Attractive Relative Value in Chinese "BATJ" vs. U.S.-Based "FANG" Stocks

Consider the basic economic truth that faster GDP growth corresponds to higher revenue and earnings growth for companies, typically leading to higher stock returns over the long run.  With this principle in mind, let's take a look at the current market situation involving large-cap Internet stocks.

Due to governmental restrictions limiting access of companies seeking to do business in China, the global Internet economy naturally divides into two geographical regions:

• U.S.-based "global" Internet companies doing business everywhere except China:  Facebook (FB), Amazon (AMZN), Netflix (NFLX) and Google/Alphabet (GOOG), comprising the four so-called "FANG" stocks, represent the ex-China Internet economy; and
• Chinese Internet companies doing business primarily in China:  Baidu (BIDU), Alibaba (BABA), Tencent (TCEHY) and JD.com (JD), being the so-called "BAT" stocks plus JD.com, represent the analogous China-centric "BATJ" foursome.

As is reasonably expected in China's developing economy (annual GDP growth = 6% to 7%) which is growing faster than the global economy (annual GDP growth = 3%), the Chinese "BATJ" Internet stocks exhibit both historical and forecast revenue growth rates that are higher than growth rates for their U.S.-based "FANG" counterparts:

• Between 2013 and 2015, the "BATJ" companies (revenue growth = 42% to 55%) showed average revenue growth about 20 percentage points higher than the "FANG" companies (revenue growth = 25% to 31%);
• For 2016, the average revenue growth figures are comparable;
• For 2017 and 2018 (based on analysts' consensus estimates), the "BATJ" companies (revenue growth = 27% to 37%) are again ahead of the "FANG" companies (revenue growth = 21% to 27%), now by 6 to 10 percentage points.

Contrary to expectation based on revenue growth, observe that over the past five years the Chinese "BATJ" stocks have actually underperformed the U.S.-based "FANG" stocks.  Between year-end 2012 and yesterday (May 2, 2017),

• $100 invested in an equally weighted (25% in each of four stocks) "FANG" portfolio, rebalanced annually, would have grown to $581, while
• the same amount of money ($100) similarly invested in the "BATJ" portfolio (with Alibaba and JD.com purchased at the end of 2014 following their IPOs) would have resulted in the lesser sum of $315.

Using analysts' consensus estimates of next year's (calendar year 2018) earnings per share and earnings growth, we can examine current market valuation by considering the PEG ratio (P/E divided by earnings growth rate).  The table and graph below show this PEG ratio for both "FANG" and "BATJ" stocks.  Observe how the "BATJ" stocks (average PEG = 0.76) are currently trading at a more attractive (less expensive) average PEG ratio than the "FANG" stocks (average PEG = 1.08).

The outperformance of the "FANG" stocks over the past four to five years is reflected in the richness of their PEG ratio relative to the "BATJ" stocks:

• (2013-2017YTD return of "FANG")/(2013-2017YTD return of "BATJ") = 581/315 = 1.84
• (2018 PEG of "FANG")/(2018 PEG of "BATJ") = 1.08/0.76 = 1.42.

In other words, if the Chinese "BATJ" stocks were to rise 42% relative to the U.S.-based "FANG" stocks, the Chinese and U.S.-based stock porfolios would show comparable valuation ratios.  Such a prospective rise of the value of the Chinese portolio would close much of the performance gap between the two portfolios that has accumulated over the past four to five years.

Therefore, a rational investor might expect, assuming all else equal,  to see general outperformance of Chinese Internet stocks relative to U.S.-based Internet stocks over the next few years.

(Disclosure:  Author currently manages portfolios long BIDU and BABA.)

Net Worth Iso-Percentiles Across Age Brackets: The Wealth and Poverty of Our Nation In Five Pictures

The Rich . . .
(the 90th percentile and above, where the top 0.1%, the top 1%, and the top 10% reside)

. . . the Upper Middle . . .
(the 70th to 90th percentile, where college graduates tend to gather)

. . . the Middle . . .
(being the 30th to 70th percentile middle, the "heart of America")

. . . the Lower Middle . . .
(the 10th to 30th percentile, where iso-percentiles continue rising even into the septuagenarian and octogenarian age brackets)

. . . and the Poor
(the 10th percentile and below, including those over-indebted with negative net worth)

Data Source and Methodology: All data are extracted from the Federal Reserve's 2010 Survey of Consumer Finances, with data set last updated September 4, 2014. The Net Worth dollar figures are for households, inflation-adjusted to 2013 dollars. Percentiles are calculated by a) ordering the data by net worth within each age bracket and b) accumulating the statistical weights (included in the data set and associated with the Fed's multiple imputation technique) corresponding to the ordered data points.

Fed's Technical Note:  "Missing data in the survey have been imputed five times using a multiple imputation technique. The information is stored in five separate imputation replicates (implicates). Thus, for the 6,492 families interviewed for the survey, there are 32,460 records in the data set. Ten observations were deleted for the public version of the data set for purposes of disclosure avoidance; thus, there are 32,410 records in the public data set for 6,482 families."

