Portfolio Optimization Software?

I've finally gotten to the point will I would like to optimize my portfolio using MPT.
I'm looking for some software (preferably free) that would allow me to run what/if scenarios.
Nothing fancy, since I'm planning on investing is ~5 Vanguard Funds (Large/Small/International/Growth/Value), but I'm curious what the historical performance of various weightings would produce in relation to the risk.
Any pointers would be appreciated.
Thanks-D
Reply to
sawyervillers
IMO the assumptions necessary to such an effort will tend to involve a high margin of error. E.g. you'll have to choose a timeframe for the average return of each category of stocks, and then weigh how meaningful this timeframe is. Some of these categories also do not even offer much historical data, so for them the statistical significance of "historical return" and related parameters is going to be low. For categories where data is sparse, the caveat "past performance is no guarantee of future performance" becomes particularly important.
I am sure one can buy such software, but mostly I think it will enrich its manufacturers, not you or anyone else. They're really selling snake oil, to a large extent, IMO.
I suggest you experiment a bit with the free online asset allocating tools linked at
formatting link
. This would be a wise choice IMO in particular because you're considering "just" the five Vanguard funds, which seem a fine set of choices to me, one which I doubt can really be beat except via luck in the future. Note the discrepancies from one tool to the next, even when using ostensibly the same set of assumptions. To me, these differences do not mean one tool is better than the next. Instead, it means that the margin of error is somewhat wide when allocating one's assets. It's a crap shoot as to how much tweaking will yield the optimum portfolio for the future.
Reply to
Elle
If you have the return series, you can use Solver in Excel to compute the historical optimal portfolio using by minimizing the portfolio return variance subject to the constraint of the return exceeding a target level and the portfolio allocations summing to one. I think some web sites discuss this.
Given expected returns, volatilities, and correlations one can use the online tool of William Sharpe (of CAPM fame) at
formatting link
to find the optimalportfolio.
A programmer can use the fPortfolio package
formatting link
the free R statistical program or can write a program in C++ orFortran (there are other possibilities) and use one of the publicdomain optimization codes in those languages. The inputs for portfoliooptimization are estimated with error, as noted by another poster. Awalk-forward test where portfolio weights are computed at each timestep using information known at the time can show whether portfoliooptimization is useful in a given context.
Reply to
beliavsky
Can't help you much on the free part, but we use SunGard's Planning Station and AllocationMaster modules. They do what you are asking. You can enter in a real or hypothetical set of asset holdings and it will give an expected return and std dev. The fund info is pulled from the internet. All you need is a symbol. It also runs Monte sims. SunGard offers a free 30-day trial to financial planners.
The software focuses on Modern Portfolio Theory, which most others seem to neglect. Plug in the assets to be analyzed and you can see where the porfolio lies on an efficient frontier. We usually find that the clients portfolio doesn't even lie on the frontier, meaning that there is a portfolio that can achieve higher expected returns for equal risk or equal returns for less risk. Holding all other variables constant, that's hard to argue with.
Reply to
kastnna
Thanks to all that answered. Sounds like it's time to break out Solver (per Beliav)...
As Kastnna indicates above, the goal is to get on the efficient frontier. Even though most of the big indexes have increasing correlation recently (small/large caps & international funds), there is enough to make it worthwhile.
It's been a few years since I did optimization (heck, it's been a few years since I calculated correlations and volitilities, but heck, since I believe in MPT, and am staking my financial future on it, I better understand the magic inside the black box.
Regards-D
Reply to
sawyervillers
IMHO the issue is not optimization per se, but rather exploring how the components of your portfolio interact with each other to move you towards the efficient frontier - towards it, not on it!
The MVO software available at
formatting link
is inexpensive and good to use for this.
The REAL problem with doing this is to get historical monthly total return data for each of the funds in your portfolio (or candidates for possible substitution or addition to it). I have spent considerable effort doing this over the years and now have 14 years of data on some 90+ funds I look at. These are put together from Reuters data service as well as manual corrections based on data as needed from fund web sites, yahoo, etc. Emphasis on MANUAL data corrections. All the data services are good on NAV values, usually dividends, but very poor on capital gains distributions. That is the weakness of this approach.
A. Bruce King
Reply to
A. Bruce King
A good place to look for total returns of indices, especially style indices, is the site of Professor Ken French,
formatting link
. One could test how high the correlation is between those returns and those of comparable index funds.
The major databases of mutual fund returns used by academics are those of CRSP and Morningstar, and there is a paper comparing their accuracy at
formatting link
. One can get more accurate estimates of volatility and correlation using daily rather than monthly returns, with the caveat that the computed correlations of foreign and domestic stock funds may be downwardly biased due to nonsynchronous trading -- adjustments can be made to account for this.
Reply to
beliavsky
wrote
How does using daily returns vice monthly produce "more accurate" estimates?
