Archive for February, 2013

Comparison of Valuation and Expectations For Apple, Microsoft and Google

Tuesday, February 26th, 2013

While Apple’s price has dropped, Google’s price has risen.  Google has become a new darling, and Apple is experiencing ownership rotation from momentum investors to value investors, and possibly income investors. Microsoft is down on a trailing 1-year basis, but less so than Apple and nothing like the decline in Apple from its September 2012 peak.

Figure 1: Price Chart

Let’s take a look at valuations and expectations for those three companies, who compete in so many ways.

Figures 2, 3, 4 and 5 from YCharts, show Apple to have a lower valuation that either Microsoft or Google by forward P/E estimate, EV/EBITDA, EV/Free Cash Flow and yield.

At some point the attractive valuation multiple should provide some sort of brake on the price decline Apple has been experiencing.

If Apple were to raise its dividend, which is appear well able to do from either cash flow or cash reserves, it could also create a compelling yield opportunity attracting dividend income investors.

Figure 2: Forward P/E Estimate

Figure 3: EV/EBITDA

Figure 4: EV/EBITDA

Figure 5: Yield

Figure 6: Valuation and Options Metrics

Based on options implied volatility for the January 2014 options, Apple as the widest probable percentage price range, while  Microsoft and Google have approximately the same probability range.  At 2 standard deviations up and down, Apple has an options implied probability range of down 41.69% and up 63.88% (on a 1 standard deviation basis the range is down 24.53% and up 26.50%).  Microsoft and Google, however, have an approximate 2 standard deviation down 29% and up 40% range (1 standard deviation down 16% and up 18%)

Options probabilities are non-directional, so other hints are needed to gauge the balance of options traders expectations. The direction of the Put/Call ratio is one helpful hint.  The Put/Call ratio shows how much people are buying protection against loss (PUTs) versus buying gain opportunity (CALLs).

On an overall market basis, PUTs tend to outnumber CALLs (ratio greater than 1.00).  Here is a chart for SPY, representing the S&P 500, illustrating that point.  The ratio is shown in blue in the images below.

Figure 7: SPY Put/Call Ratio

The 1-day Put/Call ratio for Apple is above the 30-day average (a minor negative directional indication), but the 3-year plot of the ratio shows decline in the level of protection seeking behavior.

In any event the ratio is lower than the overall market — possibly due to less protection seeking and possibly due to more opportunity seeking.

Figure 8: Apple Put/Call Ratio

Microsoft’s 1-day Put/Call Ratio is minimal at 0.1 versus a 30-day average of 0.4.  The 3-year plot shows a decline in concern for protection versus opportunity.  That could be due to more opportunity seeking or less protection seeking, but the ratio shows the balance.

Figure 9: Microsoft Put/Call Ratio

Google’s Put/Call ratio looks more like the typical market, but with a rising level of protection seeking versus opportunity seeking.  The 1-day level is 1.1 versus a 30-day level of 1.0.  The 3-year chart, shows about a year of rising Put/Call ratios.

Figure 10: Google Put/Call Ratio

Figure 6 shows that Google has more institutional ownership than either Apple or Microsoft, and fewer analysts following it.  Google has the lowest percentage gain to the high analyst estimate and the highest percentage loss to the low analyst target; and the lowest percentage change to the average analyst target.

Apple is the opposite with the highest percent to the high and the lowest percent to the low.

Microsoft is between the two.

Also in Figure 6, the dispersion of Buy, Outperform, Hold, Underperform and Sell for the three stocks shows only Apple having any Underperform or Sell recommendations (5.26% combined), but also the highest portion of Buy or Outperform (75.44% combined).

Google by contrast has 65.79% combined Buy and Outperform, and Microsoft has 59.46%.

Looking at the high, low and average 12-month analyst target prices as an 18-month time series, you see Apple with a recently declining set of averages, and a narrowing high to low range.  The upgrades to estimates were mostly over by mid-2012. The downgrades were mostly over by January 2013.

