It's All in the Math - Fixed Income Returns for the Decade Ahead (1 of 2)

It is becoming a more common belief that equity and bond market returns are likely to be lower than normal in the years ahead.  If proven out, this will have negative implications for the many retirement plans that have target return assumptions based off of historical norms.  Shortfalls in returns will require additional contributions - either out of corporate profits (for private plans), or out of the pockets of taxpayers (for public plans).  Expected blended return expectations remain above 7.5% for most plans.  Returns from traditional fixed income and equity markets will not reach this level and a rethinking of expectations and asset allocations will be necessary. 

Using models I originally developed in the late 1990’s, we can arrive at accurate return projections for both fixed income and global equity market over the coming decade. 

Starting with fixed income markets.  A bond is a fairly straight forward instrument with returns accruing to just four factors: the price paid, the coupon payments received, the reinvestment of those coupons and the ultimate return of principal.  Taking each in turn, we know the price paid.  We also know the coupon payments as they are contractual in nature.  The reinvestment return of these coupons is unknown; however, as I will demonstrate, even an immediate, radical move in interest rates will not dramatically change the overall return of a bond over its lifetime.  Finally, while return of principal to a single bond may be uncertain, when looking at the broader market of bonds of similar ratings, historical experience can provide a reasonable guide as to default and recovery rates.  Putting these together, estimating long-term bond returns is a very straight forward process.

 

AN EXAMPLE 

 

At July 30th, you could buy a ten-year US government note with a maturity of May 15, 2024 for a price of $99.49.  That note will pay a semi-annual coupon at an annual rate of 2.50%.  At maturity, an investor will receive $100 and along the way, twice yearly coupon payments of $1.25 (per $100 value).  While we do not know the rate at which those coupons will be reinvested, even if we assume rates rise by 500 basis points before the first coupon payment is received (to 7.56% across all maturities), the total annualized return from this note will rise only to 2.85% over the ten year period.  Conversely, if rates fell to zero and an investor received no return at all on the coupons, the ten year total annualized return on this note falls only to 2.29%.  Thus, assuming no default, one can not expect anything other than a return of between 2.29% and 2.85% from buying a ten-year US government note today.  Another way of looking at this is, assuming no risk of default, the best approximation of the long-term return on a bond is probably just its current yield (on the UST, currently 2.56%).  Of course, the road to that compounded annual return need not be smooth.  Outsized returns or losses in a near-year, will cause out-year returns in the other direction as the result is mathematically determined.

 

DEVELOPED MARKET SOVEREIGN DEBT

 

Looking at other developed government bond markets (G-7 plus Australia and Spain), we note 10-year yields between 0.53% (Japan) and 3.43% (Australia).  Assuming no risk of default, these again are the best estimate for annualized local currency returns over the coming decade. 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Source: Bloomberg

Of course, given the recent experience of certain governments (Argentina, Greece), zero chance of default might not be the best assumption.  If one wanted to insure themselves against default risk, we can look to the Credit Default Swap market to gauge the costs of protection.  Higher yielding markets such as Spain and Italy currently have annual “insurance” costs of 1.15% and 1.56%, respectively.  Perceived “safe” markets like the US and Germany have lower insurance costs of 0.25% and 0.42%, respectively.  Calculating the “net” return with insurance, we see a lower expectation for ten-year returns of between 2.87% (Australia) at the high end and -0.26% (Japan) at the low end.  Needless to say, developed market sovereign returns of 1% - 3% are not going to get plans to their return targets.

 

 

 

Source: Bloomberg

 

INVESTMENT GRADE, HIGH YIELD AND EMERGING MARKETS

 

Of course, government markets are not the only fixed income game in town.  Lower rated corporate credits, mortgage securities and the like broaden an investor’s opportunity set and we have seen dramatic evidence of plans reaching for yield over the past couple of years.  Still, like the sovereign bond markets, the current yield on these instruments, less an assumed default and recovery rate, makes for the best long-term expectations of their likely returns. 

While there are many segments within the broader fixed income universe, for the purposes of this posting, I have chosen to project returns for US High Yield, European High Yield, Emerging Market USD/EUR-Pay Sovereign and US Investment Grade segments – all fairly liquid markets.  Current Yields and Spreads (versus governments) are shown below.

	US High Yield	Euro High Yield	EM Sovereign	US Inv Grade
Current Spread	3.75	4.49	5.05	1.45
Historic Spread (Median)	5.34	5.89	4.78	1.97
Current YTM	5.90	4.49	6.84	4.65

Source: BofA Merrill Lynch, Brett Gallagher Calculations

Once again, assuming no default, Current Yield to Maturity is our best guess at the long-term return from the various fixed income segments (between 4.5% and 7.0% in this example).  However, as there is some realistic level of default expected in each of these riskier pools, building a sensitivity analysis around the historic default level and recovery rates makes sense (detailed in the tables below). 

For reasonable default and recovery assumptions, I turned to data gathered by Moody’s Investors Service which has compiled cumulative 10-year default percentages across a number of markets and ratings classes for the 10-year periods ending 1970 - 2013 and also used their observed historical recovery percentages. 