The only way to gage accuracy is if the actual values of volatility and correlation are known. One can (and people do) use statistical science to generate numbers from the data, but the leap from economics to an assumption that market numbers reflect science is enormous.
Reply to
Elle
On Feb 22, 10:01 pm, "Elle" wrote:
Theoretically, sampling a Brownian motion at a higher frequency produces more accurate estimates of its volatility.
Empirically, the study
Forecasting Volatility Financial Markets, Institutions, and Instruments 6 (1), 1997.
formatting link
(p53 of the PDF file) "With regard to calculating historical volatilities from daily versus monthly data, the table shows that for the longest horizon, 24 months, computing the volatility forecast from 5 years of monthly historical data gives the most accurate forecast, while for the 6 month horizon, forecasts constructed from (some amount of) daily historical data had the lowest RMSE. At the 12 month horizon, results were mixed, with monthly beating daily for 2 series, daily beating monthly for one, and one tie. Again, the GARCH model performed very well for the S&P 500 index volatility, but not for the other series, with RMSEs increasing sharply for longer horizons."
So if one is willing to change allocations at a frequency of every 6 months or higher, volatility estimates using daily data may work better. Its an empirical question.
One can study whether volatilities computed using daily vs. monthly data produce better forecasts of future volatility (which is also measured with some error) and whether portfolios constructed using daily volatility estimates have a better risk/return tradeoff.
Reply to
beliavsky
? x??V?Ü6 Ýû+¸Ê?8EI4«HQ (ºÐÈôXYr$y ÿ}%Û3??..0×ÉCòðPï?'6½;²5êÏóGåm­}ÿä?ÞÑ|â÷/?ê=®?/?>ñ??9ÐëWo_½¦¡??o£Oï~µ?Ë/??û?FÕÖxW×õGçã ú?UH5î\;Nrug?c¿½ý´y+`ÅÓÁ~ï²?,?´rtâD½LJë1¨ÄÄ1??"ù?.?d¬I3)×Üw¥},?»a??¨QÆ?Jb÷Þ!{|ã44?Ôá?é?@êÂ*Ý??Ã$¦Aì?1qs?5ç×"usr?5¾?Ü5Åäõù íè?xÿ¨W3ÐøÉM*4ÈöhT?fdJ??ÌNwÁ;?FJA5R¬/îûQ?cL=»sû??&»GWýè?ä?ê?Xÿ/;~ó?û»®?ÑÅhÞÚ6?ø¿0^HôÀÙJªe(6jý|{sÇù?:?#tAY;(ª~°?CÑ/54?6Ò>B¿uæ$t?hÙéy÷uA»ë??oPá+ûK?ï0? j?n?¼:v?ÑÚÌHÉA"U?WèD?¦QÙÌ%à*5]ý]PûLüSõ*Fâ¬;oý µQh??yµXWÕg:;tPsHÊ8p$ñÉSrØX4«??yÒV?^pÎTÉ??ø@Ç1?ïò92??3?*§&=?4©jLÛr`!Zð=j?ë?¥H?ÃÀ9?½Ò@ÍTù(0ðÿd^ ?;9Í\f|?ái?i?zæ´?¨???o?f ¬Îù?=?\0)|De=B¦0gtyY?Î8ufòÆÖÿlÜøê?$·2Ö.ÒuB­õº?R??_8ÌôS??(0 k;»¥½òðv%?1?çé?SâPÓg Üä~0A??! ?½_ÕLZÉyÌB?dk´¼?a?TÁ8ð( UøÛ
Reply to
Elle
Please excuse my naivete, but I was reading Bernstein's _The Intelligent Asset Allocator_ and he writes that it's really only possible to determine the portfolios that lay on the efficient frontier in the past. IIRC, he goes so far as to say something along the lines that those forecasting the efficient frontier might also be talking with Elvis.
Given this, I assume this software helps determine if a portfolio _was_ on the efficient frontier. Bernstein indicates that chances are that it wouldn't have been. But how useful is looking backward for performance? He also indicates that future efficient frontiers are very different than those in past.
I'm probably missing something since there's obviously a market, but why would someone use this software?
Reply to
lorax
Discussing things with you is a waste of time. You are always demanding proof of statements made by others but rarely provide evidence for your own half-baked theories and assertions. Judging from your comments in this newsgoup you know little about investing or financial theory but make a lot of strong accusations ("snake oil" salesman, "numerologists"). Professor Figlewski, the author of the paper I cited, is a respected researcher in finance. The paper I cited is a good introduction for someone interested in volatilty forecasting, but it is certainly not the last word. It does not try to "sell" anything -- don't smear him!
I have a CFA and PhD in physics, have worked as a derivatives professional for about 10 years, and I read the major finance journals. I have been posting to this newsgroup for some time, and people check my history to determine my credibility. You seem to believe there is no expertise in finance other than your own. The newsgroup would be much better off without you.