Figure 11: Analyst Opinions Time Series for Apple

Microsoft’s targets are minimally changed since early-mid 2012 and have been in a fairly constant size range from high to low.  Downgrades for Microsoft are also minimal at this time.

Figure 12: Analyst Opinions Time Series for Microsoft

Google is still getting upgrades and has a rising average target price and high target.

Figure 13: Analyst Opinions Time Series for Google

Figure 6 shows that S&P has similar 3-year estimated EPS growth projections for Google and Apple (9% and 10% respectively), an a lower 6% for Microsoft.  Comparing the forward P/E estimate to the projected growth rate, you see a PEG of about 1 for Apple, 1.6 for Microsoft and 1.9 for Google.

In terms of S&P current Fair Value, Figure 6 data for market price and Fair Values indicates undervaluation of 13% for Apple, 16% for Google and 27% for Microsoft.

S&P expects both Apple and Microsoft to strongly outperform the S&P 500 in the year ahead, and Google to be only a market performer.

Each stock offers distinctly different risks and opportunities.

Google poses the greatest disappointment risk and Apple the least.

Google is the momentum play and Apple is the “falling knife” that on paper is a great value, and a pretty good yield.

Microsoft is comparatively price stable with an above average yield, and perhaps more risk adjusted upside potential than Google.

Looking at risk and risk adjusted return, here are the 3-year Beta and 3-year Sharpe Ratio metrics for each stock as of January 31, 2013:

  • AAPL: Beta 0.75  Sharpe 1.22
  • MSFT: Beta 1.17 Sharpe 0.54
  • GOOG: Beta 1.12 Sharpe 0.18
Unfortunately, the recent Apple price performance has been so severe that the comparison is not terribly useful, but there you have it anyway.
On a quarter-by-quarter basis for the past 10 years, here is the difference between the total return of each stock and the S&P 500.
Figure 14: Apple
Figure 15:  Microsoft
Figure 16: Google
You make your choice and pay your money — we hope this data will be of assistance to you in your decision.

We own some Apple and some Microsoft.

Options Implied SPY Price Probability Ranges And Valuation

Wednesday, February 20th, 2013

Individual options traders place their bets on the direction and magnitude of price change for securities. The volatility implied in the price of an option is the basis for projecting the trader’s price probability assumptions.

Because there is a buyer and a seller on each side of a trade, options volatility data is agnostic as to direction. You need to use other tools to decide whether up or down is more likely, but the options can tell you a lot about expectations as to magnitude of change.

This table shows (as of this morning 2013-02-20) the probable price ranges for SPY the S&P 500 proxy) through the April expiration and the January 2014 expiration, and also the implied dividend yields and P/E multiples that would result from those prices, based on current dividends and earnings.

There is a lot more to think about than just this, but it is an interesting window to peer through and consider in the overall mix of data when thinking about market prospects.

It is important to note that options traders opinions change quickly and move around quite a lot, so this is a snapshot in time of fast moving opinions.

As of this morning, for example, traders saw a 10% chance of the price of SPY dropping to 142.78 by the April expiration and 129.40 by the January expiration. That January price level implies a dividend yield of 2.51% and a P/E of 11.80.

Similarly, they saw a 10% chance of the price rising to 164.38 by the April expiration, and 181.17 by the January expiration, for an implied yield of 1.79% and P/E of 16.52.

The 10% end points encompass the 80% probability range for prices.

This data was obtained using the tools provided by OptionsExpress.

Market Conditions for Gold

Tuesday, February 12th, 2013

There are many views on the future price of gold, with a strong preponderance for higher prices. It’s tough to parse through them and to decide which to rely upon. This article provides some statistical information about investor views that may help.