The Shape of History: From Predictable West-East Oscillations to Mind-Boggling Singularity (or Nightfall?)

(Below is commentary on a history book worth reading:  Ian Morris, Why the West Rules—For Now:  The Patterns of History and What They Reveal About the Future.  New York:  Farrar, Straus, Giroux, 2010.  The well-written work offers valuable historical and geographical insight, providing indispensable background reading for any investors trying to make sense of global investment opportunities today.)

Ian Morris’s Why the West Rules—For Now is the most engrossing, expansive, evidence-based, single-volume story of humankind written to date.  The author’s personable presentation is an interdisciplinary magnum opus of big-history theorizing rooted in essential bean-counting analysis, running from the beginning of observable space-and-time over 13 billion years ago to our present-day global village, and even boldly projecting our (accelerating) development out into the foreseeable future (year 2103).  No work better bridges the gap between the humanities and the sciences—the book should be required summer reading for all freshmen entering college.

Morris’s thesis can be expressed in three words:  “Maps over chaps.”  That is to say, for measuring human “progress” (defined, following Herbert Spencer, as:  when the simple becomes more complex), geography (maps) has more explanatory power than biology and sociology (chaps—O.K., the author is British, and “humans and their relationships” hardly has the same snappy ring that “chaps” does).  Morris systematically tracks a “morally neutral” social development index (additional detail available) consisting of four components—energy capture, urban population, information processing, and war-making capacity—for both a Western core (SW Asia/Europe/U.S.) and an Eastern core (China/Japan) from 14,000 BCE to the present.  His thorough analysis explains how any historical West-East developmental differences are best attributable to geography, not race and culture, and how both long-term lock-in (West always ahead) and short-term accident (change driven by one-off flukes) models fail to explain the (oscillatory) patterns of history.  “Each age gets the thought it needs, dictated by the kind of problems that geography and social development force on it. . . . [P]eople accommodate their culture to the needs of social development,” says Morris.  (Note:  Jared Diamond explained how geographical advantage led to Eurasia’s socioeconomic domination over other continents.  Morris uses geography to explain differences in development between the Western and Eastern cores within the Eurasian continent.)

Keeping Score

Archeology reveals how biologically “modern” Homo sapiens walked out of Africa about 60,000 years ago, replacing Neanderthal, Peking Man and other varieties of humankind who had left Africa earlier.  Morris’s historical account “keeps score” as leadership oscillates between West and East, impacted by semi-hard ceilings on growth, paradoxical disadvantages of development, and oxymoronic advantages of backwardness:

1. 14,000 BCE to 600 CE:  West is ahead of East for almost 15,000 years.  Following the receding of the Last Glacial Maximum around 14,000 BCE, humans transition from roaming hunter-gatherers to settled agriculturalists, beginning in the most fertile areas (Hilly Flanks and Mesopotamia, and Yellow-Yangzi river valleys) of the Eurasian continent.  Villages become cities, then kingdoms and empires.  Megalomaniacal monuments include King Khufu’s 450-foot-high Great Pyramid in Egypt and the First Emperor’s 6,000-strong clay-soldier Terracotta Army (discovered only in 1974) in Chang’an (now Xi’an).  During the Axial Age from around 500 BCE, the moral foundation of “Man, as we know him today, came into being” (Karl Jaspers), with Confucian and Daoism (East), Buddhism and Jainism (South Asia), Greek philosophy and Judaism, Christianity and Islam (West).  By 1 CE, core population soars:  Rome (population 1 million) and Chang’an (pop. 500,000) in the Roman Empire and Han China, respectively;
2. 600 CE to 1750 CE:  East moves ahead of West for about 1,000 years.  Completion of the Grand Canal during the early 7^th century Sui Dynasty catalyzes growth, continuing into the Tang and Song Dynasties with Empress Wu Zetian in sprawling Chang’an and ironmasters in coal-rich Kaifeng (pop. 1 million each), the Yuan Dynasty with Marco Polo at Kubilai Khan’s court in the 1270s, the 15^th century Ming Dynasty with admiral Zheng He’s 300-vessel Treasure Fleets carrying 28,000 men, and the middle of the Qing Dynasty in the 18^th century.  During this time, the Roman Empire crumbles, Western development shifts to peripheral areas with expansion of the Habsburg, Holy Roman, Ottoman and Russian empires, and growth later returns to Italy during the Renaissance with Leonardo da Vinci, followed by Kepler in Germany and Newton in England (*); and
3. 1750 CE to Present:  West surges ahead of East for about 250 years.  Factors driving the rise of the West are:  the relative ease of traversing the Atlantic (the Pacific is broader and more difficult to sail round-trip), closure of the steppe highway by Romanov and Qing gun power (incidentally protecting Europe from disruptive invaders), and the higher economic incentive the West has to go East (appetite whetted by Marco Polo’s tales) than the East has to look West (China stops funding voyages showing little to no economic payoff).  The 18^th century Enlightenment is propelled by science and technology (Boulton and Watt’s efficient steam engine) and finance (banking hub in the Netherlands), and growth shifts to northwestern Europe (factories in Britain), followed by the U.S. (industrialization, stock ownership, and consumerism).  In the East, the core shifts to Japan (Tokyo is now the world’s largest urban area with 27 million people) before returning most recently to China.  The result is our present-day, precarious, China-as-creditor/America-as-debtor arrangement (coined “Chimerica” by historian Ferguson and economist Schularick).

