Portfolio Charts

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JohnnyFactor
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Joined: Sun Jun 05, 2016 3:44 pm

Re: Portfolio Charts

Post by JohnnyFactor »

Being from Canada, I've been using The Stingy Investor Asset Mixer and Periodic Table. They have full data on Treasuries, TSX, SP500, MCSI, and Gold in Canadian dollars going back to 1954 for some asset classes. I don't know where the data comes from, but I'm using it nonetheless. I import the annual returns into Google Sheets and play around with AA percentages to get a feel for the numbers.

Buying US ETFs and stocks in Canada is just as simple as buying CAD ones. Specify your account is in US dollars, contributions are converted on deposit, and trade away. No extra costs. The catch is, it can fluctuate by up to 30% annually just from currency exchange. It's a risk I'm not willing to take so I just buy CAN-listed US and Intl. index ETFs.

Considering the US makes up half the global economy, it's not unreasonable to keep your site US-only. International would be nice of course but I'm reminded of why we have only, like, two Target stores here. All of Canada adds 10% to the bottom line, at most.

Tyler9000
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Re: Portfolio Charts

Post by Tyler9000 »

Thanks, JohnnyFactor. I appreciate the info, and also the Stingy Investor reference. I saw that a while back but lost track. It seems like a good resource.

BRUTE
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Re: Portfolio Charts

Post by BRUTE »

50% Small Cap Value
50% Emerging Markets

discuss.

Tyler9000
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Joined: Fri Jun 01, 2012 11:45 pm

Re: Portfolio Charts

Post by Tyler9000 »

It's basically the Swedroe portfolio of high risk/return equity assets but without the offsetting bond stability. It's a little too focused for my tastes, but I see the appeal.

BTW, I've been working a lot with the guy who maintains the Simba spreadsheet and there's a big update coming. One of the likely changes is that EM may be removed prior to 1985. The more we look into data before that date the less we trust it. Just something to think about.

But plug in International Small instead and it's still interesting. ;)

BRUTE
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Re: Portfolio Charts

Post by BRUTE »

where does the data come from, anyway?

Tyler9000
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Re: Portfolio Charts

Post by Tyler9000 »

The data is compiled in Simba's Backtesting Spreadsheet on the Bogleheads forum. The original sources are public information from all over the place -- Vanguard fund annual reports, index provider history, academic papers, and even some custom calculations that I (and others) have provided. The guy currently scrubbing them is very meticulous, and I appreciate his attention to detail. You can trace them all either in the Simba spreadsheet or in the individual Asset pages on the site.

FBeyer
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Re: Portfolio Charts

Post by FBeyer »

BRUTE wrote:50% Small Cap Value
50% Emerging Markets

discuss.
1) Drawdowns.
2) Backtesting for CAGR.

BRUTE
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Re: Portfolio Charts

Post by BRUTE »

drawdowns are much shorter than TSM. but they're hard.

brute doesn't really see an alternative for 2). history is pretty much all there is.

FBeyer
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Re: Portfolio Charts

Post by FBeyer »

Why compare to the TSM? Why not to a three part TSM TBM REIT? Why not compare to The Permanent Portfolio? Why not compare to the history of Aristocrat Dividend Investing? Your choice of reference is arbitrary. You can choose almost any other allocation and get a different profile. Is 9 years okay with you, just because something else is worse?

Looking at CAGR is the one thing I feel is the most misleading about portfolio backtesting. Testing is about seeing how the portfolio fares under different circumstances: Bubbles in the US, high inflation, oil crisis etc. Most people are looking for low volatility, stable returns or slow growth under a lot of different circumstances, if BRUTE is looking for high returns BRUTE should get itself[1] properly educated and stop thinking in terms of indexing/diversification and more in terms of being 'right' enough not to NEED to diversify in order to make money.

Also, the history of EM is bound to be different from the future of EM unless the total global economy is arranged in exactly the same manner as it was in the past. In case it is not, you need to figure out what is different now compared to then.

My bet is on infrastructure in the developing parts of Africa...

[1] I used to say himself here, but I figured that might not be the case...

BRUTE
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Re: Portfolio Charts

Post by BRUTE »

brute has actually compared it to many other ones, including PP and GB. 100% TSM is just a pretty common piece of advice in FIRE circles, maybe less so here. but MMM, jlcollinsnh, Curry Cracker, all recommend it.

and brute is not merely looking at maximizing CAGR. this portfolio seems to backtest very well in almost any economical climate. it does crash hard, but it historically recovers very quickly.

if hedged a bit by adding 15/15 of LTT/Gold or so, it has very short drawdowns - certainly much shorter than the 9 years of a TSM/TBM/REIT. it also survived the 2008 crisis much better than said 3 part portfolio.

of course history is bound to be different, but that is true for all portfolio choices based on historical data.

brute is always a little irritated when humans tell him not to chase backtesting or rely on historical data. historical data is the only data there is. if brute doesn't want to predict the future and time the market (he doesn't), then it's either history or diversification. there are no guarantees with past performance, but there are also no other guarantees.

