Barry Barnitz wrote:Hi all:
I have fleshed out the wiki page : Low Volatility Index returns - Bogleheads.
regards,
You've made some great improvements.
Barry Barnitz wrote:Hi all:
I have fleshed out the wiki page : Low Volatility Index returns - Bogleheads.
regards,
Akiva wrote:Barry Barnitz wrote:Hi all:
I have fleshed out the wiki page : Low Volatility Index returns - Bogleheads.
regards,
You've made some great improvements.
The minimum volatility index seeks to lower volatility by using an optimization of variance minimization. The low volatility indexes employ a non-optimized approach based on historical volatities.
And one suggestion:
At the bottom of each table listing the returns of each index, you have 5 and 10 year standard deviations. I think you should also include 5 and 10 year geometric average returns and then 5 and 10 year sharpe ratios using that data. (The point is to be able to compare them to the regular index rather than against each other as you allow for further down on the page. You can then see if the returns are more or less than the historic 2% negative return to residual volatility would account for and how much or little the volatility reduction helps your Sharpe ratio.)
I think some downside-risk metric like Sortino or SDR Sharpe would interesting as well because these indexes might have different skew than the underlying market-cap ones. My personal preference would be to use SDR Sharpe over Sortino because SDR Sharpe and normal Sharpe are on the same scale and can thus be compared. So it is easy to see the effect of skew and whether the skew is positive or negative.
Akiva wrote:FWIW, the relative improvement here is absolutely phenomenal and much better than I would have intuitively expected. Even if you go in and subtract 2% from all of the MV indexes returns (and thus assume that the volatility factor will have 0 expected returns going forward). The lower volatility of the MV index still results in your geometric returns being slightly higher and your Sharpe ratio being about 60% better.
Barry Barnitz wrote:Unfortunately, adding all of this is way beyond my rather feeble spreadsheet skills. However, the spreadsheets are open for anyone to edit, so all that is necessary is for the skilled to select "view the spreadsheet in google" and begin editing. I have begun to provide CAGR data.
regards,
Akiva wrote:Barry Barnitz wrote:Unfortunately, adding all of this is way beyond my rather feeble spreadsheet skills. However, the spreadsheets are open for anyone to edit, so all that is necessary is for the skilled to select "view the spreadsheet in google" and begin editing. I have begun to provide CAGR data.
regards,
I'd do it for you, but I don't know how to create an area of the spreadsheet for "background calculations" that will feed into the numbers but not display on the webpage. Can you explain how to do this?
steve r wrote:1988 to 2012 MCSI Wold MV and other weight schemes data
A makeshift efficient frontier would clearly include MV ...
Barry Barnitz wrote:As far as I can surmise, the best way to handle computations that can't be derived by a single cell formula on the front tab is to create a new tab within the sheet (in google this is the + sign in the left bottom margin, which says "add sheet" when you hover your mouse over it) and then perform the necessary computations. The final computed cells can then be placed on the front tab by referencing the cell.
Akiva wrote:[The academically interesting thing is that MV doesn't have a size or value tilt and still manages to to dominate (be both up and to the left of) the market cap weighted one. So presumably the efficient frontier would include MV, value, and small-cap portfolios at a minimum. (Though an interesting open question is whether you can do the MV thing in a way that incorporates a value and small-cap tilt.)
nisiprius wrote:3) In the words of Jeremy Siegel--let me note upfront that he says the stated assumptions are not true and that "fundamentally-weighted" indexes are better--but, nevertheless:Equal weighting is one of an infinite number of non-market-cap weightings. It's not clear what special properties it's supposed to have. I cannot for the life of me see some obvious reason why I'd want to own the same dollar value of Zimmer stock and Exxon Mobil stock. It just seems goofy to me. Can anyone give any reason other than "it outperformed the cap-weighted S&P?"Capitalization-weighted indexes... under certain assumptions give investors the "best" tradeoff between risk and return. That means that for any given risk level, these capitalization-weighted portfolios give the highest returns, and for any given return, these portfolios give the lowest risk. This property is called mean-variance efficiency.
grayfox wrote:I believe that from Modern Portfolio Theory (MPT) there is a portfolio known as the Tangency Portfolio which lies on the efficient frontier and which has the highest Sharpe Ratio. Every investor is supposed to hold a combination of the risk-free asset and Tangency Portfolio. On the Capital Asset Line (CAL) that goes between the risk-free asset and the Tangency Portfolio.
grayfox wrote:Now my question is: What is the Tangency Portfolio in real world? Is it cap-weighted Total Stock Market Index or cap-weighted Total World Stock Market Index? Or is it something else?
magician wrote:grayfox wrote:Now my question is: What is the Tangency Portfolio in real world? Is it cap-weighted Total Stock Market Index or cap-weighted Total World Stock Market Index? Or is it something else?
Something else.
It won't be just the stock market; it'll be stocks and bonds and real estate and baseball cards and so on.
Rodc wrote:If the results are completely known already the method results in no significant new information; we all knew min variance stocks/bonds portfolio was historically about 30/70.