I have converted the cumulative default figures into annual ones (shown in parenthesis below).  For the sensitivity analysis, I use the Worst, 25th Percentile, Median, 75th Percentile and Best Case historical experiences - though I would expect the 25th to 75th percentile range to capture the most likely outcomes.  Because of the longer history of the US data, I use that experience for other speculative markets as well (note: using a common data set with an inception date of 1983, European High Yield and EM Sovereign Debt actually have lower default rates than the US Universe over the common period – thus my assumptions may be slightly conservative).  For recovery rates, the sovereign experience has been better than corporates by about 10 percentage points and is also reflected in the sensitivities.

10-Year Cumulative (Annual Equivalent) Default Rates (1970 - 2013)

	Investment Grade	US HY, Euro HY, EM Sovereign
Worst Case	10.33% (0.97%)	45.88% (3.85%)
25th Percentile	5.91% (0.58%)	38.93% (3.34%)
Median	4.89% (0.48%)	32.33% (2.84%)
75th Percentile	3.63% (0.36%)	18.80% (1.74%)
Best Case	1.26% (0.13%)	0.37% (0.04%)

Source: Moody’s, Brett Gallagher

Using a plausible range of default and recovery assumptions, we are now able to construct a narrow range of likely outcomes for nearly any fixed income segment we desire.  While the returns due to risk assets appear relatively attractive when compared with developed sovereign markets, the range of returns are far below historic experience and most investors assumed return assumptions. 

US High Yield Debt – Yield to Maturity 5.90%, Median 10-year Cumulative Default 32.3%

		Annualized Default Rates
Recovery Rate	4.31%	0.04%	1.74%	2.84%	3.34%	3.85%
	30.0%	5.76%	4.74%	4.12%	3.84%	3.57%
	35.0%	5.76%	4.80%	4.22%	3.96%	3.70%
	37.5%	5.76%	4.83%	4.27%	4.02%	3.77%
	40.0%	5.76%	4.86%	4.31%	4.08%	3.84%
	42.5%	5.76%	4.89%	4.36%	4.13%	3.90%
	45.0%	5.76%	4.92%	4.41%	4.19%	3.97%
	50.0%	5.76%	4.98%	4.51%	4.31%	4.10%

 

European High Yield Debt – Current Yield 4.49%, Median 10-year Cumulative Default 32.3%

           

		Annualized Default Rates
Recovery Rate	2.93%	0.04%	1.74%	2.84%	3.34%	3.85%
	30.0%	4.42%	3.36%	2.72%	2.44%	2.15%
	35.0%	4.42%	3.43%	2.83%	2.56%	2.30%
	37.5%	4.42%	3.46%	2.88%	2.63%	2.37%
	40.0%	4.42%	3.49%	2.93%	2.69%	2.44%
	42.5%	4.42%	3.53%	2.99%	2.75%	2.52%
	45.0%	4.42%	3.56%	3.04%	2.81%	2.59%
	50.0%	4.42%	3.62%	3.14%	2.93%	2.73%

US Investment Grade (Baa) – Current Yield 4.65%, Median 10-year Cumulative Default 4.89%

                       

		Annualized Default Rates
Recovery Rate	3.09%	0.04%	0.19%	0.23%	0.34%	0.52%
	30.0%	4.57%	4.47%	4.45%	4.38%	4.27%
	35.0%	4.57%	4.48%	4.46%	4.39%	4.29%
	37.5%	4.57%	4.49%	4.46%	4.40%	4.30%
	40.0%	4.57%	4.49%	4.47%	4.40%	4.31%
	42.5%	4.57%	4.49%	4.47%	4.41%	4.31%
	45.0%	4.57%	4.50%	4.47%	4.42%	4.32%
	50.0%	4.58%	4.50%	4.48%	4.43%	4.34%

 EM Sovereign (USD/EUR Pay) – Current Yield 6.84%, Median 10-year Cumulative Default 32.3%

                          

		Annualized Default Rates
Recovery Rate	5.21%	0.04%	1.74%	2.84%	3.34%	3.85%
	40.0%	6.64%	5.75%	5.21%	4.98%	4.74%
	45.0%	6.64%	5.81%	5.31%	5.09%	4.87%
	47.5%	6.64%	5.84%	5.35%	5.14%	4.93%
	50.0%	6.64%	5.87%	5.40%	5.20%	5.00%
	52.5%	6.64%	5.89%	5.45%	5.25%	5.06%
	55.0%	6.64%	5.92%	5.49%	5.31%	5.12%
	60.0%	6.64%	5.98%	5.59%	5.42%	5.25%

 

 

In my next post, I turn to global equity markets.

The Task of Capital Allocators

I had mentioned previously that I have been furiously at work on a new venture and that I would shortly have some news to report.  Today, I'd like to let you know what I have been up to.

For the past six months, I have been consulting with the Nile Capital Group, a private equity firm based in Los Angeles that provides capital and expertise to small and emerging asset managers.  As part of my work with them, I engaged in a study with a former colleague, Pranay Gupta, most recently the Chief Investment Officer for Lombard Odier in Hong Kong.

Pranay and I analyzed literally millions upon millions pieces of data (manipulating more than 20 million data points in all), examining monthly returns and the growth in Assets under Management (AUM) for over 50,000 US mutual funds - current and closed.  Portions of the full study can be obtained by interested consultants and institutional plan sponsors by contacting Nile directly. 

For my blog readers, I can share with you some of our findings.  Certain of these findings support prior research, while others are quite new - and I think illuminating.

