@Bob – I don’t think it’s generational as much as an age thing. Just wait until you hit 30-35. Then Gen Y will be talking about mortgages, refinancing, student loans, daycare costs, and sensible minivans.

]]>@Seattle Sam – See About Me. Chicago also happens to be a lot less expensive than the bay area.

]]>It’s interesting that for my generation (Y), travel has become practically the norm – people think you’re an oddball if you don’t do it at least yearly.

]]>Now, we’re too tired to travel.

]]>Then again; an RV is a mobile Homebase, a small to large ship, and so is a small plane with beds in the back when you get a license (Jacob).

homebase*: A place where you are welcome to stay when traveling abroad if necessary.

]]>I love the idea of being able to travel both inside the US and around the world. I think that’s one aspect of early retirement that seems so appealing to me. Having the freedom to just pick up and go whenever the urge hits you.

Now, a far as financing my endeavors, I’m looking to create a hybrid model of financial independence. A good sized investment portfolio of income producing stocks, preferably dividend growth stocks with long track records, coupled with a passive or semi-passive online business that covers most of my monthly expenses.

My investments could serve as a safety net if my business failed or if I needed extra money for something like an operation or a trip to Hawaii in the winter, and if not, I could just let it keep growing.

If I get really tired of the business, I can always sell it off or form a partnership and let someone younger take over the day to day aspects. I think this plan beats working the 9 to 5 stuff for the next 40 years.

]]>Also, an important point which you mentioned in the beginning. Even a small side income or work from time to time can significantly alter the picture, as can a market boom or a market crash, or getting hit by a bus, etc.

PS: This stuff is in my bones. I’m probably assuming that this is the case for everybody but for practical purposes accuracy, precision, uncertainty, etc. are probably not universally ingrained. I worked with this stuff for many years so it’s become second-nature. It’s always hard to know what others know/understand. Like, when I used to explain my work, my first question was always “Do you know what a proton is?” That’s why I was concerned about sounding trite.

PPS: Yeah, that’s because your “needs” are around 20% and your wants are 80% and you successfully cut your wants. The needs require macrochanges.

NB: I think this is all covered in Chapter 7 ðŸ˜‰

]]>I remember the precision vs accuracy discussion from school, although I admit I haven’t internalized it to the point where I regularly use those terms. You’ll note that my units are in years though… implying a lack of precision (as opposed to months or days or fractional years, etc). It’s true that my SWR/savings rates have a couple of significant digits… but 3% is nothing like 4%…

Anyway, trying to use this terminology, what I was trying to say in my first comment was: FI after 75% x 5 is inaccurate (improbable)

And your response was: no, imprecise

And my followup was: it’s still inaccurate!

Anyway, I get what you’re saying about implying a lack of precision with 3/4s… although I personally read 75% as being more precise than “three quarters”. I like the phrasing you’ve settled on.

I agree that actual investment returns are better than SWRs. I look forward to having my own data for this, but for now historical SWR returns are pretty much all that I have.

Interestingly, I just got done reading “When Genius Failed” about the LTCM boys a few weeks ago — good read!

PS: I think I might be immune to triteness. I can’t even tell whether your reply was trite or not — I seek only to understand.

PPS: Random semi-on-topic observation: going from 75% -> 85% savings rate seems as hard or harder than 50% -> 75% was for me

]]>Maybe if I had said slightly more than 75% or “three quarters”, or about 5 years. Frankly, when I say 75% it is not meant in the precise sense. It’s sufficiently close to a “round number” (3/4) that it implies a more limited precision.

My guess is that you’re fighting your percentages on the margin: you’re out of slack given your current living arrangements. My 50-90% represents 5 different living arrangements and 3 different salaries. Rent and income makes the biggest difference.

Now onto the meat of the matter.

From a theoretical/experimental perspective, there are two challenges. I’m assuming you understand the difference between precision and accuracy. If not, then that’s a very important point. Accuracy reflects how close the model comes to the real world. If our model is a one-foot ruler, and accurate ruler would be 1.0000000 ft long. An inaccurate ruler may be 1.4756344 ft long. Precision refers to how well the ruler measures. Precision can be found statistically. If the ruler has 1/64″ graduations, it is a precise ruler. If it has 1″ graduations, it’s not very precise. So,

A 1.05 ft ruler with 1/2″ grads is somewhat accurate but not precise relative to a 1.3 ft ruler with 1/32″ grads which is very inaccurate but also very precise.

Note how instruments are called precision instruments, not accuracy instruments ðŸ˜‰ … that’s a good way to remember the difference.

With statistics, you can achieve very high precisions (goes as 1/sqrt(N), where N is the number of measurements…also follows that going from 1 to 10 measurements gives you a lot more precision than going from 10 to 20). You can never achieve a very high accuracy through lots of sampling. This is strictly model/method dependent.

Now, there are two inputs to understanding. There’s a sampling of data points in the real world (experimental). But there’s also a sampling of models (theoretical). The combination of these two yields the understanding. In general, the simpler the model, the easier it is to understand and do math with. Complex models require simulations or brain power because they can’t be handled analytically.

