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- Sector Prices vs. Summer Lows [view article]
- Performance Since the Dollar's Lows [view article]
- Second Quarter Sector Beat Rates [view article]
- Changes in P/E Ratios During the Current Bear Market [view article]
- Checking In on the All-ETF Portfolio [view article]
- Sector and Stock Performance Since Oil's Peak [view article]
- Bullish on Telcos [view article]
- International Revenues and the Dollar [view article]
- US Major Index and Sector Bull/Bear Filter [view article]
- Second Quarter Earnings Season Performance [view article]
- Q2 Sector EPS Growth [view article]
- Bespoke's Sector Snapshot (7/25/08) [view article]
loading ...Recent IYZ Articles
- Sector Prices vs. Summer Lows
- Bespoke's Sector Snapshot (9/4/08)
- Sector Impact on Tuesday's Market Move
- Sector Advance/Decline Lines (8/22/08)
- Market Performance Review: 8/20/08
- Bespoke's Sector Snapshot (8/20/08)
- Second Quarter Sector Beat Rates
- Performance Since the Dollar's Lows
- Global IT Spending To Jump 8% This Year - Gartner
- Percentage of Stocks Above 50-Day Moving Averages
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Checking 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
Considine
Checking In on the All-ETF Portfolio [view article]
To Skjellifetti:I address this specific Taleb-type argument in an article written in Feb:
seekingalpha.com/artic...
People who point out these individual events and say that portfolio theory can't "predict" such events are really missing the point. There are events like 9/11 that are impossible to model in the short term, but increased perception of risk in markets (via volatility and implied volatility) is a very useful signal with considerable information content. Anyway, for the detailed discussion of Taleb and model considerations, black swans, etc., see that article.
Reply
Considine
Checking In on the All-ETF Portfolio [view article]
To Tigisit:You can perform backtesting in QPP--and I have published a range of articles on backtesting here at SA and on my website. I am increasingly looking at writing articles where I go back and see how the forward-looking analysis has performed in real life--and this is one such article. I like SA in part because it gives readers a real time stamp tocheck if I really said something when I said it! I find it notable that so many people are now writing about the fallacy of the "decoupling" argument after the fall--but where were these analyses before?
Reply
Checking In on the All-ETF Portfolio [view article]
Emerging Markets = Diversification? www.indexuniverse.com/...Alisha you might want to read that article before adding Emerging Markets for purposes of diversification. Reply
Checking In on the All-ETF Portfolio [view article]
This may also show the limits of using MPT for divining the best risk-adjusted allocations. You have 5% devoted to Malaysia. But in 1998, during the Asian crisis, Malaysia, IIRC, put strict limits on the repatriation of international investments. That would have meant that 5% of your portfolio was suddenly unavailable. How does a tool like QPP account for this kind of risk (or is this uncertainty)?I'm not a big fan of Nassim Taleb. He is a terrible writer who is guilty of some egregious rhetorical fallacies. But his main point, that MPT has a terrible time coping with the unknown and that it is this kind of uncertainty that is the biggest source of investment losses, is spot on. That QPP would include Malaysia in a hypothetical best risk-adjusted portfolio is a good example of Taleb's point. Reply
Payton
Checking In on the All-ETF Portfolio [view article]
I'm not an active trader hence the reasoning that I invest heavily in ETFs but I acitively seek out a broad range including emerging markets such as EEM and ANDRE thinking this was an effective means to diversify so this article gives thoughtful insight on ETF portfolio building that I have thought about... ReplyChecking In on the All-ETF Portfolio [view article]
Good Analysis! Have you considered incorporating back testing into your QPP platform? ReplySecond Quarter Earnings Season Performance [view article]
I certainly agree with he above. Thanks! Reply