And yes I have strayed from one topic to a related topic; conversations are like that.
The more I think about this the more nonsensical it seems to be.
If one is building a diversified portfolio of stocks and bonds and one ignores expected returns and only looks at variance that completely ignores the rather important fact that stocks have a much higher expected return than bonds. That makes no sense at all. Might be valuable for a hedge fund that is willing to take on leverage, though may well blow up in their face, but is of no value to anyone here.
If one applies this, like the iShares funds to only a collection of say a couple hundred stocks it makes sense, especially if one sticks to large caps, to assume they have the same expected return so you can ignore expected returns. But then you must estimate expected variance (risk) of each individual company going forward (and correlation), like somehow this is a constant, like markets don't change and like this is not swamped by noise. Boy does that sound like a shady business. I might buy you have a hope, sort of or in a relative sense, to estimate the future variance of a large well defined sector (say stocks vs bonds, or large stocks vs small), but of individual companies? No way does that make sense.
grayfox wrote:Suppose asset A is stocks that has sigmaA = 20% and asset B is CDs that have sigmaB = 0 and CD returns are uncorrelated with stock returns, so sigmaAB=0.
xA = (0 - 0)/(.20^2 + 0 - 0) = 0 and xB = 1 - 0 = 1
The minimum variance portfolio wlll be 100% in CDs.
Wow! All that math to show what your grandmother already knows!
In fact I tried finding minimum variance portfolio for VTSMX (stocks) and VBMFX (bonds) over some period and the answer was something like 97% in bonds VBMFX and 3% in stocks VTSMX.
Well, if you are putting in assets like CDs that don't have nominal volatility but have real volatility, then you have to do the calculation in real terms to get a meaningful result.
StartDate Dec-1996
EndDate Dec-2012
VTSMX VGTSX VBMFX
AvgRet 0.06142 0.04746 0.05824
SD 0.16958 0.19128 0.03514
Correlation Matrix
VTSMX VGTSX VBMFX
VTSMX 1.00000
VGTSX 0.87068 1.000000
VBMFX -0.05143 -0.002638 1.000000
Portfolio weights:
VTSMX VGTSX VBMFX
0.0504 0.0000 0.9496
E[R] 5.839%
SD 3.29%
grayfox wrote:Well, if you are putting in assets like CDs that don't have nominal volatility but have real volatility, then you have to do the calculation in real terms to get a meaningful result.
Yes, maybe with CDs it wold be better to do calculations using real returns.
But, here's a case I ran to find minimum variance portfolio using monthly Yahoo data.
grayfox wrote:I think it shows that if you use both stocks and bonds and form a min variance portfolio, almost everything goes into the bonds.
Because the bonds have about 1/5 the volatility of stocks, the solution is to weight bonds heavily to get lowest volatility.
I'm thinking it would make more sense to form a min variance portfolio only with stocks.
Then you mix the min-variance-stock portfolio with bonds to get the complete portfolio.
Summary
In smart-beta indexes—such as fundamentally weighted and minimum-volatility indexes—stock weights are based not on their market capitalizations, but on some alternative formula. We have argued that the added value of smart-beta indexes comes from systematic tilts toward classic factor premiums that are induced by these alternative weighting schemes. We also showed that smart-beta indexes are not specifically designed for harvesting factor premiums in the most efficient manner, but primarily for simplicity and appeal. For a number of popular smart-beta indexes, we have discussed the main pitfalls, and how investors may capture factor premiums more efficiently by addressing these concerns. Finally, it is important to remember that although passive management can be used to replicate smart indexes, investors should realize that, without exception, smart indexes themselves always represent active strategies
Thus, equally weighted indexes are better described as strategies that try to exploit a possible difference in return between large stocks and even larger stocks. Equally weighted indexes are thus able to profit only partly, at best, from the small-cap effect considered in the literature...
frequent rebalancing is required to maintain equal weights. As this rebalancing involves selling recent winners and buying recent losers, this tends to go against the momentum effect..
In our view, therefore, a traditional capitalization-weighted (buy-and-hold) index of true small stocks is a more appropriate and also a more efficient way to capture the small-cap premium...
hafius500 wrote:FYI:
Indexuniverse March 2013- David Blitz - How smart is 'smart beta'?Summary
In smart-beta indexes—such as fundamentally weighted and minimum-volatility indexes—stock weights are based not on their market capitalizations, but on some alternative formula. We have argued that the added value of smart-beta indexes comes from systematic tilts toward classic factor premiums that are induced by these alternative weighting schemes. We also showed that smart-beta indexes are not specifically designed for harvesting factor premiums in the most efficient manner, but primarily for simplicity and appeal. For a number of popular smart-beta indexes, we have discussed the main pitfalls, and how investors may capture factor premiums more efficiently by addressing these concerns. Finally, it is important to remember that although passive management can be used to replicate smart indexes, investors should realize that, without exception, smart indexes themselves always represent active strategies
- Fundamentally Weighted Indexes
- Low-Volatility Indexes
- Maximum Sharpe Ratio Indexes
- Momentum Indexes
- Equally weighted indexes
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