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Related proxy funds:  SPY and VFINX for stocks; BND and VBMFX for bonds.

Disclosure: We own both SPY and BND.

Richard Shaw
QVM Group LLC

In the extreme short-run, it would be reasonable to assume that the U.S. stock market would react negatively, although short-term price movements are often chaotic. In the intermediate-term, if the legislation goes forward, the healthcare sector should perform at a lower level than in periods prior to national healthcare.

The chart below shows the historical relative price performance of several healthcare sectors versus the S&P 500. They are: biotech ($DJUSBT), pharmaceuticals ($DJUSPR), healthcare providers ($DJUSHP), medical equipment manufacturers ($DJUSAM) and medical supplies ($DJUSMS). The overall healthcare sector is represented by $DJUSHC.

Biotech and pharmaceuticals have underperformed. We expect that relationship to be accentuated. The other sectors are expected to have lower relative performance than before, particularly the healthcare providers, which include the health insurers.

click image to enlarge

Here are a few of the many specific negative profits factors in national healthcare:

• Drug patent protection will be shortened from 20 (+ up to 5 for approval) years to 12 years (? + up to 5 for approval), before generic competition will be possible. That reduces profitability of new drug research. Profits will be lower and fewer new drugs will be developed. That will reduce valuations on companies that develop new drugs. [In 1995, Congress increased to duration of drug patents from 17 to 20 years to encourage more development, but now in a reversal they cut from 20 to 12 to increase generic competition -- unfortunately at the cost of future medical advances].

• Annual fees to support the national healthcare budget will be assessed on insurers, drug companies, medical device companies, and clinical laboratories. That will reduce valuations of companies in those categories.

• Insurers may or may not be driven out of business (a major uncertainty that will reduce current valuations) and those that survive may effectively be converted to service utilities with regulated rates and profits (likely to reduce valuations below historic levels).

A small sampling of large companies in the healthcare field include:

• Biotech: AMGN, BIIB
• Pharmaceuticals: JNJ, PFE
• Medical Equipment and Supplies: MDT, BDX
• Clinical Labs: DGX
• Insurers: AET, UNH
• Hospitals: CYH, UHS

This list of companies is not a securities recommendation of any kind — just a representative sampling of the sector and its sub-sectors.

Disclosure: We do not own any named security.

Richard Shaw
QVM Group LLC

This short list consists of companies that  are candidates for consideration.  If you are a do-it-yourself investor who prefers individual stocks; and you have a non-speculative, conservative approach, this list may be worth researching further.

We identified those companies that S&P rated B+ or better for earnings and dividend strength, and which paid dividends continuously for at least 10 years.  Subsequently, we ran that list through a fundamental filter (described below) to arrive at this list of six prospects.

These are not recommendations for purchase, but they are a list that has been “worked over” a bit from the data angle.  We have not made a thematic evaluation and make no representation about the “story” for each company.  That’s up to you to do that. You need to look into them more fully before deciding to own any of them.  At a minimum, this list may save do-it-yourself investors some work.

The two tables that follow each contain the same list, but with different quantitative attributes.

Filter Results 11/06/2009

Companies in the tables: ADP, BF.B, ECA, HRL, JNJ, TDW.

Here are the screening criteria we used on the companies we first identified through S&P as strong and with 10 years or more of dividends payments:

Richard Shaw
QVM Group LLC

The “China up” and “U.S. down” theme is a major current mantra.  There are plenty of very bright, well informed, high profile people espousing the virtues of investing in China — people such as Marc Faber, Jim Rogers, Mohamed El-Erian, George Soros and many others.

For example, this past week Soros said that China will be the greatest winner from the global financial crisis, with the U.S. losing the most

We think that he and they are probably right, but we also think its a good idea to put data together side-by-side from time-to-time to see how the theme is holding up.  Are the current fundamentals supporting the theme?  Is the valuation reasonable?  Is the price action in accord with the theme?

While such checking can seem unnecessary at a time like this, it is a good discipline to check facts periodically, even when it seems obvious that checking is not needed.  Checking, double checking and re-validating is a good risk management discipline.

If you are on board the China theme and you are fully comfortable with that, there’s no need to read further.  If you are a China skeptic or a China enthusiast who’d like to check out the facts once again, read on.

Macro-Economic View:

Here is some data, which we believe does support the current China versus U.S. theme (proxies FXI for China, and IVV or SPY for the U.S.).

First from 2008, these data are found in the CIA Factbook:

click images to enlarge

2008 US and China Economic Statistics and World Rank

This shows the U.S. on top in size, ranked weak in terms of debt load, growth, asset re-investment, trade balance and reserve capacity to make public investments (such as major infrastructure similar to the U.S. interstate system in the 1950’s). It shows China as large and nearing the top in size, ranked strong in terms of debt load, growth, asset re-investment, trade balance and reserve capacity to make public investments.

For 2009, we have a narrower data window for China.  While it reveals some important negatives lingering from the 2008 credit crisis, it is in much better shape than similar data for the U.S.

Current China Economic Statistics

Not shown in the tables is the increase in total employed people in China over the past nine months, versus the decrease in total employed people in the U.S.  — an important fundamental directional indicator.

The U.S. has 6.2 million fewer employed year-over-year as of September, while China reports a year-to-date increase of 7.6 million jobs.

They have twice the employment base, making their increase only half as good as the U.S. decrease is bad, but the key is that they are growing and the U.S. is shrinking.

Current U.S. Economic Statistics

The U.S. is in a broad based negative change status — better than before, but not doing as well as China.

Valuation and Tabular Performance:

We think a trailing 20+ P/E is too high for the U.S.  That is a level more appropriate for good times.  These are no longer apocalyptic times, but they are definitely not good times.

Barton Biggs would certainly disagree with us on valuation.  In the October 17 issue of Newsweek in “Why the Bears Are On the Way Out” he said in closing,

What could the pessimists be missing today? First and foremost, they are betting against America, the greatest entrepreneurial engine ever created. … emerging economies may well be the new dynamo of growth. They now account for 35 percent of world GDP and are growing two to three times faster than the developed world.  S&P 500 companies now collect almost 50 percent of their revenues from overseas, and almost half of that portion comes from these fast-growing developing countries. Another factor could be that stocks currently despite the rally are still deeply undervalued. The rule of thumb is that stocks should sell at a price/earnings ratio equal to 20 less the inflation rate. Assume S&P 500 operating earnings are $70 to $75 next year and inflation is 1 percent, you get a theoretical price far higher than the current level of 1060. If inflation rises in the future, price/earnings ratios will fall but profits will be higher.

With Bigg’s formula, the S&P should be priced at about 1400 to 1500 instead of its current level between 1000 and 1100.  No thanks, we wouldn’t touch an S&P 500 index fund for anything like 1400 to 1500 right now.

We point out that in 2005 (a time of market optimism) when the trailing operating earnings were in the $70 to $75 range, the S&P was only in the 1200 to 1250 range.

Inflation was 3% that year.  The Bigg’s formula would generate: P/E = 20-3 = 17.  That multiple times $70 to $75 yields a valuation of 1190 to 1275.  His formula is right on target, BUT expectations are big part of valuation and his formula doesn’t include the overall stability level and trajectory we have today.

We think at least a 10% haircut for the precarious situation and long period projected for full recovery would suggest a value more like 1075 to (where we have just been) to 1150 as a top number (a possible approximate 10% rise from here) until facts on the ground and expectations improve.

Yeah, sure, cash is earning next to nothing, but earning nothing in the short-term is better than paying too much and risking too much.

Both FXI and IVV (or SPY) are similarly close to their 52-week highs and somewhat similarly close to their bull cycle highs.  However, since China took a larger spill in the crisis, it has experienced a greater increase to get into the position it now finds itself relative to its highs.

The 3-year volatility of the S&P 500 is nearly four times the 3-year mean return, but the volatility for the FTSE/Xinhua 25 (generally the largest China stocks) is only about 2.5 times the 3-year mean return.

The trailing P/E for the large China stocks is approximately 10% higher than the trailing P/E for the large U.S. stocks, but the GDP growth and other growth measures for China are a multiple of the U.S.  growth measures.

