Corporate High Yield Fund (COY)
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- Checking In on the All-ETF Portfolio [view article]
- Asset Allocation and the All ETF Portfolio [view article]
- Outlook for Select Sector ETFs [view article]
- Fixing Target Date Strategies: 'Target Date Folios' [view article]
- Exchange-Traded Funds and Closed-End Funds by Asset Class, Type and Provider [view article]
- Why I Bought Corporate High Yield Fund This Morning (CEF: COY) [view article]
- Stress Testing Risk Metrics Pays Off: A Case Study Portfolio for the Sophisticated Investor [view article]
- Eye on Corporate High Yield Fund (CEF: COY) [view article]
loading ...Recent COY Articles
- Checking In on the All-ETF Portfolio
- Fixing Target Date Strategies: 'Target Date Folios'
- Outlook for Select Sector ETFs
- Asset Allocation and the All ETF Portfolio
- Stress Testing Risk Metrics Pays Off: A Case Study Portfolio for the Sophisticated Investor
- Why I Bought Corporate High Yield Fund This Morning (CEF: COY)
- Eye on Corporate High Yield Fund (CEF: COY)
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Exchange-Traded Funds and Closed-End Funds by Asset Class, Type and Provider
on Jan 05, 2004| by
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Payton
Checking In on the All-ETF Portfolio [view article]
Delta,Thanks for the link to the article. I never would have come to the conclusion that the dealings we do here have such a STRONG impact on business abroad. In relation to S&P500, my favorite ETFs for diversification, ADRE and EEM have an r of no less than .6 over the last five years. Thats quite a pitiful performance. However, as a nonactive trader, I still like the idea of global markets ETFs for my portfolio purposes, and Geoff's article and the comments that ensue, are quite helpful and entertaining.
On Aug 04 05:21 PM Delta David wrote:
> Emerging Markets = Diversification? www.indexuniverse.com/...
>
>
> Alisha you might want to read that article before adding Emerging
> Markets for purposes of diversification. Reply
Considine
Checking In on the All-ETF Portfolio [view article]
SmartETF:It would be far more helpful if you published one or more articles about what you think is the best approach, how it works, back tests, etc. Simply claiming that your model is better and that you have out-performed by some measure over some period of time is not compelling. Also, publishing a portfolio and then revisiting it later and seeing how it has performed--as I did here--is a useful data point. QPP is consistent with the opinions of some of the very best minds in institutional research (Roger Ibbotson, David Swensen, etc.). This does not make it right, of course, but it is meaningful in my opinion. There may be better models in the world, but there are none that I know of that are as well documented both in stress testing and in practice.
Geoff Reply
Checking In on the All-ETF Portfolio [view article]
Smart ETF. Could email me about your firm´s services. solboy@hushmail.com ReplyChecking In on the All-ETF Portfolio [view article]
You used the term correlation; not I. Correlation refers to a form of dependency model, better known as linear correlation. If this is not the forum to express sophisticated methodologies, then why is it the forum to showcase simplistic ones? The theme was to highlight the de-coupling of indexing and correlation. That is what I was addressing.I have read your past posts and we obviously differ in several areas; but only because I’ve been in the business 25 years, have built models since the mid 80’s that have put me in the top 1% for two decades, and mostly read whitepapers, not trade magazines. In the future I would welcome a debate on your previous posts. In previous articles you cited LTCM as the exception, not the rule, I disagree. You note the underperformance of active managers, yet who determines who is active or who is a closet indexer? Two Yale professors recently came out with a new model that determines if a manager is truly active (based on 23 years of research). Truly active managers soundly beat the index after fees and expenses! BTW, I do not consider active managers to be the same thing as market timers. Taleb may be egotistical but he is right none-the-less.
I will love to resume this conversation in 10 years after you’ve experienced what is to come. My word of caution is to avoid absolutes, avoid getting sucked into the academic theories, and be careful who you choose to debate. I’ve chosen to fight the popular opinion my entire career; it’s a tough road. My best word of advice is for you to never stop asking ‘why’. As Kennedy once said “How could I have been so wrong as to trust the experts?” Don’t let a little criticism stunt your progress. I applaud your efforts and cherish your enthusiasm.