Next comes Morris’s educated guess about what will happen next:

4. Future:  East again catches West.  “As surely as geography dictated that the West would rule, it also dictates that the East will catch up, exploiting the advantages of its backwardness until its social development overtakes the West’s.”

“But here we encounter another irony.  Rising social development has always changed the meaning of geography, and in the twenty-first century, development will rise so high that geography will cease to mean anything at all.  The only thing that will count is the race between a Singularity and Nightfall.” (p. 619)

If the “five horsemen of the apocalypse” (climate change, famine, mass migration, epidemic, and state failure) trample humankind during the next few decades, we will succumb to Isaac Asimov’s terrifying Lagashian Nightfall before reaching Ray Kurzweil’s enthusiastic vision of the Singularity, when human and machine intelligence (are projected to) merge by around 2040.  Morris’s extrapolation of his social development numbers shows East surpassing West around 2100; however, ironically, if we are “fortunate enough” to reach the Singularity before Nightfall, the distinction between West and East will no longer matter.  By that time, as “machine-enhanced, post-biological creatures,” we will come to realize the irrelevance of the quaint “West vs. East” squabbling that once preoccupied us when we were “mere biological humans” earlier in our evolutionary history!

If Morris’s informed wisdom is right, our future will be even weirder than Thomas Friedman’s “global weirding” (which itself is weirder than global warming).  Get used to it.  Prepare to see a warping of the shape of history over the next few decades as social and technological change accelerates to infinite speed! (**)

Towards a More Inclusive Theory

But, wait a minute.  Is Morris right about our future?  What if, instead of experiencing a Singularity, we continue to muddle through at conventional evolutionary speed?

Surely, Morris is a unifier.  By analogy, he is archeology and history’s Newton (classical mechanics) or, better yet, a Maxwell (classical electromagnetism), but not yet an Einstein (seeker of a complete unified field theory).  Similar to Maxwell, who taught us that light is a combination of electric and magnetic phenomena, Morris provides a way of viewing humanity across the West-East divide.  However, extending beyond Eurasia-centric West and East, a more comprehensive theory would need to include at least South and Southeast Asia (with India, Pakistan and Bangladesh, Indonesia and the Philippines), South and Central America (with Brazil and Mexico), and Africa (which by 2100 is projected to have 11 of the top 20 countries by population, including Nigeria, Tanzania, DR Congo, Ethiopia and Uganda in the top 10).  In a sense, Morris’s focus on Eurasia is an example of what he elsewhere calls “chainsaw art,” making crude cuts to exhibit gross features, while ignoring finer detailing.  Because in science a single exception is sufficient to invalidate a theory, the greater diversity of our world requires a broader scope encompassing the developmental history of all geographical regions, not just Eurasia.

Perhaps a more inclusive theory would shed light on the likelihood of some other region of our world rising to global leadership as we muddle along, “rarely knowing what we are doing,” as Morris says.  If it is true that “people—in large groups—are all much the same,” what is to prevent a crowded India, resource-rich Brazil, or quickly expanding Nigeria from one day leading the pack?  After all, they too must be as “lazy, greedy and frightened” as Eurasians, also “looking for easier, more profitable, and safer ways to do things,” right?  As technology becomes more available and affordable (ever ponder what happens when 3D-printing extends to food?), more rapid oscillations in development and shifts in world leadership could conceivably lie ahead.

Maybe a Singularity (or Nightfall) really is the most probable outcome, but from my humble perspective, claiming that cultural distinctions will be erased through a Singularity appears to be the “lazy” way out of a messy, multi-continental analysis—one that, if done properly, should embrace all of the greater complexity inherent in the colorful history and cultural diversity of humankind.

In Morris’s recounting, both “Albert in 1848 Beijing” and “Zheng in 1431 Tenochtitlan,” of course, were only fictional.  How about “Morris in the 2040 Singularity”?  Ian Morris was born in Stoke-on-Kent (also called Potteries—think “Wedgwood”), England, in 1960, and as a teenager in 1970s Britain “sat around wearing American jeans, watching American films, and playing American guitars.”  In the early 2000s, when Professor Morris was busy at Stanford researching and writing Why the West Rules—For Now, “the China price” became “the three scariest words in U.S. industry,” as made-in-China anything and everything hollowed out American manufacturing.  By the time the 2040s come around, will Chimerica prove to be reality or chimera?  By 2050, I hope to read Professor Emeritus Morris’s sequel, Why the West-East Divide No Longer Matters—For the Singularity is Here!  Or, might it be, Why the East Now Rules—For the Singularity Will be Late in Arriving?  Or, maybe even, Why Africa Rules—A Fortuitous 60,000 year Homecoming?