There are four ways to deal with this.

Mathematically: (Few points, analytical/linear equations—what you’re doing)

Statistically: (Many points, analytical/linear equations—Monte Carlo)

Computationally: (Few points, nonlinear equations—simulations)

Not possible yet: (Many points, nonlinear equations—the real world, the stock market)

What I did in the book to answer your question was to use the mathematical approach with a parameter range of different SWRs and plot them. I bet some will complain that they can’t tell if the graph says 5 years or 6 years. That was intentional, however. I don’t want anyone to use this approach believing it’s in any way precise.

It is followed by a section expounding on that problem.

As you say, a brilliant… or lets just say lucky investor could have retired in 3 years, starting a savings account in 2006, learning all about investments and then dumping it all in an index fund in, oh say, March 2009. One could argue that’s cheating/unreliable. It certainly is, but so are the equation projections.

The best method in my opinion is to use cash flow. Invest as you would in FIRE. Do a dry run. This will make it much easier to gauge the impact. However, if we do cash flow, I’d argue that SWR is no longer completely relevant. Dividend investing has different return characteristics than total return. Heck, you could even be in real estate (I prefer REITs) that would be even stranger. It’s also country specific.

In the future, I will definitely say “more than three quarters of one’s income for around five years”. In this sense my numbers are accurate, but not precise.

—

“I probably still donâ€™t get your point, because Iâ€™d rather be trying to quantify the model and sometimes wrongâ€¦ than refuse to quantify.”

The risk is that quantification instills a false (inaccurate) sense of confidence. Example: http://en.wikipedia.org/wiki/Long-Term_Capital_Management … here they had models where the real world was inaccurately but very precisely approximated (to the tune of billions of dollars) by Gaussians. As it turned out (to the loss of billions) the Gaussian wasn’t accurate and since the precision had been leveraged into huge bets, the company had to be bailed out.

It’s like taking your 1.23 ft ruler and having your geniuses work on increasing precision from 1/32 to 1/64 and making bets that now you can really measure the real world because you just doubled the precision. Then it turns out you were 0.23 ft off.

I hope this wasn’t too trite.

]]>Suppose we refuse to quantify the model because it is fuzzy. We can still say that ERE is good, and that saving more will to lead to ERE faster. However, then we can’t say things like saving $100/mo should lead to retiring around x years sooner. As someone actively pursuing ERE, being able to make these kinds of tradeoffs is helpful.

I probably still don’t get your point, because I’d rather be trying to quantify the model and sometimes wrong… than refuse to quantify.

PS: If you’d have said 5x 80%-85% I wouldn’t even have commented, because I would have assumed you were giving ranges for the optimists (5×80% => FI with 4.3% ROI after inflation and taxes) and the realists (5×85% => FI with 3.0% ROI after inflation and taxes). It’s specifically 5×75% that doesn’t seem FI-probable to me.

]]>Maybe the reason I react so strongly to fuzzy ERE math is that I’m currently fighting tooth and nail for each percentage point of savings. You mentioned saving anywhere from 50%-90% but here’s my last few months (81%, 81%, 80%, 84%, 77%, 74%, 70%). What I’m doing is fighting hard to drive my expenses down — for each percentage point — precisely because it brings ERE that much closer. For me, 75% vs 80% is not a wash: it took a fair bit of effort, and it should pay off with a whole year less 9-5ing, give or take quite a large fudge factor.

I don’t want you to have to qualify every number you use… but I also don’t think anyone is hitting FI after five years of 75% savings (unless they are very skilled at investing). Of course, your big picture ideas continue to stand regardless of my nitpicking, and it’s these big picture ideas that make your site so great!

PS: If you want to give Wall Street a shot, let me know. I like the way you think, and I could probably make it happen (if not today, in a few months or a year)

]]>I’d really hate for anyone to make blanket assumptions about the percentages I mention. I remember reading in Numerical Recipes (book about computational math) in terms of whether to normalize your statistical set with N-2, N-1, or N. What they said, and I paraphrase (and fully agree) that if the choice makes a difference in the statistical conclusion you’re trying to make, you’re probably on thin ice.

This is also why specific number questions and answers (without considering the fuzzy factor) concern me. Anyone wishing to pursue this should be able to navigate the land for this (or hire a CFP to do it).

To me, there’s little difference between 75 and 80% (my savings rate has been anywhere between 50+ and 90%) If this difference matters, we’re splitting hairs. There’s also little difference between 5 years and 6 years. It’s a little bit like becoming a millionaire. I was briefly a millionaire in my native currency in 2007, not in 2008 and 2009, but then again in 2010. Expect to cross the mathematical point several times. What matters is the probability of staying at the right side of it.

I think the worst possible conclusion one can draw from my statements is that if I save exactly XX% then I can quit after exactly N years. Yes, this can be shown mathematically, but the assumptions never hold exactly and therefore the conclusions don’t either.

Makes sense?

Maybe I should be more careful in my statements whenever I use a number. To me the dangers of “math” is intuitive; probably that whole computational physics background.

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