Reply to
beliavsky
wrote
I don't know about "demanding," but I do think that the value of this group hinges largely upon critical examination of posts and asking questions where things are not clear, like my query about your claim that market behavior is necessarily that of Brownian motion. I noticed you ignored this point, when of course there is a meaningful discussion that might shed more light on from where you are coming and from where I am coming.
I don't care about credentials. Answer the questions, or not, and be revealed in these fashions. I am actually still surprised at your confusion over the meaning of statistical "confidence level."
I don't think you know my theories. Either way, ask a question about them, and I will try to respond.
Reply to
Elle
"lorax" wrote
Indeed. Any thoughtful person will note this. It's the basis for the disclaimer, "Past performance is no guarantee of the future... "
I do think that's a fair statement to keep in the back of one's mind.
snip
OTOH, I think an understanding of economics, mass psychology in the markets, and similar does allow one to hypothesize meaningfully about what the future holds for stocks and bonds. Nothing's guaranteed, but people need to plan, so we do our best, on the assumption--outlandish or not--that people do not change too much, so our societies won't change much (or they change imperceptibly slowly as far as markets are concerned, over the course of a lifetime), and there will always be a demand for the latest gizmo or super-duper service, which is often an offshoot of today's large company. (So sayeth the "large value" category of investor.)
Reply to
Elle
Like most things, the software isn't perfect. EF is a comparative tool. The most common use is to compare a clients portfolio to the efficient frontier. Of course this means that we must have both the client's portfolio (simple to obtain) and an efficient frontier (not simple to obtain). It also shows how other hypothetical portfolios and/ or changes to the clients portfolio will bring it closer to or farther from the EF.
Bernstein's argument is valid but somewhat utopian (read: childish). He suggests that because perfection cannot be reached (a truly efficient frontier), the whole theory should be scrapped. The software's EF is probably not perfect but if its close, and especially if its better than the clients current holdings, then its an improvement. And that's a good start.
A chance to improve your situation is beneficial even if it is not maximum improvement!
In three years I have yet to see a client's portfolio that lies to the left of the program's efficient frontier.
Reply to
kastnna
In article ,
...
I don't think that is his argument; at least that is not how I read it. He points out that what emerges from MVO programs is highly sensitive to the details of the current/recent volatility and correlation data. With the consequence that from a largish universe of asset classes, the generated points on the EF are not stable over time, even relatively short periods of time.
His discussion may be misleading (almost necessarily so, I think, in that it is popular in nature and does not really go into what the optimizers do and what constraints can be placed on them). I wonder (and do not have one around to play with to examine this) whether these things do well if limited to a preselected smallish ( In three years I have yet to see a client's portfolio that lies to the
Well, by definition it can't be. And almost any "seat of the pants" portfolio could probably be improved, as you suggest, by looking at MVO optimizations, allowing consideration of (but not automatically indulging in) substitutions of assets not considered by the client.
Bernstein certainly doesn't reject the notion of the efficient frontier; I read him as cautioning readers not to use MVO programs uncritically.
Reply to
Michael Siemon
Sorry Michael, I did a pretty poor job of clarifying myself above. I worded it pretty poorly.
FWIW, we can plug in as many or as few asset/indexes as we choose. The asset mix we use to simulate an efficient frontier consists of a bunch of ETFs that attempt to approach the market portfolio as close as possible. As you implied, the difficult part is generating a perfectly efficient frontier that actually has a tangency to the market portfolio. I an almost certain that our frontier is not 100% efficient. What we have found to date, is that no one has brought us a portfolio that is any closer. Our market portfolio was created by some very bright minds that actually collaborated with Mr. Markowitz while designing the software.
Keep in mind, we use MPT as a sales tool not as a scientific research method. We don't have to be perfect (no one is), we just gotta be better than everyone else. Our new prospect meetings hopefully go something like this: 1. The potential client brings us a portfolio 2. We enter it into the system 3. We show the client that a more efficient portfolio can be created using about 12 ETFs. 4. The client decreases risk without sacrificing returns. 5. We get new client, new client gets more efficient portfolio than he had before. Everyone's happy!
Reply to
kastnna
How confident are you that the efficient portfolios you generate for clients do better, AFTER they are constructed, than the portfolios clients come in with? Have you studied the level of outerpformance, in terms of Sharpe ratios?
Reply to
beliavsky
"kastnna" wrote
How come you don't word this to reflect the reality of what you're generating? E.g. "the new client gets an allocation that, by certain historical measures, would have been more efficient than his old allocation."
I support diversifying so as to increase returns and reduce risk and expect your service is worth it (assuming the cost is reasonable). But I feel a little more honesty about the uncertainty of what the future holds is appropriate. Especially when academics like Robert Shiller are going around saying that, given a choice between (1) an all-stock or (2) all-inflation "protected" bonds portfolio, he'd choose the bonds.
Reply to
Elle

BeanSmart website is not affiliated with any of the manufacturers or service providers discussed here. All logos and trade names are the property of their respective owners.