FBeyer
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Re: Portfolio Charts

Post by FBeyer »

BRUTE wrote:...brute is always a little irritated when humans tell him not to chase backtesting or rely on historical data. historical data is the only data there is.
Be irritated all you want. Portfolio back testing without a prior hypothesis is a prime example of data dredging. https://en.wikipedia.org/wiki/Data_dredging

So, what was your hypothesis about AMERICAN small cap and emerging markets before you plugged those numbers into portfoliofinder?

There is also the very real issue of extrapolation:
http://stats.stackexchange.com/question ... rapolation

Portfoliofinder is a LOT of fun to fool around with. It gives a lot of pretty pictures and graphs, and it is the most easily misused tool for dredging because is it SO easy to see patterns in the sky that we didn't think of first ourselves. Here be dragons. There is a very real reason why a horde of data scientists and statisticians have dedicated their lives and education to the art of handling, reading, and analyzing data. Numbers are not just numbers, not even when they're very easy to come by.

BRUTE
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Re: Portfolio Charts

Post by BRUTE »

the hypothesis thing is definitely true. brute did not have anything to say about US small cap.

does (falsely) extrapolating get less likely with bigger datasets? for example, it's certainly (falsely) extrapolated if brute goes all-in on a stock that did well this year. but if a portfolio does well over most of 45 years, brute feels intuitively more certain. is that intuition wrong?

it is really quite tricky to find a fitting portfolio. brute wants his to be mostly passive, and actually values stability. and it might be true that he's engaging in over optimization in the past.

but there are tons of portfolios that do terrible on many accounts even in the past - so wouldn't using one of those be worse than making up one that at least worked in the past? (if it's not extrapolated too crazy, i.e. betting on a very specific stock from a 1 year dataset or so).

for example, while the PP might have been hypothesized before actually looking at the data, it would have historically limited gains pretty strongly. so it would be a case of maybe running into a future problem vs. almost certainly running into the problem the PP has had, always. (of course not applicable if the goal of the portfolio is not to grow, but just to protect existing money - which the PP seems to do).

in another example, 100% TSM would historically have led to 10 year drawdowns multiple times, and even a 13 year drawdown after the 2000 crisis. while that might happen to any of brute's over optimized portfolios, it has already happened several times to the 100% TSM.

the TFP mentioned by FBeyer still had 9 year drawdowns, and didn't do so well in 2008. it did survive 2000 remarkably well, and has been doing well after 2009 though.

point being, it seems like there is no free lunch.

Tyler9000
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Re: Portfolio Charts

Post by Tyler9000 »

As with most things, the proper approach generally requires a bit of balance.

As I've written elsewhere, relying solely on good backtested numbers with no understanding of why it worked (and may continue to work) is a bad idea. But making decisions based solely on dogma while ignoring history is similarly shortsighted. I like to think of the Portfolios page as helping the first group, and the Calculators as helping the second.
Last edited by Tyler9000 on Mon Dec 12, 2016 6:57 pm, edited 5 times in total.

stayhigh
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Re: Portfolio Charts

Post by stayhigh »

BRUTE wrote:50% Small Cap Value
50% Emerging Markets

discuss.
When you add gold and some bonds it looks very solid.

FBeyer
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Re: Portfolio Charts

Post by FBeyer »

BRUTE wrote: 1) does (falsely) extrapolating get less likely with bigger datasets?

2) for example, it's certainly (falsely) extrapolated if brute goes all-in on a stock that did well this year. but if a portfolio does well over most of 45 years, brute feels intuitively more certain. is that intuition wrong?

3 )brute wants his to be mostly passive, and actually values stability. and it might be true that he's engaging in over optimization in the past.

4) but there are tons of portfolios that do terrible on many accounts even in the past - so wouldn't using one of those be worse...

5) for example, while the PP might have been hypothesized before actually looking at the data, it would have historically limited gains pretty strongly. so it would be a case of maybe running into a future problem vs. almost certainly running into the problem the PP has had, always. (of course not applicable if the goal of the portfolio is not to grow, but just to protect existing money - which the PP seems to do).