1. Larger funds are benchmark huggers.  This is certainly not news to most investors, and whether the result is due to structural reasons (the strategies are too big and their trades influence the markets) or business ones ("we've succeed, so now let's not get fired") is of little consequence.  Statistically, you are likely to earn near-benchmark returns if you invest with a larger manager.

2. Small funds are the best performers.  However, I must offer a caveat - they are also the worst.  Thus, if you don't have the resources for, or skill in, manager selection, you need to hire someone to do it for you or should otherwise index.

3. There is a relationship between performance and a manager's ability to grow assets.  This conclusion may seem obvious, but there is more to it than most know.  Interestingly, the best performers are not the fastest growers - and the fastest growers are not the best performers.  Factors beyond performance strongly influence a manager's business success.  Also, it should be noted that once performance falls below the median, there is little distinction in asset gathering ability between funds.

• The fastest growing decile of managers have a performance rank somewhere in the middle of the second quartile.  In other words, you don't have to be great to grow.  Good is good enough.

• The best performing managers fall near the top of the second quartile in asset gathering ability.  Again, there is more to growth success than performance.  It is also true that performance has become a less important, though still positive, driver of asset growth since 2006.

4. As noted previously, the top asset gatherers (on average) are mid-second quartile performers.  However, over the three years following their success, they become, in aggregate, only slightly better than a median performer.


Connecting the Dots

If you want better than index performance, you need to find the right small manager in each asset class you are considering.  Assuming you select the right manager, this manager's success will result in a growth in their AUM and a diminuation of your alpha over time.  You will then have to go through the selection process again.  In the meantime, the manager has created a highly-valued annuity business.

The work of the plan sponsor includes helping their plans achieve a certain assumed rate of return through asset allocation and manager selection.  Depending upon the plan's return assumption and the returns actually realized, the employer may have to increase the annual amount contributed on behalf of employees should returns fall short. 

Today, most US defined benefit pension plans are underfunded and will either need to achieve better returns, or increase their funding amounts.  With taxpayers already strapped, the pursuit of higher returns matters more than ever.  Unfortunately, and as I will show in my annual long-term asset class return forecasts next month, almost all plans will fail to meet their assumed rate of returns in the coming decade (the National Association of State Retirement Administrators has reported that the average assumed rate of return for State plans is currently 7.72% - US Corporate assumptions are close, albeit slightly lower).

Thus, it becomes ever more important to find new asset vehicles to help achieve these goals.  One area plan sponsors should consider is not only investing with the best small managers, but also investing in the best small managers.

Also, in the interests of full disclosure, since May 1, 2014 I have been employed by Nile Capital Group and may continue in a similar role in the future.  This blog post is not a solicitation on behalf of any product, current or future, that may be offered by them.  The purpose of this blog is solely to convey the findings of the Gallagher/Gupta study and to suggest a potential course of exploration for plan sponsors, whether pursued on their own or through any other party.

Caveat Emptor

Regular readers of this blog and of my previous ramblings know that I am a skeptic when it comes to the reliability of government statistics.  Such figures are important to investors trying to understand the true state of the economy in which they are investing and, unfortunately, today are so manipulated (even by the government's own admission) as to be increasingly useless.

In the September 2013 post to this blog, "Lies, Damn Lies and Statistics", I took a look at the United States' monthly jobs report and noted how seasonal adjustments applied to the figures have gotten bigger over time and how the adjustment is almost always larger than the underlying number itself.  When the seasonal adjustment is stripped away and the underlying figures are smoothed, the health of the jobs economy can be quite different from what is reported as truth each month.  Similarly, while penning the quarterly CIO Letter at Artio Global Investors/Julius Baer, the figure that bothered me the most was the CPI, the Consumer Price Index, which I argued was no longer a price index with any relevance to the pocketbook of consumers.  Changes in the way the index has been constructed over time (including the 40% weight given to housing, of which 3/4 is based on a survey question asking homeowners what they think they could rent their house for) leaves the current release unrecognizable and not comparable to historic readings.

Today, though, I'd like to talk about GDP, Gross Domestic Product, or the value of goods and services produced within the borders of a given country.  And for this, we will look overseas.  GDP per capita is often used as a measure of a society's standard of living and changes in GDP are looked at to measure the health of an economy.  Therefore, you might agree, it would be a useful number for investors to know.

As reported by the Wall Street Journal on June 9th, Italy, the UK and Ireland will be changing the way they calculate GDP.  Going forward, they will included the "value" of the illegal economy -- i.e. drugs, prostitution, etc..  As a result, GDP will be larger, not because the economy has improved, but rather because the illicit portions of it will now be counted.  Debt to GDP figures will depict greater economic "health" as the denominator in the equation is increased.  In other words, links to the past will change.

Granted, one can argue whether legal or illegal, such activities are truly a part of the economy and their inclusion is overdue.  Fair enough.  However, when measuring illegal activity, assumptions have to be made.  Lots of assumptions - many more than in the reported economy.  And to the extent the underlying activities are large relative to the size of the economy, the assumptions used can distort the true state of being.  So let's look at how these numbers will be computed and adjusted.