That said, the ride on China stocks is very bumpy with potentially gut wrenching dives. The 3-year standard deviation is a whopping 41% and the shorter term volatility risk according to Risk Grades is about 60% higher than for the S&P 500.  However, with good stop loss use, an investor can benefit by the upward volatility while limiting the downward movement exposure.

Price Behavior:

Barton Biggs makes a great point about the S&P 500 being global in nature and also about the difference between a country and the companies domiciled in it.  There are great companies in many countries and lousy companies in every country; and giant global companies are not limited by the growth of their domicile.

That said, the price performance of the S&P 500 versus China indexes, still favors China.  The next two charts plot the FXI price performance divided by the FTSE/Total World stock index (proxy VT) and the IVV price performance divided by VT over the past 5 years.  China is the hands down winner.

FXI/VT Weekly Over 5-Years

IVV/VT Weekly Over 5-Years

The funds we are illustrating don’t have long histories, so let’s look at some MSCI indexes for the World, China and the U.S. over 20, 10, and 5  years.

These charts are done in semi-log scale to more effectively show percentage changes over the long periods.  Arithmetic scale is OK for shorter periods, but when prices change radically or if one security changes much more radically than the other, semi-log scale is better.

Over 20 years, the U.S. stock market beat the pants off of the China stock market.  However, a lot has changed in both the US and China over 20 years.   The U.S. has expanded its debt, hollowed out it manufacturing capacity, and put itself in a vulnerable energy resources and manufactured goods import position.  China has strengthened its finances and massively built-out its manufacturing capacity and export distribution.

MSCI All Countries World, China and U.S. 20 Years

Over 10 years, the change in relative strengths becomes apparent in the price performance charts.

MSCI All Countries World, China and U.S. 10 Years

Over 5 years, China has been the clearly superior performer.

MSCI All Countries World, China and U.S. 5 Years

A Current Technical Point:

Both the S&P 500 and the FTSE/Xinhua 25 have found the 50% retracement level  from the 2009 low to the 2007 highs to be resistance.

As theory goes, that is an important recovery test level.  To be a long lasting and continuing bull, many would say a security must pierce its approximate 62% retracement level.

FSTE/Xinhua 25 (FXI)

S&P 500 (IVV)

FXI looks like it has good potential for support at the 38% retracement level. While the 38% level may provide some support for the IVV or SPY, other chart information suggests support may lie below that at the June/July level or possibly even a lower high experienced at year-end 2008.

China and the U.S. Are the Epicenter of the World Economy:

The U.S. and China are so central to the world economic dialogue that it is hard to imagine other countries decoupling their price pattern too much from the fate of these two countries.

This past week, economist Martin Feldstein said that,

“Global leaders have agreed reducing global imbalances is a priority. In practice, that means reducing the U.S. $500bn current account deficit and shrinking the $350bn surplus of China. All other current account imbalances pale by comparison“.

He goes on the say that in addition to more savings in the U.S. and more consumption in China, the Dollar must fall and the Renminbi must rise.

Both China and the U.S. face potential bank problems, although the size and immediacy of those problems in the U.S. is of greater current concern.

Both countries also have delicate timing issues to resolve when and as they remove the massive relative stimulus programs they each implemented.

China’s program resulted in huge lending programs, tax cuts, major increases in capacity development (overcapacity in some sectors), and increased industrial employment output.  The U.S. program resulted in financial institution capital strengthening, tax increases, capacity bailouts, and has not resulted in an increase in overall employment and industrial production.

The uses and benefits/disadvantages of the two programs are quite different, but the risk of ill-timed or badly managed withdrawal are substantial in each case.

World Free-Float Market-Cap:

Because most of the stock in the U.S. is in the free-float, and because most of the stock in China is not in the free-float, the index weights of the two countries are far more different than the relative financial size of their markets.

The U.S. represents 44.2% of the current FTSE/Total World index, while China is but 1.3% of the index.  The U.K, Japan, France, Australia, Canada, Germany and Switzerland all have higher weights in the index than China, but probably none has has many eyes, ears and calculators focused upon it as China.

Conclusion:

We think the fact checking shows the China theme to be in tact.  Although we exited the equities markets entirely last Wednesday morning in our active trading accounts (not in our long-term client accounts), we do expect to be back in again sometime soon. When we go back in,  China will have an allocation at a multiple of its 1.3% world index weight through a combination of its weight in the emerging markets index and through a China country fund holding.

Disclosure: We do not own any of the named securities at this time.

Richard Shaw
QVM Group LLC

Obamacare in the U.S. will be no different.  For investors in healthcare companies, it is a good idea to begin to think through which companies will be most severely negatively impacted or least impacted, to potentially make  deletions or substitutions.

One dimension of healthcare companies is research and development, which has been an important driver of future growth and value for many companies in the biotech, pharmaceutical and medical devices industries.

To the extent that the rewards of research and development are reduced by price pressures due to national healthcare, research and development will decrease, and therefore growth in sales, profits and value of those private companies will slow.

One way to begin the process of determining the sensitivity of biotech, pharmaceutical and medical device companies to a switch from a private to a public U.S. healthcare system is to identify what portion of their total revenue comes from the U.S.  Those with a greater U.S. revenue exposure are more likely to be damaged by Obamacare than those with less U.S. revenue exposure.

This chart identifies 21 healthcare companies that have expended for R&D on average for the past 7 years at 15% of sales or more, and that have a current market-cap of $10 billion or more.

click image to enlarge

Company symbols in the table image: STJ, AMGN, CELG, AGN, BMY, BSX, MRK, LLY, GILD, BIIB, JNJ, GENZ, WYE, ESALY, NVS, GSK, AZN, PFE, RHHBY, NVO, SNY, SGP.

While there are many other questions to ask about a company to judge its sensitivity to potential U.S. national healthcare, looking at geographic revenue segmentation is a good place to start.

Some, but not all, of the other factors, you will probably want to analyze as you do your investment research are:

• current profit margins on U.S. revenue versus non-U.S. revenue
• split of consumer products that are not covered by current insurance, nor likely to be covered by Obamacare (e.g. aspirin and cold remedies)
• sales and growth rate contribution from the U.S. versus other countries
• what they have already in late state development or clinical trials
• the duration of patents on their key drugs or devices
• the current degree of market adoption of their key drugs or devices

While the answers to the above questions could prove more important than geographic revenue segmentation, preliminary logic would say that large companies with lower U.S. revenue exposure are candidates as potential substitutes for large companies with higher U.S. revenue exposure.

Even though companies with less U.S. revenue may have substantial European revenue, the national healthcare impact from those countries is already a known.

One of our clients who is in the medical services business, told us that a national healthcare official there told him that European healthcare officials recognize that the profitable private market in the U.S. has enabled much of the research and development by healthcare companies around the world.  He said the flow of new drugs, treatments and devices that they rely upon is dependent on companies being able to profitably develop them for the U.S. market.  European officials are concerned that their national healthcare will consequently suffer a decreased flow of new drugs, treatments and devices if the U.S. eliminates its private healthcare system.

Whether that is correct, we don’t know, but it is an interesting issue from an investment perspective.  It suggests that even though there are important European companies doing research and development, they may not do so much of that if they cannot sell new products into the United States at higher prices than they can at home.

The story points to the need for a large private healthcare market somewhere to make development of new medical technology economically attractive to private companies.

Without private research and development, we are left with politically directed research which is more likely to be incremental as opposed to breakthrough. There certainly are some examples of government directed and funded research creating breakthroughs, most notably in space exploration and in military technology.  However, those types of programs were not characterized by cost containment as a key objective, but cost containment is one of the key goals in any national healthcare system.

All this leads us to think that healthcare investing would need to refocus on the “Walmarts” of healthcare (high volume, low margin); that biotech venture capital would have to be rethought; and that large pharma and device companies may need to merge to create larger more efficient, but less research oriented entities.

There will still be success stories and investment profits to be made, but not with the same old investment selection models.

We aren’t entirely sure what the new models would look like, but we do think a re-think of what a good healthcare investment would be is essential.

For starters, the U.S. versus non-U.S. revenue mix is a dimension to consider.

Approach healthcare providers, biotech companies, pharma companies, medical device companies, and medical or psychiatric REITS with an extra dose of investment research and caution until the U.S. sorts out its healthcare system plans.