(*)  On p. 113 of Why the West Rules—For Now, Morris mentions Leo Tolstoy’s “odd excursus denying free will in history.”  He offers a slightly modified quote from the Second Epilogue, Chapter 11, of Tolstoy’s War and Peace that cites the laws of Kepler and Newton.  Next, Morris calls Tolstoy’s thinking “high-level nonsense.”  In my opinion, Morris is being (uncharacteristically, for his writing is otherwise quite level-headed and gentlemanly) too harsh and judgmental here.  As the next and final chapter in the Second Epilogue of War and Peace reveals, Tolstoy is posing two viewpoints for understanding history—an older one based on Ptolemaic-style individual free will (what Morris calls, “great men and bungling idiots”) and a newer one based on Copernican-style universal natural law (science-based).  Among these opposing viewpoints, Tolstoy states an intellectual preference for the utility of the universal-law approach over postulating individual free-will-based causes to explain historical events.

Tolstoy mentions an interesting analogy:  Just as we do not feel the earth’s motion (we think we are not moving) but must admit it (our motion) to understand the laws of astronomy, we also are not conscious of our dependence on everybody and every thing around us (we think we have free will) but must admit it (our lack of true freedom) in order to understand the laws of history.  In other words, as Einstein was so adept at showing us through his Gedanken experiments relating to relativity, one’s frame-of-reference matters, especially when theorizing.  Personally, I find more harmony than discord in the philosophy behind Tolstoy’s “odd excursus” and Morris’s own style of analysis.

(**)  As if global weirding and the Singularity are already not weird enough, consider philosopher Nick Bostrom’s “simulation argument” which, for our purposes, essentially states:  Assuming that a) the human species will most likely not become extinct before reaching “post-human” stage (i.e., we avoid Nightfall), and b) advanced civilizations, including our own, are prone to running simulations of their evolutionary history (and variations thereof), we are forced to conclude that, although we feel that we are “truly real” flesh and bones, we are, like it or not, almost certainly “merely artificial” beings living inside of a more advanced civilization’s simulation.  Now, that’s quite a humbling predicament for any free-willed humanist, isn’t it?

On Wealth Accumulation and Inheritance

While most of us are busily engrossed in our oh-so-American habit of trying to accumulate unbounded wealth, it is instructive to remind ourselves of the words of philanthropic wisdom penned by Andrew Carnegie more than a century ago:

"[T]he duty of the man of wealth . . . [is] to set an example of modest, unostentatious living, shunning display or extravagance; to provide moderately for the legitimate wants of those dependent upon him; and after doing so to consider all surplus revenues which come to him simply as trust funds which he is called upon to administer . . . to produce the most beneficial results for the community." (Andrew Carnegie, from essay on "Wealth" published in the North American Review, 1889)

A quintessential living example of Carnegie's model philanthropy of 1) living frugally, 2) providing modestly for the material well-being of family members, and 3) giving the remainder back to the community, is Chuck Feeney, the so-called "billionaire who wasn't":

"He was prepared [in 1997] to reveal his secret to the world, that he was not a billionaire, as he was usually referred to in the business pages, and that he had long ago given everything, including his DFS [Duty Free Shoppers] shares and his businesses, to his two philanthropic foundations, the Atlantic Foundation and the Atlantic Trust, based in Bermuda. He was personally worth less than $2 million, a fact known only to a tight circle of family and friends. . . ." (excerpt from Conor O'Clery, The Billionaire Who Wasn't: How Chuck Feeney Secretly Made and Gave Away a Fortune, 2007)

Apparently, at least for Feeney in 1997 at the age of 65, less than $2 million out of his $4 billion fortune is all that he felt necessary to retain to assure his (and his wife's) own personal financial security during the remainder of their lifetime.

Taken together, the above two quotes on philanthropy provide what I consider to be valuable ancillary guidance on inheritance, particularly for any parents deliberating over how much wealth to leave to their children:

a. "Provide moderately for the legitimate wants of those dependent upon [them]": Though Carnegie is not more specific on this point in his "Wealth" essay, it seems fair to interpret "legitimate wants" to range from basic needs to a modest though comfortable lifestyle, and "those dependent on [them]" to refer to children of minor age and any dependents of majority age in need of funds due to illness, unemployment or other significant financial setbacks in life;

b. "Less than $2 million": If a person who made not "just" millions but billions of dollars can feel secure retaining less than $2 million in personal wealth, then we can reasonably infer that anyone outside of this rarified circle of billionaires ought to require no more than $2 million to feel materially content. In other words, we should interpret $2 million as an upper limit on the total amount of accumulated wealth that a single individual or married couple could possibly require to meet personal needs, including whatever earnings and savings they are able to realize through their own efforts prior to considering any inheritance.

The implication here is that parents should not feel obligated to bequeath to their children any more than $2 million minus whatever the children are able to accumulate through their own careers, and for children with high earnings power this means no inheritance whatsoever is in order. As Carnegie states, most giving spreads "a spirit of dependence on alms, when what is essential for progress is that they [the recipients] should be inspired to depend on their own exertions." In an even earlier age, Plutarch issued the warning, "he that first gave thee money made thee idle, and is the cause of this base and dishonorable way of living."