Drugs

In the UK, the trade in six substances will be added to GDP - heroin, powder cocaine, crack, ecstasy, amphetamines and marijuana.  And here's where the math gets interesting.  According to a UK crime survey, the number of heroin users climbed to 38,000 in 2009 from 36,000 in 2003 (assumption #1).  The purity of the heroin has climbed to 43% from 33%, yet its price has fallen by 31% (assumptions #2 and #3).  So to measure the value of heroin in GDP, you take the base year (2003) sales of GBP 1.349 million and multiply by the increase in users (38,000 divided by 36,000) and then by the increase in price to get a base-level value of product sold.  Then you further multiply by the 2003 purity level and divide by the 2009 purity level to get the total value of heroin consumed (the purity adjustment is the hedonic, or quality adjustment, so prevalent in many economic statistics compiled today).

GBP 1.349 * (2009 heroin users/2003 heroin users) * price * (2003 purity/2009 purity)

You are not done yet.  Now you have to account for imported heroin and subtract that out of the total number as GDP is only value produced within a country's borders.  So based on another set of calculations using UK Border agency seizures and a UN estimate of the imported price level, this figure is calculated.  The total value of heroin to the UK economy is thus "exactly" GBP 536 million.

The value of the largest drug, crack, weighs in at GBP 2.9 billion - or as the Wall Street Journal points out, more than the GBP 2.5 billion in profits from Barclays, the nations largest bank and employer of approximately 60,000 Britons.

Prostitution

To measure prostitution, the measurements get a little more complex.  A 2004 survey estimated there were 58,000 prostitutes at work in the UK.  Since then, the population of men in the country older than 16 years has increased by 5%, so it is assumed the number of prostitutes has kept pace.  Using data from the Netherlands, it is further assumed each prostitute sees 25 clients each week and that in 2004 the price was GBP 55 per visit.  Lap dance prices in the country have climbed by 22% since then (and we know this how?), so it is assumed so has the price received by prostitutes.  These figures must then be adjusted by the purchases prostitutes make in the course of doing business as GDP only measures final sales, not intermediate sales (for example, if the Brown Forman company sells a bottle of Jack Daniels to my local liquor store and the liquor store then sells that bottle to me, only my purchase is included in calculating the value of GDP).  So, when a prostitute buys a condom it is not included in the value of GDP.  However, when a private person buys a condom, it is.  So total condom sales must be adjusted downward based on an assumption between professional and personal useage.  The same holds true for hotel rooms and any other consumables used in the provision of the prostitute's service.

Is there a point to all this?

The point I am making is that economic statistics are important and their estimation is hard enough.  When multiple assumptions are then mixed in, and the size of the underlying segment changed is large relative to the whole, the value of the resulting number has to be questioned - especially when making comparisons with previous measures of the same.  Unfortunately, many economic series including jobs, inflation and GDP are now all suspect.

Happy July 4th

Not So Random Thoughts

It has been a busy few months, not that the volume of postings to this blog (zero) is indicative. However, in the next few weeks, I will be able to share news regarding a new venture about which I am very excited and shortly thereafter release a white paper that I hope will cause many readers to reconsider the way they view the typical investment opportunity set.  But, until then, a lot has transpired in the global economy and I wanted to share with you some of what I think to be the most interesting and significant insights out there today.


THE RISK TRADE IS ON.  BUT FOR HOW LONG?

Plan sponsors and investors in general have become somewhat frustrated by the returns available from "low risk" investments such as cash and high grade bonds.  As a result they have progressively taken on greater amounts of risk in the quest for higher returns.  That is all well-and-good, but the question becomes whether and when they may have over reached and set themselves up for potential disappointment.

Consider:

• US Households now hold the largest percentage of their financial assets in risk assets (stocks, corporate bonds and mutual funds) since Q3 2000.  At 34.9% of total, holdings in these risk assets is just short of the 60-year high of 38.4% reached in Q1 2000 (blog).

• Spain, just a couple years ago, seemed on the verge of imploding.  This past month the Kingdom of Spain was able to issue notes that traded BELOW those of the US Government. Two years ago, they paid more than 7 percentage points more than Uncle Sam (article).  Even Greece has been able to issue bonds at a yield of 5% in spite of the fact that their finances (Debt/GDP) and employment situation are in worse shape than when the crisis began (blog).

• And even the riskiest markets are becoming more expensive.  Last year we saw investors gobble up offerings from Nigeria, Ghana, Mozambique and Zambia. The interest rate spread on Eurobonds issued by such frontier markets has fallen to below 400 basis points versus US Treasuries while the gap between JP Morgan's Emerging Market Bond Index and Frontier bond markets narrowed to a record 68 basis points this past month (article). 

In summary, spreads are narrow:

Issuers have flooded the markets:

And "safe" assets have been shunned:

Which raises the question of whether we've gone too far.  I don't believe we are there yet, but the caution lights are on and a reduction in risk is advised.  In a recent speech, Federal Reserve Governor Jeremy Stein cited the work of Harvard professors Robin Greenwood and Samuel Harrison who developed a credit-based early warning measure - simply the ratio of the volume of non-investment to investment grade issuance (rather than the more typical relative price measure, the comparison of spreads).  At prior stress points, this ratio reached extreme levels.  Though we are not quite there today, we are in the neighborhood (blog).  .  