Disclosure: We do not own any company identified in this article.

Richard Shaw
QVM Group LLC

New York Times (October 25, 2009)

“Germany’s new finance minister, the veteran conservative politician Wolfgang Schäuble, moved swiftly Sunday to assert his power and tell his compatriots and the world that the finances of the largest European economy were dire and would take years to mend. …   It was “utopia” to believe that the budget could be balanced during this legislative period that lasts four years, he said. … The programs announced for the new government included a €24 billion, or $36 billion, cut in taxes, which Mr. Schäuble had opposed as unrealistic given the parlous condition of state finances and the continuing uncertainty over the stability of German banks.”

The IMF recently published their forecasts for 2009 and 2010 growth for key countries and regions. Germany (as well as Italy and Spain) are lower performers in that list.  France and the U.K are expected to grow faster than the other listed European countries, but not as fast as Japan, the U.S. or Canada.

click image to enlarge

Related funds: Germany (EWG), Italy (EWI), Spain (EWP), United Kingdom (EWU), France (EWQ), Europe (VGK), United States (SPY), Canada (EWC) and Japan (EWJ).

Perhaps Europe’s stock markets have gone too far too fast, as the U.S. market seems to have done when looking at prices from a fundamental valuation perspective instead of a momentum perspective.

Disclosure: We own SPY, VGK and EWC in some managed accounts.

Richard Shaw
QVM Group LLC

The downloadable PDF file provides an historical perspective from 1968 through 2008, and projections for 2018 for taxes, spending and public debt.

click image to download PDF file

On the economic projection front, the CBO sees real GDP growth for 2009, 2010, 2011 and 2018 at: -2.5%, 1.7%, 3.5% and 2.2% respectively.

They see unemployment for the same periods being: 9.3%, 10.2%, 9.1% and 4.8%.

For CPI, the CBO sees -0.5%, 1.7%, 1.3% and 2.0% for 2009, 2010, 2011 and 2018.

They see the 3-month Treasuries and 10-year Treasuries for the same periods as (3-mo/10-yr): 0.2%/3.3%,  0.6%/4.1%,  1.7%/4.4%,  4.8%5.7%.

Federal Reserve View:

The Fed sees 2009 real GDP change at -1.6% to -0.6% (with a central tendency at -1.5% to -1.0%).  They see 2010 real GDP change at 0.8% to 4.0% (with a central tendency at 2.1% to 3.3%).  For 2011, the Fed sees a range of 2.3% to 5.0% (with a central tendency of 3.8% to 4.6%).

While the Fed GDP figures are somewhat encouraging, their unemployment forecast is not encouraging.  By 2011, they see a range of 6.8% to 9.2% (with a central tendency at 8.4% to 8.8%).

Our Thoughts:

First, all forecasts are prone to be wrong or subject to substantial change.  We’ve all experienced that in business and the markets.

The CBO had surplus forecasts for years in a row in their reports before 2008, for example — then we had the crash.

Then there was the AAA Moody’s rating for Lehman days before they filed for bankruptcy.

So, it’s good to know what the other guy, or in this case our government, is thinking, but not to rely on it without putting your own mental sweat into the questions.

We think the CBO and Fed projections seem a bit rosy, in terms of deficits and interest rates, given the extraordinary policy objectives of the current government, the enormous debt projections, high continuing unemployment and implied rising tax rates.

Certainly unemployment will dampen domestic demand and not put so much pressure on interest rates, and maybe more savers will chose Treasuries over stocks to further depress rates, but how long will China and other creditors accept low interest rates on Treasuries denominated in a declining Dollar while loaning money to an increasingly indebted nation?

That doesn’t make us feel all that good about the major U.S. stock indexes longer term, such as the S&P 500 (proxy SPY) or the Russell 3000 (proxy IWV).  There is liquidity chasing those indexes, but we really don’t see the sales growth aspect, unless it comes from abroad.  We’ll look at the growth picture globally through IMF and other reports in follow-up article.

We continue to feel substantial non-US stock holdings is appropriate.  We recommend beginning thinking with a world market weight, then deviate to tilt toward opportunity, mindful of risks.

Disclosure: We own SPY in some managed accounts.

Richard Shaw
QVM Group LLC

]]> http://www.qvmgroup.com/invest/archives/6573/feed http://www.qvmgroup.com/invest/archives/6573 http://feedproxy.google.com/~r/qvmgroup/yrMF/~3/qvf3Sk1DxFk/6538 http://www.qvmgroup.com/invest/archives/6538#comments Fri, 23 Oct 2009 17:53:18 +0000 RichardShaw http://www.qvmgroup.com/invest/?p=6538 There are many good things about being rich, but wealth also brings some problems.  The most obvious problem is how to stay rich in these troubled times.  Less obvious for the wealthy is that they have fewer practical investment vehicles than the average investor.

Just as large institutional investors have a smaller universe of individual stocks they can buy without becoming too big a factor in the security.  Wealthy individual investors and smaller non-profit or institutional investors have a smaller universe of funds they can buy without becoming too big a factor.

There are more established mutual funds of substantial size than there are ETFs of similar size, which argues for mutual funds over ETFs for large investors.  However, for those who wish to be in a listed security for intra-day entry or exit (including using automated stop loss orders to protect against large drops in price), mutual funds don’t work.

With ETFs as client mandate, what does work?

We recently performed an analysis for some of our wealthier clients to identify those ETFs they could use in their portfolios without moving the market when they decide to move their money.

Here is what we found:

We made the arbitrary decision that a client would not want to own more than 0.5% of a fund’s total assets, and would not want to have any position that was more than 0.5% of the fund’s average daily Dollar trading volume.

Our database tracks 832 ETFs.  Of those funds, this is how many can “handle” positions of various sizes based on the above criteria:

• $10 million position: 5 funds
• $5 million position: 12 funds
• $1 million position: 46 funds
• $500,000 position: 76 funds
• $250,000 position: 97 funds
• $100,000 position: 141 funds
• $50,000 position: 197 funds
• $10,000 position: 335 funds.

Those five funds with the capacity to absorb $10 million positions at or under the lesser of 0.5% of assets or average daily trading volume are:

• SPY (S&P 500) — U.S. large-cap stocks
• QQQQ (NASDAQ 100) — U.S. large-cap stocks
• IWM (Russell 2000) — U.S. small-cap stocks
• EEM (MSCI emerging markets) — emerging market stocks
• FAS (Russell 1000 financials)  — 3x U.S. financial sector stocks.

To keep the list in the unleveraged category, we step slightly over our arbitrary limit and add XLF (S&P 500 financials), which can justify about $7.7 million position based on our arbitrary 0.5% screening rule.

click image to enlarge

Screening Results for Most Liquid ETFs

Nearly 500 of the 800+ ETFs (60+%) are not ready for prime time with just about anybody, and only a handful of ETFs are large enough to accommodate an investor who has $50 million to $100 million or more to invest and who wishes to put $10 million into a single ETF position.

It is true that special manual arrangements can be made through brokers to get into a fund without disturbing it.  However, that makes getting out without disturbing the fund a special manual arrangement too, which is not something we would recommend.  There are some times when a quick exit is needed, or an exit is needed at a particular price point, neither of which would be achieved by the special arrangement process.

An alternative to mutual funds (which lack stop loss opportunity) would be to purchase more than one fund with the same or near same objective; or to purchase the maximum liquid size in the fund of choice and then purchase a collection of individual stocks from the holdings of that fund.  That way liquidity can be maintained and stop loss protection can be applied.

Disclosure:  We hold SPY, IWM, and EEM in some managed accounts.

Richard Shaw
QVM Group LLC

The degree of “normality” of S&P 500 price changes is high on a daily basis — it’s visually symmetrical.  The average change of 0.03% is less than the median change of 0.05%.

The monthly distribution is not as visually smooth or symmetrical, but presents a “pretty” good bell shaped curve.  The average change of 0.67% is less than the median change of 0.91%.

The calendar year distribution requires a bit of squinting and some imagination to see a bell shaped curve — making it “sort of” normal looking.  The average change of 8.02% is less than the median of 9.76%.