Reply
Considine
Checking In on the All-ETF Portfolio [view article]
To Andrew Muchmore:I am not sure what you are asking here...
Geoff Reply
Considine
Checking In on the All-ETF Portfolio [view article]
Smart ETF:No model is perfect and there are many ideas for better models. A forum like SA is a great way to show what a model says and then to go back and revisit it later to see how it did.
I do favor simpler models when they work and QPP has held up very well for what it is designed for--and this article is a case in point. The ultimate test of statistical models is that they work operationally.
If you have an operational model that is of value, I am sure that many people here would be interested in what it says. But how do we establish value? In a broad forum, it is by publishing positions / suggested allocations that can be benchmarked later.
There are so many complexities in how even a model like QPP deals with stationarity and correlation that this is probably not the forum. QPP does not assume stationary statistics or linear correlation, for example. I often show correlation matrices but QPP is not a so called Delta Normal Mean Variance model. I am not sure where you got that idea.
Geoff Reply
Considine
Checking In on the All-ETF Portfolio [view article]
Indexor: I just checked and it is up--must have been a glitch at the server farm earlier. ReplyChecking In on the All-ETF Portfolio [view article]
Geoff:You're web site is not working. Reply
Checking In on the All-ETF Portfolio [view article]
Geoff, I meant no offense, my goal is to help investors universally.First, Mandelbrot wrote his book four years ago and we had already built the same concepts several years before. So the fact he hadn't seen the models work doesn't mean they don't exist.
Second, I like your idea’s but I’m highlighting the weaknesses in your models and offering improvements to help; not to be critical. You choose to indirectly advertising QPP so I choose to freely suggest how models can be improved.
So the question is:
a) Do you believe normal distributions are better than stable distributions? I welcome this discussion.
b) Do you believe linear correlation is better than copula dependency? I welcome this discussion.
c) Do you believe a concept from 1952 called mean-variance can possibly be better than another Nobel winning formula created this decade? I welcome this discussion as well.
I’m not advertising our firm but will share our asset allocation mix as of July 22, 2008, the date of our last rebalancing.
2.00% Vanguard Health Care VIPERs VHT
2.00% Vanguard Industrials VIPERs VIS
5.00% Short QQQ ProShares PSQ
3.00% iShares MSCI Brazil (Free) Index EWZ
2.00% iShares FTSE/Xinhua China 25 Index FXI
3.00% iShares S&P Latin America 40 Index ILF
2.00% BLDRS Emerging Markets 50 ADR Index ADRE
3.00% PowerShares DB Agriculture DBA
2.00% iShares Dow Jones US Real Estate IYR
3.00% iShares GS $ InvestTop Corp Bond LQD
71.50% iShares Lehman 1-3 Year Treasury Bond SHY
1.50% Money Market Fund MMA
Because asset allocation models all follow a 3 step process I will describe the advantages in each step:
1) Step 1 (univariate model): a Stable ‘t’ distributions with GARCH features better determines the current risk & forecasted return of a security as opposed to a rear-view mirror approach based on normal distributions.
2) Step 2 (bivariate model): a copula dependency more accurately examines the current relationship between two securities as opposed to linear correlation based upon long-term averages.
3) Step 3 (multivariate model): ranking the bivariate models with Monte Carlo modeling to forecast produces an optimal mix based on current market conditions as opposed to Monte-Carlo modeling based upon long-term averages.
So you can see from our current allocation the risk/return trade-off for securities is unattractive in the current market conditions and the recent volatility is keeping investment out of securities which have traditionally low or negative correlation.
So you see I have only upgraded the basic attributes of asset allocation and continue to follow the same 3-step process as you and the other solution providers.
Again, I wasn’t trying to change the conversation over to EVT but was trying to address the blindness in risk modeling and offering a solution to the problem.