STILL, THE SEARCH FOR RETURN CONTINUES

Traditional asset classes are getting pricey when measured against historical norms, whether we're looking at stock P/E ratios, bond yields or credit spreads.  So perhaps it's not surprising that hedge fund assets have reached new record highs as investors seek alternatives.  Hedge Fund tracking firm HFR noted that Assets Under Management at hedge funds reached new highs in each of the past seven quarters and that hedge funds now managed in excess of $2.7 trillion (article).  Yet, at the same time, hedge funds as a group posted their worst Q1 results in six years, and over the past 12 months, hedge funds were up just 8.53% compared to the S&P 500, up 19.32%.  Since the beginning of 2011, the HRF Equity Hedge Index (long/short funds) has actually lost more than 7% while the S&P is up 59% (article). Defenders of the industry will note that the word "hedge" implies they should lag in an up market because of the downside protection offered when things turn bad.  We will see, but investors should be very comfortable with the strategies employed by their managers and understand how they have performed in tough periods in the past, because the testing of the "hedge" may be forthcoming. 


WITH LITTLE HELP FROM EARNINGS

Over time, earnings drive stock prices - or so we have been led to believe.  In the short-run, this isn't necessarily the case as the value one places upon each dollar of earnings (the P/E ratio) can fluctuate based on expectations for the future or on current levels of risk tolerance (see above).  However, if earnings growth really is the longer-term fundamental link to equity performance, one might begin to get a little nervous.  From the last earnings peak (Q2 2007) through the first quarter of this year, we have seen the second weakest earnings cycle in more than 50 years.  Previous cycles have averaged 6.0% compounded annual growth as measured from peak-to-peak. Currently, we are on track for just 2.6% annualized -  and though well below the norm in terms of magnitude, in terms of duration, this cycle is just about average.

ROOKIE MISTAKES?

As interest rates hover near record lows, corporate treasurers have been quick to take advantage and lock-in the attractive funding costs.  Corporate debt levels have climbed, even as interest costs have fallen.  At the same time, the US Government has decided to issue its first-ever floating rate notes (FRN's).  Instead of locking in today's low rates, taxpayer interest costs will fluctuate in line with the market.  As rates rise, so will interest costs.  Should rates fall, costs may go down, though that benefit is limited as we are already close to the zero floor.  It seems to be a one-side trade and not one in the taxpayer interest.

Not to be outdone by the Treasury Department, the Federal Reserve has been lengthening the maturity of the Treasuries it holds in its portfolio.  The $2.3 trillion portfolio now shows bonds with a maturity of more than 10 years comprising 26% of holdings (versus 18% just four years ago).  Maturities of between five and ten years account for 37% of holdings versus 26% as recently as 2010.  Short-term notes (91 days to one year) were 23% of holdings prior to 2008.  Today they are zero.  This means, the Fed has taken on more interest rate risk just as rates trade near historic lows.

It appears the US Government (and by extension, taxpayers) have taken the opposite side of the bet from Corporate America.

THE DARK SIDE OF QE?

Supporters of the Federal Reserves' massive quantitative easing programs (aka QE1, 2 and 3), when confronted with the question of why things haven't worked out better, say "it wasn't big enough" - an argument that could be made no matter the size of the program or the outcome.

If you want to see what big does, however, just look at the Bank of Japan and their impact on the Japanese government bond market. The JGB market is larger in size than even the US Treasury market.  In spite of the smaller economy, the BoJ holds nearly the same amount of its own government debt as does the Fed.  So what can go wrong?  In reality, plenty.  The BoJ is, essentially, the Japanese bond market, having pushed all other players to the sideline.  For the first time in 13 years, the benchmark 10-year bond went untraded - not one single trade - for more than a day.  Overall trading volume is down nearly 70% from the same period last year.  When a central bank intervenes in a public market, prices are naturally distorted - in this case pushing yields lower than might be expected.  Given the lack of liquidity in the market, traders and investors worry what happens when the big buyer tries to catch his breath.  The answer is that yields can spike dramatically in a short period of time, leaving bond investors with large losses (article).  Better to sit on the sidelines or go elsewhere seems to be the result.

Meanwhile, savers are penalized while debtors reap the benefits of cheap money.  As discussed in a previous posting, "Winners and Losers (Nov 17, 2013), while the low interest rate policies have bailed out the banks, boosted the stock market and real estate, those with money on deposit have lost ground to inflation.  Richard Barrington, an analyst at Moneyrates.com, estimates that U.S. savers have lost $758 billion since the crisis began due to the erosion of purchasing power from the difference in interest earned and inflation  (article).  The McKinsey study cited in my earlier posting looked at the cost by estimating what savers could have earned had rates been in a more normal rate state relative to the level of inflation.  In either case, the costs are not insignificant.

HAVE I PAID MY FAIR SHARE YET?

And how can we let April 15th go by without commenting on taxes?  By this year's tax deadline, Americans as a group paid roughly $3 trillion in federal taxes and $1.5 trillion in state taxes, an amount greater than they will spend on the necessities of life - food, clothing and shelter (article). 

And, as the tax take has climbed, wealthier Americans continue to shoulder a larger portion of the federal tax burden.  According to the Tax Policy Center, the top 1% of earners, who take home 17% of all income, now pay 29.3% of all taxes (article). 

Many will argue that this is fair, or that the "rich" should do even more.  But just who are these 1% er's? According to a study by Thomas Hirschl of Cornell and Mark R. Rank of Washington University, 12% of the population will find themselves in the top 1 percent of the income distribution for at least one year during their career.  39% of Americans will spend at least a year in the top 5 percent and more than half will spend at least a year in the top 10%.  An astounding 73% will spend a year in the top 20 percent of the distribution. So rather than thinking of the top group as a fixed bastion of fat cats who deserve to be flayed annually, perhaps we should remember it is most people who dream the dream and often get pretty close, only to fail to stay there that are supposedly not paying their fair share (article).