SOME OF THE QUALITATIVE ARGUMENTS

On the positive side — central banks are strong net buyers (the U.S. not included).  Some countries are repatriating gold reserves held outside of their borders.  China and some others are diversifying their foreign reserves to include currencies other than the U.S. Dollar and gold bullion. Central banks are debasing currencies around the world with various easy money programs that apparently have no visible signs of being tempered.  We are in a world or negative real interest rates.  Those things suggest gold  may see price gains for a while.

On the negative side — central banks have been net sellers at times — if their appetites are satisfied, a reduction in purchases would change the supply/demand relationship and potentially push gold prices down significantly.  Interest rates will rise some time due to improving economic conditions, at which time the emotional and financial appeal of gold would decline relative to bonds, stocks and real estate.  Just as negative real interest rates supports the price of gold, positive real interest rates create headwinds for gold, which produces no income and has some costs of carry for storage and other costs of holding directly or through funds.  Importantly, it is hard to be fully comfortable with gold when everybody and his brother feels it must be owned — when the radio is saturated with advertisements by gold dealers with suggestions to buy gold coins and to convert IRAs to gold IRAs, and when the web is fully of articles, books and videos about the coming disaster for which owning gold is posed as a solution.  Lastly, if the world was coming apart, gold confiscation by governments (as it was in the 1930’s by President Roosevelt) is a clear risk; and the vaults that hold bullion for gold ETFs could well be looted by criminal bankers or rioters.

Morgan Stanley thinks gold will rise to about 1775 in 2013, and then 1845 in 2014 (it is at about 1650).  It has a trailing 1-year high/low range of approximately 1540 to 1790.

Goldman Sachs thinks gold will rise in the early part of 2013 to about 1825 during US debt ceiling and sequestration debates, but then decline in the second half as the U.S. economy improves, reaching 1750 by 2014.

Felix Zulauf of Zulauf Asset Management in Zurich believes that if gold goes above 1750 to 1800, and negative real interest rates continue, gold will go to 2200 by 2014.

PRICE CHARTS

Gold has gone down in the past as well as up, and has only been freely traded in the U.S. for less than 50 years.  It has a history as long as civilization, but the investment alternatives that exist today did not exist over the history of civilization, so ancient data while often cited, is of questionable analytic utility.  Some analysts discuss gold and Roman Empire, or other history, but we think sticking with the modern era is best for finding insights

For the past year, gold has been rather “dead money” and its chart looks like it could be creating a rounding top, instead of waiting to burst upward.

The chart shows price (black line), 1-year moving average price (dash gold line) and 1-year high to low price range (tan shaded area).

It’s nice to have the opinions of big name houses, they generally don’t tell you how they arrive at their views, other than making broad statements about fiscal and monetary policy, and that sort of thing — hardly precise.  Unfortunately, there are no fundamental data such as sales, earnings, dividends, or interest rates to which valuation multiples can be applied.

To complement the gold forecasts of various analysts, not all of whom can be relied upon to be objective or non-conflicted, we think it makes sense to canvas what the bulk of the investor community is forecasting with their risk capital.

To look forward for plausible gold price ranges, we can be assisted by examining:

  1. extrapolation of historical volatility of gold
  2. directional signals from long and short futures positions in gold
  3. extrapolation of options implied volatility for gold

Extrapolation Based On Historical Volatility of Gold

This chart plots statistical price probability ranges for GLD (the gold ETF that is priced at approximately 10% of the price of gold) using historical volatility of GLD.

The green cone projects the 70% price probability range from 02/12/2013 to 02/12/2014 based on 1-year historical volatility of GLD.  The end-point values are 174 and 146 (equivalent to 1740 and 1460 for gold).  The purple cone projects the 90% price probability range, with end-point values of 184 and 139 (equivalent to 1840 to 1390 for gold).

The tan colored line is the 1-year moving average price, and the dashed black line is the linear regression best fit trend line from the beginning of 2007 through 02/12/2013, and extended to 02/12/2014.  Those values are 162 and 200 respectively (equivalent to gold 1620 to 2000).