My own view is that the best gift that parents can provide their children is making sure that the children learn by the time they reach adulthood how to educate themselves, earn their own living and save for retirement through their own effort and ingenuity, without counting on any inheritance to be forthcoming from parents or the proverbial "rich uncle." Large gifts of money and assets unfortunately subject recipients to the risk of reduced motivation and deflated self-esteem, arguably to a larger extent than providing any real benefit to their material well-being. After children reach adulthood, parents should, while continuing to offer open-minded and big-hearted emotional support, provide for their children (and grandchildren) not much more than a financial safety net, similar in substance to temporary unemployment benefits--all in the spirit of, as Carnegie put it, "helping those who will help themselves."

How Guessing Market Direction Can Be PREDICTABLY Bad for Your Financial Health

"The game is called probability guessing. . . . [S]ubjects are shown a series of cards or lights which can have two colors, say green and red . . . appear[ing] . . . with different probabilities but otherwise without a pattern. . . . The task of the subject, after watching for a while, is to predict whether each new member of the sequence will be red or green. . . . Humans usually try to guess the pattern, and in the process we allow ourselves to be outperformed by a rat. . . ." (excerpt from Leonard Mlodinow's The Drunkard's Walk--How Randomness Rules Our Lives, 2008)

In a stock market context, the probability guessing game described above would read like this: In any given year, the stock market either rises (green) or falls (red). If we look over the past six decades, from 1950 through 2009, we find that during the sequential decades (1950s, 1960s, and so on) the S&P 500 Index rose in 8, 6, 7, 9, 8 and 6 out of the 10 years (using data from Yahoo! Finance). In other words, during a "typical" decade annual stock market returns are "green" about 7 or 8 out of the 10 years, and "red" about 2 or 3 out of the 10 years. Based on these historical data, we can infer that the stock market tends to rise during any particular calendar with a probability of about 75%, and fall with a probability of about 25%. As investors, we, of course, would like to try to predict whether this year (or next year, or any future year for that matter) will be green or red.

For us investors, the million-dollar question is: Should an investor attempt to "time" the market, by investing in stocks during years the market is more likely (in the investor's opinion) to rise and staying out of the market during other years when the market is more likely (again, in the investor's opinion) to fall?

Obviously, if the investor truly has enough information, foresight or precognition to know with a high degree of certainty when the market will rise or fall, then market-timing makes perfect sense and will lead to higher returns. However, what happens if the investor only believes that he knows but actually does not, so that for all practical purposes the investor is really faced with the 75% green versus 25% red probabilities described above? Is any harm done by guessing?

Analogous to the general guessing game Mlodinow mentions in his book, let's consider two strategies:

1. Buy-and-Hold Strategy: Since the market rises during 75% of the years, one could just go long the market by buying an exchange-traded fund tracking the S&P 500 Index (or buying individual stocks), without attempting to time the market at all. A buy-and-hold investor can expect to generate positive returns 75% of the years but must also accept the unavoidable "fact" that the market will typically fall 25% of the time. In this "simpleton" strategy, an investor's long-run win percentage (i.e., the percentage of years the investor's portfolio will show positive returns) is expected to be 75%;

2. Market-Timing Strategy: A presumably more "sophisticated" investor will, through some combination of fundamental and technical analysis and application of his general intelligence and market wisdom, come up with a convincing explanation for why the market is more likely to rise (or fall) during any particular year. Believing he can distinguish beforehand (i.e., predict) which years are among the 75% "green" years when the market will rise and, likewise, which years are among the 25% "red" years when the market will fall, such an investor will want to go long 75% of the time and stay out of (or go short) the market 25% of the time.

If the bright and sophisticated market-timing investor has an "edge" over the the naive and unthinking buy-and-hold simpletons, then he will end up being right more than 75% of the time and will show higher long-run returns. At the other extreme, if it turns out that the market-timer only believes he has an edge but actually does not, one would think that his edge would just vanish and there should be no penalty for guessing, right?

Well, you might think that guessing carries no penalty, but that's actually wrong! Quite counter-intuitively, investors should expect lower returns when they guess. Here's why.

Let p be the (stationary) probability that the the market will rise in a given year, i.e., p = 0.75, representing the 75% "green" probability. Supposing that the market-timer's guesses do not give him any significant edge, his overall win percentage is given by a straightforward weighted-probability calculation:

Market-Timer's Win Percentage
= (Portion of time the market-timer goes long) x (Probability that market rises)
+ (Portion of time the market-timer stays out of market) x (Probabiility that market falls)
= p x p + (1 - p) x (1 - p)
= p² + (1 - 2p + p²)
= 2p² - 2p + 1.