But at least we're not the Europeans (yet).  The chart below from the consultancy of Ernst & Young shows the number of days of work it takes for citizens of a given country to pay their respective tax burden:

WHAT TO DO?

To those readers who agree that the topics raised about are potentially troublesome, the question of what to do next remains paramount.  With traditional asset classes historically expensive, economic growth below trend, the unknown consequences of Central Bank interventions yet to be felt and aggressive return hurdles to be met, we all have our work cut out.

I hope to offer at least one alternative in my coming white paper.  Please stay posted.

The Other Olympics

What do the United States and the United Kingdom have in common, economically, with Argentina, Pakistan, Uganda, Venezuela, Greece and North Korea?  Answer: they have all become less free over the past 20 years.

I am writing this note a bit later in the month than I normally do and will ascribe the delay to Olympic Fever.  Well, perhaps that’s an exaggeration, but I have to admit that I find something compelling about watching men and women fly down a hill, unprotected, at speeds greater than I than I am allowed on the freeway.  However, now that the athletic competition is over, I can turn my attention to the more important global competition, the Economic Olympics.

Every day of every year, companies and individuals compete economically.  Most are looking to enhance their own quality of life.  Some do better than others.  Some do worse.  Some of the outcome is due to the effort put forth.  Some of the outcome is due to the skills of the competing parties.  And some is due to the environment in which they operate.  It is the last of these that I look at in this month’s post.

About 15 years ago, I first came across the Wall Street Journal and Heritage Foundation’s annual Index of Economic Freedom and was immediately hooked.  This year’s release marks the 20^th anniversary of the index.  The concept of Economic Freedom and the construction of the index made intuitive sense to me.  As described by the authors, Economic Freedom is a condition where individuals are free to work, produce, consume, and invest in any way they please. It also describes a situation where governments allow labor, capital and goods to move freely, and where they refrain from the coercion or constraint of liberty.  In measuring economic freedom, the Index analyzes countries’ commitment to the rule of law, principles of limited government, regulatory efficiency, and open markets – what they refer to as the “four pillars”.

Each pillar is comprised of two to three sub-categories which themselves are comprised of a variety of quantitative and qualitative measures.  The four pillars and the ten sub-categories are:

• The Rule of Law (property rights, freedom from corruption);
• Limited Government (fiscal freedom, government spending);
• Regulatory Efficiency (business freedom, labor freedom, monetary freedom); and
• Open Markets (trade freedom, investment freedom, financial freedom).

Each of the ten economic freedoms within these categories is graded on a scale of 0 to 100. A country’s overall score is derived by averaging these ten economic freedoms, with equal weight being given to each (http://www.heritage.org/index/about).

This year, 186 countries were included in the study and 179 received scores.  While the difference in ranks should not be taken as a precise measure of guaranteed success (really, what is the difference between a score of 73.2 and 76.1?), countries can more easily be delineated into one of five broad classifications: Free (currently 6 countries), Mostly Free (28), Moderately Free (56), Mostly Unfree (61) and Repressed (27).  In addition to the broad classifications, I have always been interested in how countries have moved within the rankings.  I would find more comfort starting a business in a country, for example, that moved from 100 to 60, than in one that fell from 20 to 40.

This year, only six countries are considered truly Free.  They are (in order) Hong Kong, Singapore, Australia, Switzerland, New Zealand and Canada.  Hong Kong has remained the most free country since the inception of the study.  On the other hand, the United States’ score has now fallen in each of the past seven years; and while it was ranked as high as number five just six years ago, it is currently number 12.  The country, though, still remains Mostly Free.

With that in mind, I look to summarize the winners and losers over the past 20 years.  During this time, the general level of global economic freedom has increased, though it has not been consistent over time or across countries.  In addition, the size of the scored universe has increased meaning many countries have fallen in the rankings simply because new countries have entered, even though absolute scores may have increased. It is also harder to move up in the rankings when you already have a high freedom score and rank and it is easier to improve when you have a low rank and score.  With all these moving parts in mind, I have looked at winners and losers in a couple of different ways.  Note that this specific analysis of the data has not been endorsed by the authors and is mine entirely.  I would direct you to their complete study to see their conclusions.  That said, allow me to present my winners and losers.

The Winners

Only five countries moved up in the rankings during both the periods 1995 – 2004 and 2004 – 2014.  They are Bulgaria, Canada, Chile, Hungary and Sweden. In all of these cases, the absolute scores improved in both periods.  I consider these countries all Gold Medalists.

If, instead, I measure winners and rank countries by percentage improvement in score over the full period (and then eliminate any whose scores declined in the most recent 10-year period or which are not currently considered Moderately Free or better) I am left with 21 names – Romania, Albania, Poland, Bulgaria, Botswana, Hungary, Madagascar, Sweden, Peru, Malta, Ghana, Canada, Uruguay, Australia, Chile, Jordan, the Slovak Republic, the Philippines, Mexico, Singapore and Hong Kong.  All are interesting and comprise my Silver and Bronze Medalist lists.