The most extreme outliers, as measured by standard deviation, are at the daily level, then monthly and lastly calendar year.

click images to enlarge

Daily % Price Change Distribution

Monthly % Price Change Distribution

Calendar Year % Price Change Distribution

Directly relevant S&P 500 index funds are: SPY, IVV and VFINX.

While the “worst” has been worse than the “best” has been better, the negative outliers can be filtered out with stop loss orders.  If persistent trailing stop loss orders are used to filter out the bad or poor, not just the worst; while letting the positive deviations run, the returns are increased.

We will reproduce these data sometime again over a shorter period.  The daily data will  look the same, as most likely will the monthly distribution.  The annual data will vary substantially over different shorter periods.

For the data hungry, we hope this is helpful.

Richard Shaw
QVM Group LLC

]]> http://www.qvmgroup.com/invest/archives/6515/feed http://www.qvmgroup.com/invest/archives/6515 http://feedproxy.google.com/~r/qvmgroup/yrMF/~3/frGhYPezf6U/6495 http://www.qvmgroup.com/invest/archives/6495#comments Wed, 21 Oct 2009 20:25:45 +0000 RichardShaw http://www.qvmgroup.com/invest/?p=6495 These two charts present the monthly and daily percentage price changes in the S&P 500 from January 1950 through the most recent period in 2009, roughly 60 years.

After the exceptional experiences of the past year, a long-term look back may be helpful. Of course, we are in a different environment than the U.S. has seen since 1950, and the U.S. economy has been and is in continual change, but an awareness of history is still a good thing to have.

click image to enlarge

Monthly Price Change

If you take the 80% of months in the middle, the extremes of monthly change were -4.40% and +5.35%.

If you take the 90% of months in the middle, the extremes of monthly change were -6.20% and +7.13%.

Daily Price Change

If you take the 80% of days in the middle, the extremes of daily change were -0.98% and +1.01%.

If you take the 90% of days in the middle, the extremes of daily change were -1.42% and +1.44%.

Neither of these charts provides data about back-to-back runs of monthly increases or declines.

Different investors will make different use of this sort of information, but we wanted to put it out there for those who may find it useful or insightful.  It’s good to have a sense of the “thing”.  Investors often write to us for long-term data such as this.  Then again, some will say “so what” and that’s OK too.  We think in some way, at some time, it would be helpful to have these statistics available.

Related S&P 500 index funds: SPY, IVV and VFINX.

Disclosure: We own SPY in some managed accounts.

Richard Shaw
QVM Group LLC

Obama on Cost Impact of Climate Policies (March 18, 2009):

Warren Buffett on Cost Impact of Climate Policies (March 9, 2009):

There is now concern that Obama will sign a treaty that will limit the options of our legislators or subsequent presidents to modulate our approach to the climate change issue. Whatever burden the U.S. may carry under domestic policies, we expect the burden would be greater under international treaty requirements.

We believe that the general direction of domestic policy in the U.S., and plausible international treaties the President may sign, will among other things:

1. limit manufacturing in the U.S. by cap and trade regulations
2. limit personal consumption of energy by law and costs
3. cause the cost of energy to increase
4. cause goods and materials to become more expensive
5. cause transportation to become more expensive
6. prevent the U.S from growing out of its economic problems as effectively as it has in the past
7. assure and accelerate the shift of economic growth and profitability from the U.S to emerging markets.
8. not limit the amount of stuff manufactured worldwide as global consumerism increases
9. increase the percentage of stuff consumed in the U.S. manufactured in emerging countries (who will not be subject to the same carbon emissions limits)
10. cause the U.S. to become an even greater debtor while China becomes an even bigger creditor
11. add momentum to the movement away from the U.S. Dollar toward an alternate single or composite world reserve currency
12. increase the cost of Treasury borrowings
13. increase the cost of commercial, mortgage and personal debt tied to Treasuries
14. reduce the exchange value of the Dollar
15. reduce home purchase and ownership affordability
16. drive up federal and state taxes.

The pace and degree of these sorts of change is uncertain, but the direction of policy change is clear.  Without commenting on the political or moral issues that are hotly debated, the clear implication of the direction is at least a reduced rate of improvement in U.S. standard or living, potentially an absolute decline, and adverse overall U.S. stock and bond consequences for a considerable time.

The political claims are that the conversion to alternate fuels and more energy efficiency will create a new and brighter economy — only time will tell.  However, we expect at a minimum a very bumpy transition that will be difficult for investors.  Countries not going through that transition or exempted from the transition may have smoother economies as a result.

As a general proposition, we’d prefer to have a large slug of our money working in economies that are not going through the economic experiments, successes and failures, and trials and tribulations that we expect domestic laws and international treaties will impose on the United States.

The short story is that the domestic and international energy and carbon policies (with their stricter limits on developed countries and lower limits on emerging countries) are in effect China and India stimulus plans — a wealth and wealth opportunity transfer from the U.S. to emerging countries.

The simplest investment response is to diversify cash, bonds and stocks more fully to other parts of the world, and to have a less U.S. centric portfolio.  At least for now there are no significant currency controls, international investment limitations or tax surcharges on investment gains or income from non-domestic investments.  For now, and we hope forever, you are free to invest your money globally.  We suggest that you do so.

The logical investment responses would be:

1.  Reduce stock allocations to the United States and increase emerging markets allocations.

2.  To the extent you invest in U.S. companies, focus on those with low energy or materials consumption, or that will increase sales directly due to carbon or energy limits, or to those companies with substantial non-U.S. operations and sales.

3.  Stay at the shorter duration on bonds, because Treasury interest rates are likely to increase and trend at higher levels than when the U.S. was less of a debtor and not limited in its ability to grow out of its debt.

4.  Think through how decreased house affordability will ripple through various industries when investing domestically, because homes are likely to become less affordable as energy costs rise, mortgage rates rise, local taxes increase and construction materials cost more — while at the same time the equilibrium rate of unemployment will be higher than in the past and the rate of growth of wages will struggle to keep up with inflation.

5.  Diversify fixed income assets to include high quality international debt denominated in other major world currencies.

6.  Consider holding part of cash reserves in multiple currencies.

7.  Expect carbon credit investments to become popular with a proliferation of funds which may eventually become useful in portfolios — not yet though.

8.  Perhaps abandon the simplistic concept of developed and emerging markets (now cast in cement by index providers and index fund managers), and replace that with a differentiation between net creditor and net debtor nations, net importer and net exporter countries, resource exporters versus goods and services exporters, and low GDP growth versus high GDP growth countries.

A simple way to monitor the shift would be to watch these three percentage performance charts:

1. three equity funds: VTI, VEA and VWO (for total U.S. stocks, total developed market stocks ex Canada, and emerging markets stocks)
2. three funds: BND, BWX and EMB (for U.S. bonds, local currency developed country bonds, and Dollar denominated emerging market bonds)
3. three indexes: oil (proxy USO), gold (proxy GLD)and U.S. Dollar index (proxy UUP).

You can get a pretty good idea of the global picture from those nine plots without spending too much time. You could track the oil, gold and Dollar proxy funds instead of the indexes, but at least for oil, the tracking is not necessarily good.

Short-term versions of those three charts follow:

Enjoy the U.S. and global bull of the moment, but think long-term by becoming more of a global investor.

Richard Shaw
QVM Group LLC

These two tables show the options implied (30-day future) volatility for several important indexes or index funds:

click image to enlarge

The “per year” column is the published annualized volatility (1 standard deviation). The columns for other periods (quarter, month, week and day) are math transforms of the annualized volatility to show the expected volatility for those periods of time.

Plus or minus one standard deviation is expected to encompass 67% of prices during the period.  Plus or minus two standard deviations is expected to encompass 95% of prices during the period.

Example:  The “per day” column says that the price of a GLD position is expected to move within a plus or minus one-day 1.09% variation with a 67% probability, and to move within a plus or minus one-day 2.19% variation with a 95% probability.

This sort of information can be useful in selecting securities based on volatility and also in setting stop loss parameters.

The proxy securities for the indexes in the tables are DIA (DJIA 30), SPY (S&P 500), QQQQ (NASDAQ 100), and IWM (Russell 2000).  Oil, gold and the Euro volatility indexes are based directly on the underlying ETFs: USO, GLD and FXE.

