your spending is assumed to come from any Social Security and pensions you entered, as well as from the portfolio".

So I suppose I should have set the SS at zero to make the results more general. But my thinking with this thread was more about the fact that cutting back on the equity led to safer (minimum) withdrawal rates during the really bad stretches of years.

However, I have to now confess that I didn't read that (red) sentence above. :rolleyes::confused::facepalm: Yikes, this means the spending numbers that I thought were really high are not nearly so high in our case. The basic info here is good I think. It's just the interpretation in our case that is a problem for me.

So now I'm wondering, have I really "won the game"? By staying at a higher equity allocation, the average spending numbers increase even though the minimum worst case years show a dip. I've probably lost some (most) readers at this point. :)

Anyway, I also have done a fairly careful spreadsheet analysis of these sorts of results. Maybe I'll present the data once I go back and rework my thinking.

Thanks to ERD50 and NW-Bound for bringing this up! This thread has had an unexpected outcome for me, but getting things correct in the end is the important point for me.

I now think that NW-Bound's table from Nov 29 (first page here) is the best way to summarize things.
 
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Two comments about the OP. The optimum portfolio is a classic example of data mining also known as curve fitting.

The CAGR and GSD are identical: 40% Xstocks + 60% FI = 60% Ystocks + 40% FI.

X = SC, EM and some say REITS. Y = LC. The real expected return of Xstocks = 5%. For LC = 4%.
 
... Yikes, this means the spending numbers that I thought were really high are not nearly so high in our case. The basic info here is good I think. It's just the interpretation in our case that is a problem for me. ...

I've been thinking about the fact that for many (most?) of us, our WR changes over time - one spouse still working for a while, retired for a few years before taking pensions/SS. It makes it tough to compare.

So I've come up with a pretty simple process to equalize all this, and will tyr it post it later today.

Two comments about the OP. The optimum portfolio is a classic example of data mining also known as curve fitting.

...

I was thinking about this while reading his 'optimum portfolio' thread.

Optimal FIRECalc Portfolio - Early Retirement & Financial Independence Community

Of course, one could say any run of FIRECalc is 'data mining'. But getting to shorter time frames and more specific investments takes you deeper into that territory, it seems to me.

I feel better seeing that a wide range of AA ( ~ 45/55 to ~95/5) provides similar success rates. That shows a strong general trend. Not sure I feel that way about more specific profiles - but who knows? It is interesting to ponder.

-ERD50
 
I've been thinking about the fact that for many (most?) of us, our WR changes over time - one spouse still working for a while, retired for a few years before taking pensions/SS. It makes it tough to compare.

So I've come up with a pretty simple process to equalize all this, and will tyr it post it later today.
...
-ERD50
I'll be interested in seeing what you come up with ERD50. Need all the help I can get. :)
 

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