Directional Signals From Long and Short Gold Futures

The CFTC (Commodity Futures Trading Commission) publishes weekly figures on the number of contracts that different types of investors hold (called Open Interest or OI) for gold and other commodities and financial indexes.  They call that report the “Commitment of Traders”. Their most recent report on gold is shown below.

This report will not tell us what price level to expect, but it provides clues as to whether to look to the upper half or lower half of the price probability ranges that we develop using historical and options implied volatility.

The data in this table is extracted from a larger data set in the Commitment of Traders report for February 5.  We highlight three groups; large professional money managers, other large futures traders, and small traders (those whose holdings are not large enough to require reporting to the CFTC).  The first two are considered the smart money, and the small traders are considered the dumb money.

click to enlarge

We see that all three groups have a lot more long gold futures positions (“Long OI”) than short gold futures positions (“Short OI”).  The money managers has a long to short ratio (“L/S Ratio”) of 3.28; the large traders 3.35; and the small traders 2.55.

Perhaps somewhat more revealing is that the money managers have increase their net long positions by 2.61% since last week; the larger traders by 17.32%; while the small traders have decreased their net long positions by 8.1%.  That patterns suggests gold is more likely to rise than fall near-term.

We can’t tell the mix of short-term and long-term futures contracts in these Open Interest figures, but they tend to be more near than far, so this data is not a long-term indicator.

Zooming out to a multi-year view, we see a rather constant number of longs and shorts among large traders and small traders, and not large changes in the ratio of long and short positions.  However, among large money managers we see big changes.  At the end of 2009, the large money managers had 224,030 long positions and only 6,874 short positions (a long/short ration of 35.29).  From there to mid-2012, their longs were substantially reduced and their shorts substantially increased to produce a 3.39 long/short ratio, which is close to where we are today.

So, long still outweigh shorts, but the level of interest in gold has moderated significantly among large money managers since 2009. This is not surprising, given that competing alternatives, particularly stocks have been doing well, and the sense if imminent doom that helps support gold prices is much reduced.

Futures open interest data indicates a reduced focus on gold, but still a positive view on prices — a rosier picture than the price chart would suggest.

Extrapolating Options Implied Volatility for Gold

Based on the January 2014 options for GLD (and assuming a continuing ratio of the price of GLD to gold at 1:10), and using the tools provided by OptionsExpress, the 90%  price probability range is bounded by 1310 and 1950.  The 70% price probability range is 1410 to 1810.

Statistical Views and Morgan Stanley / Goldman Sachs Forecasts

The statistical projections make room for the Morgan Stanley and Goldman forecasts, both of these are for prices in the upper half of the price probability ranges.  The Zulauf price forecast is outside of the statistically projected price ranges.

Mkt price 1650 % From Mkt
Historical Vol. 90% Hi 1840 11.52%
Historical Vol. 70% Hi 1740 5.45%
Options Implied 90% Hi 1950 18.18%
Options Implied 70% Hi 1810 9.70%
Morgan Stanley 2013 Tgt 1775 7.58%
Morgan Stanley 2014 Tgt 1845 11.82%
Goldman Q1 2013 Tgt 1825 10.61%
Goldman Q4 2013 Tgt 1750 6.06%
Zulauf possibility 2200 33.33%
Historical Vol. 90% Lo 1390 -15.76%
Historical Vol. 70% Lo 1460 -11.52%
Options Implied 90% Lo 1310 -20.61%
Options Implied 70% Lo 1410 -14.55%

Events can totally upset all of these data, but for now we go with what we’ve got.

An issue to keep in mind, is that in spite of all the excitement about gold, the percentage price changes in the statistical projections and in the Morgan Stanley and Goldman scenarios are not spectacular.  They are broadly in line with what might be achieved by a selection of stocks as well.

Gold is minimally correlated with stocks and bonds, which makes it a good diversifier to potentially help reduce overall portfolio volatility.  In the near term, however, unless the overall world and national situation changes, gold is not destined to massively outperform, and allocations to gold should not be overly large.