Disclosure:  We own SPY, IWM, GLD and FXE in some portfolios.

Richard Shaw
QVM Group LLC

We screened the S&P 1500 for stocks with rising prices and falling volumes.  More specifically, we looked for stocks with “sinker” attributes:

• last closing price > 21-day simple moving average price
• positive 21-day price rate of change
• negative 21-day volume rate of change
• negative money flow (more vol. on down days than on up days)

We had the necessary data for 1470 of the 1500 stocks. Of those 104 met the sinker screening criteria as of end-of-day Oct. 15, 2009.

This image shows the 10 companies from that list with the greatest negative 21-day volume rate of change.  (download spreadsheet of full list).

click image to enlarge

If you own any of the stocks on the screened list, look at them again fundamentally and technically to make sure you are OK with holding them.  Don’t close a position based solely on these few criteria, but take note and do some more research to see if you should consider closing the position.

Note: We make no representation as to the quality of any company on this list or as to their probability of rising or falling in price.  This is simply a screened list to potentially identify stocks for which short-term negative volume trend suggests short-term positive price trend may be heading for a reversal.  You need to look further to see if any of those companies are future sinkers or current stinkers.  All this list does is tell you that there is a divergence between the behavior of volume and price.

Disclosure: We are neither long nor short any company on this list.

Richard Shaw
QVM Group LLC

We also expressed our concern that we could not assess the myriad economic data and opinions to draw a convincing fundamental argument to support those technical conclusions.  The fundamentals are mixed and the global condition may be delicate, with potentially major geopolitical risk in the background (Pakistan/Taliban and Iran/Israel in particular).  The rewriting of the rules of capitalism in the U.S and the still looming foreclosure situation are not encouraging.

Overall, we see very roughly +/- 9% change potential in the S&P 500 by 12/31/2009, unless there is some major economic shock or geopolitical event. [read article]

Reader Request:

One reader of our article asked whether volume was supportive of the forecast, and if we would publish some related volume studies.  That’s what this article is about.

We think it may be interesting to present data for both the U.S. and Chinese stock markets, since they seem to be somewhat opposite poles around which much current global economic reporting revolves.

Volume’s Role In Analysis:

Share volume is a collateral indicator for market performance.  Generally, rising volume indicates a strengthening price move, and declining volume indicates a weakening price move.  Divergence between price and volume indicators is typically seen as a sign that a change in direction is possible.  The assumption is that volume is a leading indicator of trend changes.

Volume:

Volumes for the S&P 500 (proxy SPY) and the China Xinhua 25 (proxy FXI) since the March 9 beginning of the bull run in the U.S. are slightly down.  In the case of both country funds there is a divergence; the prices are up and the volumes are down.

That information may be cause for caution regarding increased cash commitments, but it alone is not a cause to sell existing positions.  We do recommend, and have been recommending all along, that you use persistent trailing stop loss orders to protect positions.

The stacking of the price and its moving averages of various lengths (21-days, 63-days, 126-days, and 252-days) is in an up trend for each of SPY and FXI.  However, the stacking of the volume and its moving averages of the same lengths are stacked in a down trend for each of SPY and FXI.

Caution is warranted by this measure for both SPY and FXI.

SPY Price and Volume Since 03/09/2009

FXI Price and Volume Since 03/09/2009

Money Flow - On Balance Volume:

On Balance Volume (”OBV”) is the cumulative total of positive and negative volume.  It is calculated by adding the day’s volume to a running cumulative total when the security’s price closes up, and subtracting the volume when the price closes down.

A rising OBV confirms a price trend.  A declining OBV shows a weakening price trend.  A divergence between OBV trend direction and price trend direction is a warning that the price trend may not continue.

The value of OBV is not important.  The direction of the OBV line is important.  A user should concentrate on the OBV trend and its relationship with the security’s price trend.

SPY Price and OBV Since 03/09/2009

For SPY, the OBV and its moving averages are stacked in a bullish order at the moment, although the OBV fell through its 21-day and 63-day levels before bouncing off its 126-day level.  The OBV has since recovered somewhat, but is still below its high.

Caution is warranted according to this indicator.

FXI Price and OBV Since 03/09/2009

For FXI, the OBV took a deeper dive below its 126-day average, but has recovered to a level closer to its high than is the case for SPY.

Caution is still warranted, as some accumulation fatigue is apparent.

Money Flow - Chaikin Money Flow:

Chaikin Money Flow (”CMF”) is an oscillator (not trend following) that attempts to show the degree of buying or selling pressure on a security over a selected period of time.

StockCharts.com describes the formula for Chaikin Money Flow as “the cumulative total of the Accumulation/Distribution Values for [x default 21] periods divided by the cumulative total of volume for [x default 21] periods.”

StockCharts.com describes the formula for Accumulation/Distribution as “a value based on the location of the close, relative to the range for the period. We will call this value the “Close Location Value” or CLV. The CLV ranges from plus one to minus one with the center point at zero. There are basically five combinations:
( ( (C - L) - (H - C) ) / (H - L) ) = CLV
1.    If the stock closes on the high, the top of the range, then the value would be plus one.
2.    If the stock closes above the midpoint of the high-low range, but below the high, then the value would be between zero and one.
3.    If the stock closes exactly halfway between the high and the low, then the value would be zero.
4.    If the stock closes below the midpoint of the high-low range, but above the low, then the value would be negative.
5.    If the stock closes on the low, the absolute bottom of the range, then the value would be minus one.
The CLV is then multiplied by the corresponding period’s volume, and the cumulative total forms the Accumulation/Distribution Line.”

Three key attributes are: (1) whether the indicator is above or below zero, (2) the length of time the indicator is above or below zero, and (3) the magnitude of the positive or negative reading.

SPY Price and CMF Since 03/09/2009

For SPY, the CMF is (1) still above zero [accumulation], (2) has been above zero for 3 months and most of the past 6 months, and (3) the magnitude of the positive values for the 21-day figure have been deteriorating since August to an essentially neutral level.

Caution is warranted.

FXI Price and CMF Since 03/09/2009

For FXI, the CMF (1) has been below zero over the last few days and has recovered to just over zero, (2) has been above zero for most of the past 6 months, but with 4 short periods below zero, and (3) the magnitude of the positive position has been fading since August, culminating in a mild below zero position that is only just reverted to a minimal positive value.

Caution is warranted until a solid positive number is observed.

Volume By Price:

Volume By Price (”VBP”) shows the volume of trading that took place at each price range.  The horizontal histogram at the left is on the same scale as the price shown on the right.

Larger histograms will result from either a high volume as the security passes through a price, or the security spending more time in the price range than in other ranges over the measured period (including through the price range up and down at different times).  Smaller histograms will result from either a low volume as a security passes through a price, or the security spending less time in the price range over the measured period.

SPY Price and VBP Since 03/09/2009

SPY has seen the most volume in the high 80’s and low 90’s and very little volume at the bottom in early March. The contraction of the histogram in the high 90’s probably reflects disbelief that the recovery from the July down draft would hold.  Once the post-July recovery seemed to be real, the volume picked up as it did in April after the post-March low recovery began to attract followers.  The chart shows that the great bulk of those buyers since March 9 are in a gain position (bought before the end of August).  Whether they are skittish and likely to cash out or confident and likely to stay in for potential gain in not indicated by this type of chart.

Some people believe that price ranges with the highest volume are likely support or resistance areas. Taking that approach would tend to agree with price-based logic for support in the high 80’s to low 90’s for SPY.

FXI Price and VBP Since 03/09/2009

Unlike SPY which saw a bulge in volume mid-move since March 9 (partly due to some consolidation at mid-move prices), FXI has seen a general increase in volume as the price has risen.  Only at the very top of the FXI price so far have we seen volume falling off.  It deserves watching, but is inconclusive.

A large portion of FXI buyers since March 9 did so after August, and are in a shallower gain position than the bulk of SPY buyers since March 9.

Summary:

We are not big users of volume for analysis.  Maybe we should increase our volume observations.  We’ll think about that.

The flows of money are key to market action — prices go where money flows.