The Losers

A much larger group of countries fell in the rankings during both periods, though as mentioned earlier, in many cases a fall in the absolute rank was due to an expansion of the number of countries scored in the study (up from 101 in 1995 to 155 in 2004 to 178 today).  Excluding those whose absolute score today is higher than it was in 1995, we are left with 27 countries who lost ground during both periods (the bolded countries are the larger and more investible).  They are Argentina, Belize, Costa Rica, Ecuador, El Salvador, France, Greece, Guatemala, Guinea, Italy, Morocco, North Korea, Oman, Pakistan, Panama, Sierra Leone, Sri Lanka, Swaziland, Thailand, The Bahamas, Tunisia, Uganda, the Ukraine, the United Kingdom, the United States, Venezuela and Zimbabwe. 

A smaller list of eight countries saw raw scores decline in both periods.  They were Argentina, Ecuador, Greece, Guinea, Panama, Venezuela and Thailand.  Of these, only Thailand and Panama remain in the Mostly Free category.  These are consistently bad players.

The countries whose score declined by the greatest percentage (and by at least 10%) over the past ten years include North Korea, Bolivia, Venezuela, the Central African Republic, Argentina, Turkmenistan, Equatorial Guinea, Cuba, Chad, Mauritania, Algeria, Trinidad and Tobago, Ecuador and Belize – on nobody’s list of economic paragons and, for the most part, not investible countries. 

Of the larger and more liquid countries, deterioration in Freedom scores of at least 5% over the past ten years were seen in Brazil, the Ukraine, South Africa, Greece, Ireland, Italy and Egypt.  Of these seven countries, only Ireland (solidly) and Italy (though just barely) remain in the Mostly Free category.  This should be disconcerting to those looking to start businesses or those who have large operations in these countries.

Economic Freedom scores are not, by themselves, an investment strategy.  Instead, they can be used as a risk measure and as a caution for companies with large investments in the less free regions.  Also they should serve as a wake up call for policy makers not in the Free or Mostly Free categories, or in those countries not moving up quickly from the lower ranks.

I Dream of Gini

Some who talk about inequality would like you to think they are talking about the plight of the poor.  In fact, the inequality gap tells you nothing about the life of those at the bottom of the income distribution.  Not understanding this can lead to dangerous policies which hurt the entire society, and perhaps the poor the most. 

In just the past few weeks, a ground swell of discussion regarding income inequality and its inherent evils has been heard.  The leader of the world's largest economy, US President Barrack Obama, as well as the moral leader of 1.2 billion Catholics, Pope Francis, have led the charge. 

Very quickly, US Media outlets picked up on the theme, praising both men whilst deploring the inequality problem.  Expect increasing chatter on this topic later in the month after the President delivers his State of the Union Address.

Before we get too far along, however, let me beg you to hold your applause.  What these gentlemen did (intentionally or not) was to equate income inequality with the plight of the unfortunate.  In fact, the two are not related and not understanding this will lead to the adoption of precisely the wrong economic policies.  Allow me to explain.

Just because the income gap between two people or groups is large or has grown, really tells us nothing about whether the gap is inherently good or bad or about the fate of each group.  Take the two person world of Oprah Winfrey (the highest paid celebrity of 2013) and Brett Gallagher.  The income gap is incomprehensible, I can assure you.  In a case like this one, any policy that focuses on a meaningful redistribution of wealth away from Ms. Winfrey would reduce both our incentives to work - a sub-optimal result for any society.  A slightly larger hypothetical might be the distribution of income at a successful hedge or private equity fund where the top partners walk away with a lion's share of the income, but where everyone does pretty well.

What some who talk about inequality want you to think is they are addressing the plight of the poorest.  As the preceding hypotheticals show, the inequality gap itself tells you nothing about the life of those at the bottom of the distribution.  Any policy that focuses directly on reducing the gap, rather than growing the pie is likely to produce perverse results.

Measuring Inequality

Before we can discuss inequality, we must measure it – a problem in and of itself.  The most commonly cited measure is the Gini Coefficient (sounds like "Jeanie").  The GC for any economy ranges from 0 (a perfectly equal distribution of income where the bottom 5% of the population make 5% of the income, the bottom 20% make 20%, and so on) to 1 (one person makes all the money).  Many pundits use results drawn from the GC to support redistribution conclusions – and they are wrong to do so.  Again, not only is inequality not an issue, but I would also guess the majority of its adopters also don’t understand the limitations of the Gini.

The mathematical formula for the calculation of this number is complex and would make little intuitive sense to most of us.  However, the concept itself is relatively easy to grasp.  Perfect equality, or a Gini equal to 0, is represented in the graph below by the straight line drawn at a 45 degree angle (where 5% of the people earn 5% of the income, etc).  In no society have we ever seen such a distribution.  Typically, the more realistic distribution is represented by a saucer-shaped line, drawn with an increasing slope, called the Lorenz Curve, below.  Such a depiction measures a situation where the lowest earners earn less a share of the income than their share of the population and the highest earners earn a greater share of the income than their representation in the economy.  The Gini Coefficient is the ratio of the area between the two lines (shaded Grey) and the total income (the sum of the Grey and Blue areas). The greater the inequality, the bigger the Gini Coefficient.

While this calculation may be a convenient way of capturing in one number the distribution of income in an economy, it does have numerous shortfalls that do not lend themselves to support many of the conclusions pundits have drawn.