If income is important to the portfolio, then gold might be avoided, or held as GLD while writing short-term, out-of-the-money covered calls on the position.

We hold GLD is some portfolios and write covered calls on GLD in some portfolios.  Our allocation limit is 5%.

GOLD VERSUS OTHER ASSET CATEGORIES

Here are a series of 7-year, weekly charts showing the ratio of the price of gold to the total return for different asset categories.  A rising line means gold is doing better.  A falling line means gold is doing worse.

Gold vs S&P 500

Gold vs Dow Jones Select Dividend Index

Gold vs Dow Jones Liquid Investment Grade Corporate Bonds

Gold vs Brent Crude Oil

Gold vs Silver

Gold vs Copper

Gold vs Platinum

Gold vs Gold Miners

Gold vs Corn

 

Federal Debt / Federal Receipts From 1947

Monday, February 11th, 2013

 

Make Your Own Target Date Fund and Save Expenses (increase return)

Monday, February 4th, 2013

In spite of all the promotion, as a category, target date funds merely modulate the ratio of cash, stocks and bonds based on the target retirement date (and presumably average retirement ages).  They do make shifts toward lower volatility with higher bond allocations at older ages, but they do not accomplish very much in terms of a shift toward more cash income versus capital appreciation at older ages.

They don’t do much with the ratio of economically sensitive versus defensive stocks.  They don’t to much with allocation between major regions of the world (although they do tail off emerging market exposure somewhat).  They don’t do much with sector allocation.  They use essentially the same bond duration, although they do increase their government bond exposure and reduce low credit quality in later years.

They primarily manage the allocation between cash, stocks and bonds, but they charge on average about 50 basis points or a bit more.  In some cases, that expense may possibly be on top of the cost of underlying funds

There are many hundreds of target date funds, so there is clearly dispersion of approaches, but if you have to research to select among them, then you are doing the work that the target date concept was supposed to help you avoid.  If you are seeking a simple approach, why not decide what is best for you and allocate between a handful of pure index funds at much lower expense.  You could probably save around 40 basis points.  Over a long period, that can add up to big bucks.

Let’s look at the actual averages for target date fund categories, as reported by Morningstar Principia (as of December 31, 2012).  Then we’ll look at a simple low cost fund combination that should accomplish the same thing.

There are four index ETFs from Vanguard that can, for practical purposes simulate the aggregate allocation of the average target date fund with minimum effort and a definite reduction in expenses.

  • Cash:  VMMXX (exp. 16 bpt — except currently waived – yield 0.01%)
  • Total US Stocks: VTI (exp. 6 bpt – yield 2.02%)
  • Total Non-US Stocks: VEU (exp. 18 bpt – yield 2.87%)
  • Aggregate US Bonds: BND (exp. 10 bpt – yield 2.74%)

It would be quite easy to observe the allocation of the target date funds, and then to emulate their allocation with these four funds.

Within the context of the allocations by target date funds, a somewhat more complex set of funds would represent the non-US stocks with two funds, VEA (exp. 12 bpt – yield 2.86%) for the developed markets, and VWO (exp. 20 bpt – yield 2.19%) for the emerging markets.

Alternatively, for similar expense savings, are the Vanguard Retirement Target Date funds, which also primarily modulate the cash, stock, bond ratio.  Here is how those target date funds change yield and allocation by retirement date:

We believe it is possible to do better with at least some additional funds, to tweak the allocation a bit and increase the cash yield, but these funds could make a nice set of core holdings, and save you lots of money over time.

Not even counting the savings up to the time of retirement, a 35 to 40 basis point savings on a $1 million portfolio over 30 years of retirement could save you $105,000 to $120,000, or more if the portfolio grows.  Put differently, it could add $3,500 to $4,000 per year to your retirement income per million of assets.  That is not chicken feed.