In writing this article, we mostly wanted to respond to reader request for  information about volume as a follow-up to our article on volatility and probability based projection of the year-end price for the S&P 500.  Nonetheless, we found this volume exercise to be useful and appreciate being prodded to do the study.

The idea that volume precedes price is attractive, but the degree of reliability of specific volume indicators has not been demonstrated to our satisfaction (or perhaps our study has not been extensive enough) to make volume other than collateral information at his point.

Most likely, we would be motivated by major volume trends or significant divergences, but not by fine movements in volume indicators.

That said, these volume indicators all seem to suggest some degree of trend exhaustion and that caution is in order.

Our price volatility analysis suggests a roughly 80% probability of a +/- 9% price change range for SPY through year-end based on 3-month daily historical and options implied volatility. Price moving average trends suggest an upward bias in that range. Volume and some fundamentals suggest investors be alert for a negative bias.

Historical 3-month daily volatility for FXI, suggests a roughly 80% probability of a +/- 8+% price change range by year-end. Price moving average trends suggest an upward bias in that range. Volume and some fundamentals suggest investors be alert for a negative bias.

Disclosure:  We own SPY and FXI in some managed accounts.

Richard Shaw
QVM Group LLC

Historical volatility for the past 3-months would suggest 971 to 1151 for 80% probability.  Implied volatility in the 3-month CBOE volatility index would suggest about 974 to about 1172.

. . . . . . . . . . . . .  DISCUSSION . . . . . . . . . . . . .

In our last article, we continued the discussion of price projection based on historical volatility.  We provided an historical example of quarterly projections from 12/31/2002 at 95% probability (2 standard deviations) based on 63 days (3 months) of daily historical volatility. Some of our readers have asked for a projection with a narrower range, so here is one based on 80% probability.

Multi-Year S&P 500 Price Probability Projection:

This chart projects forward from the beginning of each calendar quarter to the end of the quarter, based on the daily volatility of the prior calendar quarter.  Each cone delimits the area on the price chart that is likely to contain 80% of the closing prices. That still leaves roughly 10% that might close outside of the cone on either side, but prices are more likely to be inside the cone than outside, so long as the level of volatility in prices remains about the same as in the prior quarter.

The chart also shows the 63-day (3-month) price channel for comparison.

click images to enlarge

Implied Volatility in S&P 500 Options:

While volatility could pop up at any time, it has a recent general pattern of decline.  That makes a bet on same to lower volatility not unreasonable (in the absence of new shocking news).  This long-term VIX chart shows the pattern of change in one-month volatility expectations for the S&P 500 over 20 years.

Looking more closely at the daily VIX for the past 3 months, the pattern of volatility decline is clear. Declining volatility would tend to make price probability projections based on past volatility more reliable.

The quarterly price probability projections from 2002 through 2009 are for 3-month forward periods.

For a better fit than the VIX which looks forward 30 days, let’s look at the less noted CBOE 3-Month Volatility Index which looks forward 3-months.  That index is also declining, supporting the current reliability of the price probability projections.

While same or lower volatility supports the price probability range, it does not support direction.

A prior article provides discussion of using options implied volatility to project future prices.

Trend Direction for S&P 500:

For directional clues, we need to look to trend indicators, such as moving averages.  Looking at longer-term trends, the cross-over pattern of the 26-week and 52-week simple moving average of the S&P index is bullish.

Looking shorter-term, the 1-year daily chart of the S&P 500 shows that a series of simple moving averages of different lengths are stacked in a bullish pattern (price higher than the shortest average, and each moving average higher than the successively longer average).

Price Projection Summary:

Taken together, we think these charts reasonably indicate a year-end 80% probability closing price range between 1150-1170 and the low 970’s (from the Oct 13 close of 1073; from up 7% to 9% through down 9+%).

The quieting volatility increases our confidence (absent new shocks) in the range.  The longer-term and shorter-term trends suggest a bias toward the upper half of the probability range.

That said, we are not at all comfortable with the general economy in the U.S. and cannot make a fundamental argument for the price levels of the S&P 500 index.  However, we do not wish to argue with the market.  Because shocks and sudden reversals are always possible, we have persistent trailing stops on all of our listed positions.

Questionable Fundamentals:

All the U.S. has done is kick the problems of 2008 down the road by transferring private debt to public debt.  The federal government seems to be using the cover of bailout to expand the scope of government and its cost beyond the levels required to delay or solve the economic problems.  The federal, state and local tax burden is about to increase substantially with negative impact on business activity.  The federal government has taken certain actions and expressed certain views that are hostile to capital.  The quality of bank assets in the event of rising interest rates is in question, and the scope of loan defaults that lie ahead is uncertain to negative.

There are some good things happening elsewhere, such as Australia raising its central bank rates in response to favorable economics. China seems to be growing well (although the government there has some concerns about the quality of that growth), but they have the financial reserves to continue stimulus if necessary.

Basically, trying to fathom all the different economic reports around the world and to absorb all the divergent opinions is a bit like drinking from a fire hose.

We do buy into the argument of a secular shift of economic power and growth from the West to Asia, and are shifting assets accordingly.

One nice thing about charts is that they tend to distill all the myriad data and opinions into a single thing — the price.  The price and price action may not be as forward looking as opinions, but the price is what makes or breaks your portfolio.  We don’t believe in arguing with the market when it is moving as it is.

Conclusion:

Price probability projections based on historical volatility (as well as on implied volatility for securities with high option volume) are helpful in understanding and managing risk and opportunity.

We see an 80% chance of the S&P 500 closing 2009 at between roughly 970 and 1170.  We don’t see too much reason for melt-up beyond 1170, but can imagine reasons for melt-down below 970.  Use persistent trailing stop loss orders to limit risk.

. . . . . . . . . .

Securities directly related to this projection: These securities track the S&P 500 — SPY and IVV.

Securities closely related to this projection: These securities are broad U.S. index funds with an extremely high correlation of price change with the S&P 500, making S&P 500 percentage price changes potentially highly relevant to them as well — IWV (Russell 3000) , IYY (Dow Jones Total U.S. Market), ISI (S&P 1500) , TMV (DJ Wilshire Total Market), VTI (MSCI Prime U.S. Market), RSP (S&P 500 Equal Weight).

Disclosure: We own SPY and VTI in some managed accounts, and may own some of the others from time-to-time.

Richard Shaw
QVM Group LLC

]]> http://www.qvmgroup.com/invest/archives/6264/feed http://www.qvmgroup.com/invest/archives/6264 http://feedproxy.google.com/~r/qvmgroup/yrMF/~3/VnHKPnzf9AU/6223 http://www.qvmgroup.com/invest/archives/6223#comments Tue, 13 Oct 2009 13:22:51 +0000 RichardShaw http://www.qvmgroup.com/invest/?p=6223 Last week we published a visual view of price range probability cones for several securities (SPY, FXI, TLT and UUP).  This article builds on the concepts in that article and provides a tabular view of the same kind of data for twenty-seven asset categories.

The two tables below show the maximum and minimum price change that statistics would suggest are probable over the 21 trading days after October 9 (last Friday), based on 21 days (1 month) and on 63 days (3 months) of historical price volatility.

click images to enlarge

21-Day Projection Based on 21-Days of Volatility History

21-Day Projection Based on 63-Days of Volatility History

The Statistical Approach:

By measuring the standard deviation of the percentage price changes (or of the difference in natural logs of successive prices) and making the assumption of an approximately “normal” frequency distribution curve (bell shaped curve), we can estimate the range for future prices in “normal” circumstances.  All bets are off in the extreme situations such as we experienced in 2008.  Fortunately, price behavior is more often “normal” than not.

Note that this approach does not speak to direction, just magnitude in either the up or down direction.

Overlay Direction on Probable Price Ranges:

Since statistically estimated price ranges give no indication as to direction, additional information is needed to judge whether positive or negative price movement is likely.  You might use fundamental and/or technical means of making that decision.

One approach to thinking about direction is through moving averages — the classical trend indicators.  Moving averages do lag and trends can change, but moving averages are widely used as indicators of direction.

You can look at moving averages of several lengths to see how they are stacked up.  For example, if each successively shorter average is above the next longer average, that is a strong positive trend indication. If each successively shorter average is below the next longer average, that is a strong negative trend indication.  You might also look at the slope of one or more moving averages to indicate whether the forces at work are pushing up or pulling down.