On the other hand, the Buy-and-Hold Investor's Win Percentage is just p, as we saw earlier. Consequently, we may write that the expected potential downside of the market-timing strategy versus the buy-and-hold strategy is the difference:

(Buy-and-Hold Investor's Win Percentage) - (Market-Timer's Win Percentage)
= p - (2p² - 2p + 1)
= -2p² + 3p - 1
= 2(p - 0.5)(1 - p),

where the last expression is the factored-form equivalent of the quadratic polynomial in the previous line.

From the factored-form expression, we can easily see that whenever p is in the "physical" range (i.e., consistent with the probabilities indicated by market history for a wide variety of investment time windows) from 0.5 to 1.0, a buy-and-hold investor is expected to outperform any market-timer who is really just guessing without appealing to any special knowledge of market direction. In particular, when p = 0.75 (which is the historical win-percentage for a sequence of annual returns), the Market-Timer's Win Percentage becomes 2(0.75)² - 2(0.75) + 1 = 0.625, or 62.5%, which is 12.5 percentage points worse than the Buy-and-Hold Win Percentage of 75%.

Therefore, to the extent that a market-timer is "only guessing" (and who can really be so certain?) about market direction, he is (presumably unknowingly) effectively "shooting himself in the foot," following a self-destructive path of degrading his expected returns by staying out of the market 25% of the time (by the way, shorting the market 25% of the time would make matters even worse). Despite his seemingly sophisticated ways, this market-timer can actually be expected to underperform the simpleton buy-and-hold investor in the long-run.

Lesson: Don't attempt to "time the market" unless you are absolutely certain that your market-timing strategy actually works, since your expected downside from "believing without knowing" far exceeds your time spent strategizing, not to mention your trading costs and commissions consumed.

Perpetual Income Generation

A student who earned a few thousand dollars over the summer working remarked to me yesterday, "I don't know how I'm going to spend the money if I don't use it to travel over the holidays."

At first, this statement seemed quite innocuous, in line with what I have come to expect in our work-and-spend, consumer-oriented society. People earn money working and then, quite predictably, spend the bulk of their earnings soon thereafter, buying all types of consumer goods and services with whatever remains after paying for life's essentials.

Three Personal Financial Management Philosophies

Upon further consideration, I became struck with just how one-sided the student's attitude on what to do with his money is. On the spectrum of personal money management philosophies, he is at the consumerist end of the two extremes:

Consumerist Philosophy: Earn and spend; earn and spend; earn and spend. In short, spend all of today's earnings on consumer items, because another paycheck will always come "tomorrow." Examples of this type of philosophy include people who live paycheck-to-paycheck more by choice than circumstance, the young woman from England who won a multi-million dollar lottery six years ago at the age of 16 and now regrets having spent all of the money so frivolously, and highly successful, high-income celebrities like photographer, Annie Leibovitz, and singer, Michael Jackson, who, despite their millions in earnings, have ended up "awash in debt" due to their personal financial management, or lack thereof.

Wealth Accumulator's Philosophy: What's important is accumulating as much wealth as possible during one's lifetime. Be frugal, even to the point of being miserly. Save as much as possible from one's earnings, prudently invest one's savings, and reinvest as much as possible of one's investment earnings. An example of this type of thinking is self-made billionaire, Warren Buffett, who not only is worth some $40 billion but is rumored to have once stooped down to pick up a penny in an elevator, remarking to those around him, "This is the start of my next billion."

My opinion is that most of us will be best off following neither of the above extremes but, instead, adopting a middle-of-the-road philosophy, which emphasizes neither consumer spending nor wealth accumulation:

Perpetual Income Generation: Use one's "excess" earnings (i.e., whatever is not needed to pay for basic necessities) from work and investments to build an investment portfolio that will reliably generate long-term income to cover all of life's expenses. The focus here is neither on spending all of one's earnings, just because one has money currently available to spend, nor on stockpiling cash without limit, primarily to see how much wealth one can accumulate. Rather, the core of this philosophy is to accumulate enough wealth to reach an ongoing state of financial independence, which means that the income generated from one's investment portfolio should over time be enough to support one's lifestyle without relying on external employment.

Historical Analogies

I'm now reading Jared Diamond's insightful work, Guns, Germs, and Steel, which discusses how and why some societies developed farming and technologies and came to dominate societies that remained hunter-gatherers throughout the millennia since the most recent Ice Age some 13,000 years ago. We can draw a simplistic analogy between hunter-gatherer societies and the consumerist philosophy mentioned above, since both emphasize current consumption without any significant savings component. Similarly, agricultural societies may be compared to the wealth accumulator's philosophy, since any excess harvest can be stored or sold for income, allowing for investment in technology development, which in turn can be used to promote further wealth accumulation.

As Diamond mentions, the recurring pattern throughout history has been that agriculture-based societies have not only developed better technology but have also deployed it to exploit societies having more primitive technology. A striking 19th century example is how, in December 1835, a group of 900 Maoris from New Zealand's North Island sailed 500 miles east to the Chatham Islands and conquered a peaceful society of 2,000 Moriori hunter-gatherers, brutally and indiscriminately killing men, women and children who refused to become their slaves. Apparently, what induced the Maoris to attack the Morioris en masse was news from a seal-hunting ship that visited the Chathams, revealing islands rich in shellfish, eels and berries, with inhabitants who "do not understand how to fight, and have no weapons."