First and foremost, the most oft cited measures of the GC do not take taxation into account.  Nor do they consider transfer payments received by the poorest.  When such figures are included, the differences in spending power within a given economy decreases universally.

Secondly, there are situations where a GC can rise (a supposedly a less equal income distribution), but where the ratio of incomes between the lowest and highest wage earners actually narrows.  What causes the GC to decline in such cases has more to do with the way income is spread amongst the middle portion of wage earners than just the spread between the highest and lowest.

Different income distributions
with the same Gini Index

Household Group	Country A Annual Income ($)	Country B Annual Income ($)
1	20,000	9,000
2	30,000	40,000
3	40,000	48,000
4	50,000	48,000
5	60,000	55,000
Total Income	$200,000	$200,000
Gini	0.2	0.2

Also, we can also look to the real-world example of China, where over the past two decades, between 400 and 600 million have been moved out of poverty (depending upon who you believe), yet where the GC has steadily increased.  In this case, the rising “inequality” of income has in-arguably been a very good thing.  Conversely, one might note in the preceding graphs for Greece and the US, "inequality" decreased during the recent economic troubles, yet few would argue that the poor were better off.

We can also show a homegrown example from the United States (1979 through 2010) where the GC rose from 0.40 to 0.47 (i.e. incomes became less “equal”), but where the lowest wage earners actually saw their incomes increase, even after adjusting for the drag of inflation.  In fact, those earning more than $100,000 (measured in 2010 dollars) rose from 11.5% of the population to 20.5% while those earning less than $35,000 fell from 38.6% of the population to 36.6% (those earning less than $15,000 fell from 14.6% to 13.1%).  In other words the US poor are better off than they were 30 years previously, even as the gap between them and the “rich” grew.  Unless envy is one’s true concern, anything which allows you to increase your quality of life should be viewed as a good thing – even if your neighbor’s quality of life improved more.

The following chart shows the progression of incomes in the United States, by quartile, over this time period.  Note, that these figures are pre-tax and pre-transfers, so the gap in disposable incomes is not as great as first appears.  What it does show, however, is that income growth for the poorest 50% of Americans has been anemic and that, not the gap, is the issue that must be addressed.

While I acknowledge that a dramatic difference between the “haves” and “have nots” can create stress within a society, I would also argue that it would be naïve for the government to proffer policies to address the “gap” itself, rather than trying to pursue policies that increase economic growth which lift all its citizens to a better life style.  Most would agree that we are not really better off as a society if we all have less.  So, when a political figure or media pundit calls for reducing inequality, an informed person should consider three things:

•        Are they really talking about the plight of the poor or are they just upset by the gap?
•        How do they measure the inequality they are talking about?  Are they literally measuring the difference between one sizeable segment of the population and another or are they looking at 500 CEO’s and comparing their income to that of the average worker (and then offering prescriptions that reach well beyond these “Fortunate 500”)?
•        Do the policies they put forth directly address the plight of the poor, or are they simply redistribution efforts which are unlikely to increase the economy’s overall wealth?

I am deeply worried that policies proposed in the name of helping the poor climb up the economic ladder (i.e. a sharp rise in the minimum wage - see Bill Gates comments here), will in reality result in anti-growth policies that will hurt us all.  An honest debate about the plight of the poorest among us, does not seem to be in the cards.

'Tis the Season(ality)

As we embark upon the holiday season, I wanted to take a moment to update a data set which relates to the seasonal performance of the S&P 500 industry groups.  The history runs monthly from January 1990 through November 2013 - nearly 24 years and 23 industry groupings.  

While using seasonal tendencies alone is not a robust investment strategy, it does add an interesting aspect to to the discussion.  I believe such analysis has the most relevancy when combined with relative valuation work (i.e. an industry group entering a seasonally strong/weak period is more likely to show its tendency if also supported by relative under/over valuation measures).

I also believe that many analysts make an easy mistake when discussing seasonality by choosing to comment on average relative performance.  The danger of using an average is that one or two very strong, or very weak observations can skew the general tendency.  For example, although the average relative performance in April of the Autos & Components sector is 4.91% better than that of the index (one of the strongest monthly outcomes), it has only outperformed in 13 of the 24 Aprils - just one observation away from a coin toss.

Therefore, to help overcome the tendency of averages to skew results, I prefer to rely on median performances and the absolute number of periods in which a sector has done better than the market.  Below I display the monthly median relative performance (blue) followed by the number of months in which the Auto & Components sector outperformed (yellow) the S&P 500.  There is very little seasonal tendency in this sector, save some weakness in May.

After examining 276 industry months (23 industries across 12 months), only 14 industries show performance consistency of 75% or greater in a given month.  In five of these instances we find industries which have outperformed, and another nine which have underperformed similarly.

The most seasonal sector would appear to be Capital Goods which appears three times (consistently strong in November and December and consistently weak in October).  The strongest seasonals though, would appear to be Software & Services in June (outperform 75% of the time, by a median of 2.19%) and Transportation in October (75% and 2.34%).  The weakest seasonal would be Food & Staples Retailers which tend to underperform in April 75% of the time by a median of 2.17%.

Seasonality is just a beginning and not an investment strategy in and of itself.  For those who would like to see the complete data file and graph set to combine with their own valuation work, please drop me an email and I will be happy to provide the full results.

Best Wishes to all for a Very Merry Christmas and a Happy New Year.