6) the TFP mentioned by FBeyer still had 9 year drawdowns, and didn't do so well in 2008. it did survive 2000 remarkably well, and has been doing well after 2009 though.

point being, it seems like there is no free lunch.
I wish we had a white board and a conference room... I don't even know the financials, but the data part alone could take a few hours of lectures. From a data point of view I think these are good questions, I'll do my best to answer to the best of my current knowledge.

1) No. And Yes. :roll:
If 'the process that generates the data' is the same, then more data is better. If the process is different, you need to identify the characteristics of the process to know how to interpret the outcome. Economic conditions change over time, and so the process that generates returns differs over time. Every specific return at some point in time is a result of politics, investor expectations, actual conditions, current momentum and expected stability of returns over time. History shows that unstable times yield more than stable times. Times have been quite stable since the end of the second world war right? Many argue that the post-war buildup has given investors an unrealistic idea of the long term gains of general investments, ie indexing. Go back 70 years and 'things always go up'. Why is that necessarily the case for the next 30-40 years where you and I are supposed to live off of our investments?

Statistical analysis can only give you more information after you applied as much expert knowledge as possible. Math and graphs do nothing on their own, without coupling to domain specific knowledge. It is the most difficult task of the statistical consultant to goad that knowledge from the client before, during and after gathering data. The graphs support the hypothesis. You cannot form a hypothesis based on past data and conclude that you are right, you must conduct a new experiment to see if the hypothesis applies to newly acquired data as well. Pattern recognition is a discipline all on its own, and the alluring thing about pattern recognition is that you seem to get results from data immediately, but what you truly get is 'ideas to test' from past results. It's very hard to explain to people why concluding anything from a past pattern is not a result, but a suggestion. The confusion of the two is the basic pitfall of p-hacking. Expert knowledge on a domain is the pillar on which the data analysis and the pattern recognition rests, not the other way around.

More data means more power. Power means the ability to detect smaller effects/differences. The actual causality of the difference is up the expert to hypothesise on, then back to the statistician who has to help conduct a new experiment to see if the hypothesis is correct. That means that with a lot of historical data, we're quite certain that small cap value stocks HAVE indeed generated a higher return that the total stock market. Why that is is up to someone else to find out. whether that will be the case in the future depends on the underlying mechanism that generated the excess return.

TL;DR extrapolation works when you know you have the same conditions in the domain you're extrapolating to as the domain you're extrapolating from. That is why a higher sampling density on a closed interval gives you better statistics, but analytical forecasting from more data does not. You require expert knowledge of the subject to make efficient use of a forecast.



2) Uncertainty on the mean. By sampling over an index rather than a single stock you're averaging the effect of every single company out and try to capture the compound effect. By analysing more companies over a longer time frame, compared to one company over a short time frame you're simply getting a better estimate of the uncertainty on the mean, or the uncertainty on the CAGR is you will. An investor will most likely want to capture one-tailed outliers, not the average. Your knowledge of the CAGR is better. The improved statistics should give you a much better confidence interval when projecting into the future, yes. That is, if the underlying data generating process is still the exact same... If that is not the case, then the effect from the erroneous data generating model is much more important than the actual accuracy of your parameter estimates from past times. You can extrapolate quite well if you don't extrapolate very far, but you and I are most likely trying to extrapolate 30 years into the future with our lazy portfolios aren't we?

The intuition is not wrong, but rather off. You're more certain that the returns are actual returns, that the numbers are real if you will, rather than flukes of mispricing (fuck the EMH) but the continued realization of those returns in the future depends on point 1) above. The index is more well-priced, almost by definition, than single companies are. Whether the index is correctly priced is something else entirely.

Investments will make money if the fundamentals to make money are there and if the prevalent investor psychology is there to drive prices up. That is the basic issue with fundamental analysis: A vastly underpriced company will not rise in price until the rest of the stock market catches up. Are the fundamentals to keep driving the stock market up at the same pace as in the past there for the next 30 years?

3) If you want stability, why are we talking about a portfolio composed of the two most volatile stock indices? The Permanent Portfolio is designed to be stable. The Global Portfolio is designed to be lazy. Choose one of those instead. There is expert knowledge behind the design of those two, rather than being a back testing driven build.

4) Yes. Do you KNOW and UNDERSTAND why those portfolios fared badly in the past or can you just see that they fared badly by looking at the graphs on portfoliocharts?

5) The PP does exactly what it was designed to do: Preserve capital. It's exact performance based on what it was designed to do is, IMO, one of the reasons why so many people talk about it. This was not a CAGR/efficient frontier optimized portfolio, it had a specific outset and was built from first principles.