Such are the tragic consequences of the collision of societies. Other well-known examples range from the probable driving of the Neanderthals into extinction by Cro-Magnons some 40,000 years ago, to Cortes's and Pizarro's 16th century conquests of the Aztec and Inca empires, respectively, to the so-called Manifest Destiny of European settlers in the 19th century to expand across North America, decimating native Indian tribes in their path.

I mention these historical analogies because of the perspective they bring to personal financial management. As history shows, societies that have had a "savings" component in their culture have inexorably won an upper hand over societies with more purely consumption-oriented habits. If taken to the extreme, this might seem to indicate that pure wealth accumulation should be, at least from a survival point of view, our preferred personal financial management strategy. Hence, my advice to the student I mentioned at the outset could be to save all of his summer earnings in order to maximize wealth accumulation, but is this really best?

Goal: Perpetual Income

Pure consumers live for the present, much as hunter-gatherer societies have throughout history. On the other hand, pure wealth accumulators emphasize the future, based on a "stockpiling" mentality that always favors acquiring more, no matter how much one already has. Rather than simply consuming or saving, it is, in my judgment, critical to forecast one's future financial needs and reach the right balance between consumption and savings that will best optimize one's overall life satisfaction.

So, my advice to the student is: Instead of focussing on how to spend your earnings, or saving all of it for the future, ask yourself how best to utilize your earnings to begin to create a perpetual income stream that will allow you to gain financial independence and support your future lifestyle. Your focus should be neither on consumption nor on wealth accumulation, but on how best to employ your earnings, consumption, savings and investments to one day to replace your own labor as the primary source of income in your life. (Note: Some people call it "retirement," but for me it's closer to financial "rebirth.")

College and Salary: "With Whom" You Study Matters as Much as "What" You Study

The topic of how attending a "good college" relates to getting a "good job" came up in a recent conversation I was having with my high school-aged son, whom I am encouraging to give serious consideration to both what he enjoys doing and what type of lifestyle he wants to have after he graduates from college.

Using the popular U.S. News & World Report ranking of universities and salary data from Payscale.com, we can take a look at the correlation between university attended and resulting mid-career median salary. The table below shows the top 30 U.S. universities and the mid-career median salary of their graduates.



As might be expected, Ivy League schools (Harvard, Princeton, Yale, University of Pennsylvania, Columbia, Dartmouth, Cornell and Brown) figure prominently on the list, along with the well-known science and engineering schools (Caltech, MIT) and the so-called non-Ivy Ivies (Stanford, University of Chicago, Duke, etc.).

The relationship between university attended and salary can be seen in the graph below.



The regression line is:

Mid-Career Median Salary = $121,400 - $900 x (Ranking of University Attended),

giving a decrement of about $9,000 in annual salary for each 10 spots in university ranking. For example, a graduate of a university with a ranking of about 5 might expect to have a mid-career salary of about $9,000 more per year than a graduate of a university with a ranking of about 15. The numbers actually show more scatter and skew than is captured by the linear regression, as evident in the following examples of ranking-university-salary:

4. Caltech, $115,000
5. MIT, $126,000
6. Stanford, $124,000

14. Johns Hopkins, $94,900
15. Cornell, $106,000
16. Brown, $107,000

24. UCLA, $97,000
25. University of Virginia, $97,200
26. USC, $103,000.

The general trend of higher ranking (smaller number) correlated to higher salary (correlation of .63) is clear. While there are, of course, many individual exceptions to the rule, one of the tell-tale indicators for predicting lifetime earnings and net worth is the college one attends.

As I tell my son, the college one attends (i.e., with whom one studies) is just as important as what one studies in college. Choice of a college typically has a lifelong impact on one's social circle, which in turn often influences whom one does business with throughout one's career.

The Impact of Sidelined Cash in Disequilibrium on the Stock Market

The purpose of this note is to reconcile two contrasting viewpoints on how the amount of cash in our economy impacts future stock prices:

A. Sidelined Cash View: An example of the view that cash held in investor accounts matters is Alexander Green's commentary this week: 'In February . . . the decline in stocks was just about over [because] . . . [t]here was more money available to buy shares than at any time in almost two decades. The $8.85 trillion held in cash, bank deposits and money market funds was equal to 74% of the market value of U.S. companies, the highest ratio since 1990, according to the Federal Reserve. . . . [T]here is still over $8 trillion on the sidelines earning next to nothing in short-term deposits. . . . Expect to see cash coming off the sidelines to accumulate shares of the largest, most liquid firms around the globe.'