In the tables above, information for each of four moving averages (21-days, 63-days, 126-days, and 252-days) is shown to give some indication of direction to help you work with the price probability data.  For both tables the moving average data shows the ratio of each of the averages now to its value 21 days ago.

The Conical Shape of Probable Price Ranges:

Key to projecting prices is that the range of probable prices widens (with the square root of time) as the projection horizon extends farther out, creating the conical shape to the probable price range.

click image to enlarge

68% Probability and 95% Probability:

The tables show the maximum probable price change after 21 days for +/- 1 standard deviation either way (encompassing 68% of probable prices), and for +/- 2 standard deviations (encompassing 95% of probable prices).

What lies outside of those ranges (roughly 2.5% on each side), can be quite exciting as we learn painfully upon infrequent occasions.

Multi-Year View of Probability Price Projections:

This chart of successive quarterly 95% probability price projections for the S&P 500 index might have been useful to some investors to see the problems of 2008 developing.  From the beginning of the last bull in 2003 to the end in 2007, the realized price range in each calendar quarter occurred within the 95% probability projection based on the preceding 3-month daily price volatility.

Early in the first quarter of 2008, the realized price range moved outside of the 95% probability projection.  That was a warning that the situation was no longer normal and was negative. The price behavior in the first quarter generated a very wide 95% projection range for the second quarter — also a warning sign that something unusual was happening.  The negative trend was indicated by the raw chart and moving average cross-overs by that time as well.

The third quarter remained mostly inside the 95% boundaries, but touched the downside edge near the quarter’s end — and the downward trend was visually clear on the charts.

The combination of price behavior at or near the 95% probability level and the downward trend, should have been enough to suggest taking at least some money off the table, if not all.  Something unusual — something disorderly — was developing. Ambient fundamental data was deteriorating too.  “Unusual” and “disorderly” at the very least call out for heavy scrutiny, and perhaps standing aside until things are sorted out.

click image to enlarge

By the time we reached the beginning of the first quarter of 2009, the probability cone was so wide that just about anything could happen, but with a clear down momentum.  The market went well down from there.

In the second quarter of 2009, the probability range narrowed (but was still wide) and prices remained within the range.  The third quarter 95% probability range narrowed again, and prices continued to remain within the conical boundaries.  These were signs of a return toward normal market behavior.

We are now in the fourth quarter.  The probability range is narrower than the third quarter and the trend is still up, suggesting that absent a major shock, the S&P 500 should end the year between about 930 and 1200 based on 95% probability (and based on trailing 3-month daily volatility).

The 68% probability (not shown on the chart) would put the year-end at about 990 to 1130.

Understanding and Managing Risk to Increase Gains and Limit Losses:

You need to use stop loss orders or other active measures to protect against the improbable, but can benefit by otherwise understanding and managing risks based the probable.

For example, if you are an options buyer, you would most likely want to own strike prices inside the price probability cones.  However, if you were an options seller, you would most likely want to write options with strike prices outside of the price probability cones.

Similarly, if you are taking an equity position, you might want to know what statistics based on volatility tell you about the size and probability of a possible price decline, and of a possible price rise.

Probability price projections are imperfect, but potentially helpful for market interpretation when considered in combination with other fundamental and technical data.

Some Observations from the Tables:

Real estate, pipelines and oil have the widest probable percentage price ranges over the month (21 days) following last Friday (Oct 9).  Bond percentage price ranges are lower than equity price ranges.  Long-term bonds have wider ranges than short-term bonds.  U.S. stocks have narrower ranges than non-U.S. stocks.  Emerging market stocks price ranges are not terribly different from those of non-US developed markets, except for Japan.  The Japanese stock market has a slightly narrower probability cone than the U.S. stock cone.  Aggregate U.S. bonds, junk bonds and TIPS have similar narrow probability cones.

While several of these observations are consistent with general perceptions, some may not be so.  Even if all were general perceptions, it is useful to test perceptions so that we don’t “drink the Kool-Aide” or have our mental feet in cement.  Instead, we need to read the data to let the market inform and update our perceptions.

Do take note that these are short-term projections based on short-term data.  Volatility changes, and this data is only useful in the short-term.  It needs to be regularly updated to be of continuing help as one tool of many in your investment research and decision toolbox.

Disclosure: We own several of the securities named in this article in various managed accounts.

Securities named in the tables: BND, MUB, IRF, TLT, LQD, VEWHX, BWX, EMB, VCVSX, PFF, VTI, VEA, VWO, VGK, EPP, EWJ, FXI, IFN, EWZ, TIP, VNQ, DBC, GLD, USO, DBV, UUP.

Richard Shaw
QVM Group LLC

In this article, we provide short-term probable price range estimates for large-cap US stocks (SPY), China stocks (FXI), the US Dollar (UUP) and US long-term Treasuries (TLT).

Understanding and Managing Risk:

Gauging probabilities for uncertain future prices of highly variable securities is the kind of thing that options traders do all the time.  It is also something that stock and bond investors can do as part of their effort to understand and manage risks.

Of course, there are the exceptional shock events such as the world experienced in 2008 that fall well outside of normal probability ranges.  In a negative situation like that, protective stops or other active steps are necessary to just get out of the way.

Price changes could be flat, upward moving, or downward moving over any projection period, but the probability ranges derived with standard deviation data and a normal distribution curve assumption can bracket the range within which prices are likely to close.

The boundaries of those ranges can be useful in selecting stop loss trigger points or in selecting option strike prices, and generally to appreciate the level of risk or opportunity that may be present in the short-term for each security.

You need to apply additional fundamental or technical information and judgment to decide the direction of price movement.  Probability ranges simply help you understand the probable limits to price movement for a security over the selected number of forward market days, but do not suggest direction.

Statistical Tools:

While securities do not exhibit a perfect “normal” bell-shaped distribution of percentage price changes, most (but not all) of the time the pattern is reasonably close for general bracketing of probable price changes.

The pattern of likely future prices expands as the future date moves farther away form the current date.  In a “normal” distribution, the shape of the range of probable prices is conical (it expands as the time distance from the starting date increases).  Some people call those ranges “probability cones”.

If the price change distribution is approximately “normal” (a working assumption) and if you know the historical standard deviation of the percentage price changes, then you can make estimates of the range within which future prices will probably close.  You can do the same thing with implied future volatility in options, but not all securities have active options, making historical volatility more universally available.

The argument against historical volatility is expressed in the SEC’s obligatory caution to be made by advisors; “past performance is no guarantee of future performance”.  That said, the past is not irrelevant.  Back testing of probability cones using short to intermediate history shows them to be fairly good at bracketing short-term future price action — not perfect, but pretty good.

We like to look at 1-month and 3-month future periods, based on 1 and 2 standard deviations derived from several historical periods (252-days, 126-days, 63-days, and 21-days).  This post presents 1-month forward cones for those standard deviations derived from those historical periods.

One more time, remember that price range probability cones do not predict where within those ranges, either up or down, prices will close — just the range within which closing prices are likely to occur at selected levels of probability based on known historical volatility.  Less probable prices can and sometimes do occur outside of the probability cones .

Available Software Tool:

Metastock software has a built in function that calculates and plots the “probability cones” for any level of probability for any future period based on any past period of observations.  The charts in this post were developed with Metastock.

Price Range Probability Cones:

Here, we look at probable price ranges from October 7 through November 6, 2009 based on 68% probability (1 standard deviation) or 95% probability (2 standard deviations) for SPY, FXI, UUP and TLT.

For each chart, there are probability cones for four different historical periods of price variation. The red cones are based on the last 252 closing prices (1 year).  The green cones are based on the last 126 closing prices (6 months).  The blue cones are based on the last 63 closing prices (3 months).  The gold cones are based on the last 21 closing prices (1 month).  The thin purple lines are the 21-day high-low price channel for reference.

In some instances the 63-day and 21-day cones are so close that the gold is covered by the blue and cannot be seen.  It’s still there, just behind the blue.