All the best - Reply
Considine
Checking In on the All-ETF Portfolio [view article]
Smart ETF: You always post this stuff to my articles and I have previously proposed to you that you show us a portfolio of ETF's that looks good on the basis of your models--which would be fascinating since Mandelbrot himself says that his approach to modeling is not yet practical for actual use. Let's see one of these better designed portfolios. ReplyChecking In on the All-ETF Portfolio [view article]
One contributor wrote: “it is impossible to ‘predict’ fat-tail events”. Yes, using traditional asset allocation models. I have used Extreme Value Theory for four years and have avoided all the major sell-offs, including 9-11, and the fun year of 2008. Our growth models range from +2% YTD to minus 4.5% YTD depending on the fund universe. Check out the latest books by Benoit Mandelbrot or if you prefer heavy reading, any of the recent books on EVT. ReplyChecking In on the All-ETF Portfolio [view article]
Finally an intelligent string of correspondence!Yes, the MPT, APT and follow-up portfolio theories rely on normal (arithmetic) distributions, henceforth ignoring fat-tail events. Converting to a stable (log) distribution exposes the tails to more accurately define the actual risk.
These traditional models rely on mean-variance which is why they predict 10% annualized returns (based on the past 80 years. It is ~ 7% over the past 180 years). Using mean-variance, your clients should have doubled their money since 1998; but in fact the S&P 500 is still down after 10 years. Making a bet on the law of large numbers is great if you have 50 years for a pay-off; I don’t. Markets move through economic cycles that reward equities positively on average 18.5 years (bullish) and penalize equities negatively on an average 17 years (bearish). It can take up to 20 to 30 years for an investor to break-even if invested at the market highs.
An upgrade can be made to mean-variance with a newer Noble prize winning formula (circa 2003) called GARCH (Generalized Auto-Regressive Heteroskedacity) that tracks the clustering of data.
The third problem with traditional models is that they assume markets are static as well as correlation. We all know that correlations increase as markets become more volatile. Why not have real time correlation models? You can upgrade linear correlation to a dynamic correlation by switching to a copula dependency model.
Upgrade your 1) risk analysis using stable distributions, 2) time-series using GARCH, and 3) correlation dependency using copula dependency. These upgrades significantly add to performance and are the underlying concepts of Extreme Value Theory. Reply
Considine
Checking In on the All-ETF Portfolio [view article]
Skjellifetti:Yes, but..you have taken a brief statement from a longer point. In the short term, portfolio theory models will under-estimate the probability of "black swan" events. If you expand the time horizon--even including these events--the models do well. If you are a short-term trader who needs to model the amplitude and duration of daily-monthly fluctuations in extreme one-off events, this is not an ideal model.
With regard to systemic risk in Malaysia, why are you so confident that this risk is not priced into the implied volatility? you MAY be right, but what is the evidence? This actually relates quite closely to the work that I did on credit ratings and implied volatility (also on SA).
Geoff Reply
Checking In on the All-ETF Portfolio [view article]
From your Feb article [my substitution]:If we have [$BLACK_SWAN], the short-term losses to any portfolio are likely to be far greater than Quantext Portfolio Planner or any other portfolio model can estimate. This kind of massive disruptive event is not what these models are capable of estimating.
...
Ultimately, portfolio models are perhaps most useful because they give investors objective tools to:
1. examine diversification benefits in their portfolios
2. estimate total portfolio risk (albeit not very well for market crashes, wars, epidemics, etc.)
3. estimate total portfolio returns in light of assumptions
It is point number two that I was trying to highlight. MPT is all about creating portfolios with the best return for a given amount of risk. But if we are doing a poor job of estimating risk, then it is not at all clear that we are, in fact, maximizing expected returns per unit of risk. Tools such as QPP may thus be giving us a false sense of security when they recommend, say, a concentrated position in Malaysia over a larger more diversified basket of emerging market stocks.
Reply
Muchmore
Checking In on the All-ETF Portfolio [view article]
Hey Geoff,I enjoyed the original article and am glad to see the portfolio held up well under pressure. I think this sort of statistical approach is much more useful the majority of analysis on this site, which is too often based on emotion and short term trends. Have you tried using this methodology to build a portfolio that places more emphasis on return and less on standard deviation? For the long-term buy and hold investors who have time to wait out the swings, such a portfolio would be preferable. Thanks for a great article! Reply