6) I pulled numbers out of my ass (PUMA). My point was not to find a portfolio with the smallest drawdowns in the past, that would most likely be the Golden Butterfly, my point was more that your choice of reference ie the TSM was arbitrary. Again, apply knowledge, then dig around in the data, not the other way round.

I know I don't know a lot of things. If I knew things, I wouldn't need to diversify my own investments...

BRUTE
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Re: Portfolio Charts

Post by BRUTE »

brute thanks FBeyer for the lengthy explanation, even though it just seems to confirm brute's uncertainty.

FBeyer is of course right about the PP, but preserving wealth is currently not brute's goal, creating more wealth is. thus, while brute accepts and likes stability like in the GB, he sees is as more of a bonus - he doesn't have much to lose yet and returns are more important. thus any portfolio that generates great returns while still providing stability would be perfect. this is in essence saying that brute believes there are things too good to be true. in brute's experience, most humans invest for the same reason they do 99% of what they do, to follow the herd. thus it wouldn't be surprising to brute if there is something out there that has both a higher CAGR and shorter drawdown periods. the GB already seems to prove that there is a certain amount of free lunch if not locked into the "stocks/bond - age" dogma.

edit: regarding stability/volatility, brute forgot to mention that he thinks anti-correlated volatile stocks can actually increase stability. kind of a nassim taleb thing maybe, where stability is not the opposite of volatility. it's of course uncertain if assets (or some assets) display these characteristics and will continue to do so. but certain assets seem to have correlated negatively to add up to a pretty stable portfolio, for example the PP and the GB.

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jennypenny
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Re: Portfolio Charts

Post by jennypenny »

@brute--There's no reason you have to go all-in on either safety or gains. At first, it's good to focus almost solely on gains. As your portfolio grows, you can take some money out of the 'gains' category and move it into safer investments. It's like how I periodically cash in chips when I gamble to (1) make sure my kitty is always small enough so that a dollar still looks like a dollar (no purple chips!), and (2) I don't give all my winnings back to the house. I've shifted money from stocks to bonds and now to treasuries and gold. After 25 years, the bulk of my portfolio resembles the PP but it was a slow evolution over time into that allocation. And I still have 10% in a trading fund that I will use as an income fund whenever we decide to live off of our kitty.

I'd say have two layers of allocation, the first being a designation of either gains or safety, and then within those another allocation with something like the PP for safety and whatever stock/bond recipe you like for gains.

Sorry if I'm derailing T9000.

ThisDinosaur
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Re: Portfolio Charts

Post by ThisDinosaur »

Tyler, what is the nature of your concern about the EM data? Is the earnings data *after* 1985 more trustworthy?

wrt investing Hypotheses, what is the proposed mechanism/reason for the outperformance of Small Cap & International Small Cap indices?

Tyler9000
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Re: Portfolio Charts

Post by Tyler9000 »

@ThisDinosaur -- The general rule of thumb for how the Simba SS prioritizes data sources is:

1) Known returns from a passive index fund currently traded on the market. It is often the Vanguard version, but sometimes other funds are used if VG is too active in their management.
2) Known returns from the underlying index that the modern fund tracks. This will be directly from sources such as CRSP and MSCI.
3) Reconstructed returns that follow the same methodology as #2 using good source data. For example, I rebuilt the full US stock history from Fama-French data, and another Boglehead did the same for US treasury funds using Federal Reserve data.
4) Other sources.

Long story short -- it turns out that #2-level data for EM starts in 1988 and there's no data available to accomplish #3. We've been using #4 -- a public PDF from DFA -- and recently dug into where those numbers actually come from. It turns out that they simply used 50% int'l value and 50% int'l small as a proxy for EM, but that's really a terrible assumption that does not track known good years even remotely well. So the data prior to mid-80's is getting nixed.

That doesn't mean I'll be removing EM from the calculators. I'm working on something too complicated to explain just yet, but it should be pretty cool once it's done.

WRT small caps, the classical answer is that the market dictates that things with more risk generate greater returns. I'm not sure it's that simple, but it's a good place to start.

Smashter
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Re: Portfolio Charts

Post by Smashter »

I just want to chime in here and say that Portfolio Charts is the best. I am emerging from an all day binge of this thread, as well as related Golden Butterfly threads on Bogleheads and MMM.

Tyler9000 is a freaking saint for always staying classy even when dealing with the most annoying, dense, and rude people the MMM board has to offer. As Brute mentioned, reading through those threads made me appreciate this community all the more.

A quick question for the Golden Butterfly brigade: what would be the best way to organize the GB for tax efficiency? I have a really good 401k and a Roth to work with. Is gold best held in the 401k?

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