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SPY 68% Probability

SPY 95% Probability

FXI 68% Probability

FXI 95% Probability

UUP 68% Probability

UUP 95% Probability

TLT 68% Probability

TLT 95% Probability

Securities Mentioned: SPY, FXI, UUP and TLT.

Disclosure:  We own SPY and FXI in some managed accounts.

Richard Shaw
QVM Group LLC

Asset Allocation Among Public Investment Funds:

This table shows the asset allocation among public investment funds available in the U.S.  segmented by equity funds, bond funds, money market funds and hybrid funds (they invest in both stock and bonds).  There is no separation of domestic, international and global assets in these data.

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These figures do not include variable annuities.  The figures do include assets from both individual investors and institutions or private funds that invest through public funds.

The current equity allocations are the lowest they have been in the past twelve years, except for 2008 and 2002, both bear market bottom areas. That suggests there is more money yet to be allocated to stocks as risk aversion abates.

Bond allocations are the highest they have been in twelve years, which we expect is as much a function of the aging baby boomers as it is risk aversion caused by the recent bear.

Money market assets are higher than the twelve-year average, but not as high as they were in 2008 or 2002.  What we don’t know is how much money market oriented cash has migrated to bank CD’s due to the combination of negligible money fund rates, and the loss of faith in the $1.00 fixed price of money funds due to the 2008 debt market liquidity freeze.

Hybrid funds have somewhat below average allocation, but the category is not major.

Keep Perspective When Reading News:

Beware of forming opinions with data out of context.  For example, on September 28, Bloomberg published an article with a correct fact, but perhaps a false implication.  The article was titled “Obama Stock Advance Persists on Money Fund Hoarding“. The first paragraph said:

“Americans holding $3.5 trillion in cash are giving money managers increasing confidence that the stock market rally under President Barack Obama will continue through the end of the year.“

The financial data is right (the Obama linkage to the money fund data is a gratuitous toss-in) and the implication that the entire $3.5 trillion may flow to stocks is essentially false.

By examining historical allocations, it is clear that over up and down cycles, there are substantial money fund holdings.  Over the past twelve years, the lowest money fund allocation among public funds was about 23%, which translates to a likely stable cash reserve in money funds today of about $2.3 trillion.

Our impression is in accord with the Bloomberg article, in that there is cash on the side to come into stocks, but we would judge the amount of money available for reallocation to stocks to be more like $1.2 trillion.  That amount is fairly consistent with a fact found later in the Bloomberg article, “Investors placed $1.45 trillion in U.S. money market funds in 2007 and 2008.”

It looks to us as if the amount of money that moved into money funds during the declining market is the amount of money that may come back to stocks, not the total amount in money funds.

Assets by Type of Fund:

Mutual funds in August accounted for 92.5% of public investment fund assets in the U.S., while ETFs accounted for only 5.7% of assets.  UITs and CEFs made up the difference.

Average Fund Dividend Rates:

In 2008, the total of all fund dividends (from interest and dividends received from fund underlying assets) was 2.66% of all fund assets — bond funds, stock funds, hybrid funds and money market funds combined.

Total Fund Assets:

Public investment funds available in the U.S. in August totaled $10.4 trillion.

U.S. Fund Assets vs Worldwide Fund Assets:

Total mutual fund  assets in the U.S. in 2008 were $9.7 trillion, while worldwide mutual fund assets were $19.0 trillion — 51% of worldwide mutual fund asset were in funds available through the U.S.

Index Funds:

Index funds have an increasing role in portfolios. In 2008, 13% of equity funds were index funds, up from 8.9% ten years earlier, and up from 3.3% fifteen years earlier.  S&P 500 index funds account for 40% of index fund assets.  That means that SPY, IVV, VFINX and other S&P 500 index funds account for 5.2% of public equity fund assets.

Number of Funds vs Number of Stocks:

There were over 10,000 public funds (8,889 mutual funds, 646 closed-end funds, and 743 ETFs) registered in the U.S at year-end 2008, which is substantially more than the number of US stocks that most investors would consider owning.

The S&P 500 index (proxy SPY or IVV) covers 500 stocks.  MSCI U.S. Prime Market index (proxy VTI) covers about 1,750 stocks.  The Russell 3000 index (proxy IWV) covers 3,000 stocks, and the Dow Jones Total Market index (proxy TMW) covers 5,000 stocks.

It’s been this way for a long time, but keep in mind that there are more investment funds available than there are individual stocks worth thinking about.  Are there really enough good ideas to support that many fund portfolios with differentiated composition, approach or results?  Probably not.

Allocation Redux:

After allocating the hybrid funds 60/40 to stocks/bonds (an assumption based on the “classic” balanced fund model), the current allocation of public fund assets available in the U.S. is about 47% equities, 19% bonds and 32% money market funds.

We speculate by looking at past allocations and the likely trend toward somewhat higher bond allocations, that when markets normalize, the average allocation will be something like: 55% to 60% equities, 30% to 35% bonds, and 5% to 10% money markets.

Of course averages can be deceptive.  Two investors, one 100% stock and one 100% bonds, have an average allocation of 50%/50%, yet neither looks anything like that.  Nonetheless, based on millions of accounts the averages are potentially helpful to understand as you decide to go with or against the crowd.

Richard Shaw
QVM Group LLC

Bonds are an important part of portfolios that deserve investigative attention too.

This article provides data for  bond funds of various types in terms of price rate of change (not total return) versus price volatility to help “do-it-yourself” investors with their bond fund decisions.

Fund total return is ultimately more important than price change in theory, but in practice price change tends to strongly drive entry and exit behavior (including stop loss orders on exchange traded funds), which modifies realized total return.  That makes examining price change a useful element in the full set of data for a bond fund.

To complement that data, we include a table of fundamental bond fund information, and a table of price change correlation to the aggregate bond index.

Reward-to-Risk Scatter Diagram (1-year):

A plot of the 1-year rate of price change (ended 9/11/2009) versus the 1-year price volatility for  20 types of bond funds plus preferred stocks, shows dramatic performance differences.

Developed markets local currency sovereign debt (BWX) generated the most favorable ratio reward-to-risk (rate-of-change divided by volatility).  Not far behind were actively managed global bonds by Loomis Sayles (LSGLX) and US agency backed mortgage securities (MBB).

On the other end of the scale, the most strongly unfavorable reward-to-risk ratio was for junk bonds (JNK), with a negative return and high volatility.  Preferred stocks (PFF) had a positive return, but more than ten times the volatility.

Less dramatic, but still unfavorable, were emerging market bonds, both local currency denominated (PLMDX) and US currency denominated (EMB), as well as convertible bonds (VCVSX), inflation protected Treasuries (TIP), long-term Treasuries (TLT) and actively managed unhedged international bonds (PFBDX).

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The next two tables, provide the detail supporting this reward-to-risk scatter diagram.  They also provide rate of change and volatility for several periods shorter than one year.

Rate of Price Change:

This table itemizes the price change of each fund type over one month, two months, three months, six months, and twelve months through 09/18/2009.

Price Volatility:

This table itemizes the volatility of each fund type over one month, two months, three months, six months, and twelve months through 09/18/2009.

Fundamental Data and Calendar Total Returns:

As you think through what types of bond funds you would like to include in your portfolio, this table (through 09/11/2009) of yields, expenses, duration, credit quality, 3-year total return and standard deviation, and calendar year total returns will be helpful too.

Price Change Correlation to Aggregate Bonds Index:

Finally, this table (through 09/18/2009) shows the correlation of daily price change to the aggregate bond index for one month, two months, three months, six months, and twelve months.

Collectively, data in this article may be helpful to you as a “do-it-yourself” investor when composing the bond portion of your portfolio.

Don’t forget to read the prospectus and to study the detailed holdings of each fund before investing.

Also, once you narrow your choice of funds, build a correlation matrix to make sure you are getting helpful correlation differences between and amongst the funds and the other non-bond assets under consideration.

Securities named in this article: BND MUB, VWSTX, TIP, VCVSX, MBB, SHV, IEF, TLT, BSV, BIV, BLV, LQD, JNK, LSGLX, PFBDX, RPIBX, BWX, EMB, PLMDX, PFF.

Disclosure:  We hold several of the named securities in various portfolios.

Richard Shaw
QVM Group LLC