B. Equilibrium View: The opposite view, that consideration of market equilibrium reveals the "tautology" of speaking about cash on the sidelines, is voiced by John Hussman in his comment this week: '[A]s a result of more than a trillion dollars of new issuance of Treasury securities with relatively short durations, it is a tautology that there is a mountain of what is mistakenly viewed as “cash on the sidelines” invested in these securities. This mountain of “sideline cash” exists and must continue to exist as long as these additional government securities remain outstanding. It is an error to view outstanding debt securities as if they are “liquidity” poised to “flow back into the stock market.” The faith in that myth may very well spur some speculation in stocks, but it is a belief that is utterly detached from reality. The mountain of outstanding money market securities is the result of government debt issuance that must be held by somebody until those securities are retired. It is not spendable “liquidity” – it is a pile of IOUs printed up as evidence of money that has already been squandered. The analysts and financial news reporters who observe this enormous swamp of short-term money market securities, and talk about “cash on the sidelines” as if it is spendable in aggregate immediately reveal themselves to be unaware of the concept of equilibrium and of the nature of secondary markets (where there must be a buyer for every security sold, and a seller for every security bought).'

Which view is right? Is it useful from a trading or investment timing perspective to think of sidelined cash as waiting to flow back into the stock market? Or, does any particular stock transaction involve a mere transfer of cash from buyer to seller and, therefore, leave the aggregate amount of cash in the economy, sidelined or not, unchanged? Further, what is the long-run impact of the amount of cash in our economy, i.e., the money supply, on stock prices?

The Fed, the Treasury and the Private Sector

Three primary parties feature in our analysis: the Federal Reserve ("Fed"), the U.S. Treasury and the private sector. To illuminate essential points, I intentionally employ a "no frills" simplified model of the creation of cash (or, more generally, a broader measure, M2), bonds and stocks in the economy:

1. Cash Creation and Swap: The Fed creates cash (in the amount of 50 units) and swaps it with the Treasury for a like notional amount of newly issued government bonds.

Fed: Cash = -50, Bonds = 50
Treasury: Cash = 50, Bonds = -50

(In each of the skeletal balance sheets here and below, the sections shown in bold indicate a change from the immediately prior stage of the analysis.)

2. Deficit Spending: The government uses the cash to finance expenditures such as national security, infrastructure projects, entitlements and other deficit spending. The private sector ends up holding the cash, received from the government through employment and entitlements.

Fed: Cash = -50, Bonds = 50
Treasury: Cash = 0, Bonds = -50
Private Sector: Cash = 50

3. More Bond Issuance: The Treasury issues more bonds, this time to private sector investors instead of to the Fed.

Fed: Cash = -50, Bonds = 50
Treasury: Cash = 50, Bonds = -100
Private Sector: Cash = 0, Bonds = 50

4. More Deficit Spending: The government deploys the cash in accordance with its budget, with the private sector again being the recipient of the cash.

Fed: Cash = -50, Bonds = 50
Treasury: Cash = 0, Bonds = -100
Private Sector: Cash = 50, Bonds = 50

5. Entrepreneur-Led Growth: Assisted by years of government spending on infrastructure, enterprising individuals form companies and develop new technologies and products for growing consumer markets. Rising stock prices of these entrepreneurial companies represent new wealth creation, seemingly materializing "out of thin air," but actually resulting from the "value-add" through conversion of natural resources, labor, capital and technology into useful products and services.

Fed: Cash = -50, Bonds = 50
Treasury: Cash = 0, Bonds = -100
Private Sector: Cash = 50, Bonds = 50, Stocks = 100

6. Business Cycle: As the market's perception of future business prospects shifts, stock prices rise and fall. The corresponding aggregate wealth held by the private sector in stocks fluctuates from a cycle low of, say, 75, to a cycle high of, say, 150. At the nadir of the business cycle, the corresponding cash-to-stocks ratio is 50/75 = 67%, while at the peak this ratio is 50/150 = 33%.

7. Government's Rescue Plan: During the depths of an extended recession (i.e., when stocks = 75), the government implements an economic rescue plan, involving

a. Creation of more money (25) by the Fed;
b. The Fed's use of this money to purchase lower credit assets from banks;
c. Banks' use of the proceeds to purchase new bonds from the Treasury.

This plan strengthens bank balance sheets and provides the government with cash for new deficit spending. (By deliberate design, this model parallels the actions taken by the Fed and Treasury over the past half year in dealing with the current financial crisis.)

Fed: Cash = -75, Bonds = 50, Other Assets = 25
Treasury: Cash = 25, Bonds = -125
Banks: Bonds = 25, Other Assets = -25
Private Sector: Cash = 50, Bonds = 50, Stocks = 75.

8. Still More Deficit Spending: The government deploys its new cash of 25 as part of a stimulus package to jump-start the economy (cf., Obama's approximately $1 trillion fiscal stimulus package, currently being deployed). As before, the cash ends up in the hands of workers and consumers in the private sector.

Fed: Cash = -75, Bonds = 50, Other Assets = 25
Treasury: Cash = 0, Bonds = -125
Banks: Bonds = 25, Other Assets = -25
Private Sector: Cash = 75, Bonds = 50, Stocks = 75.

The result is an increase in the cash-to-stocks ratio to 75/75 = 100%, which is a sign of the gross disequilibrium now inherent in the economy, since the cash-to-stocks ratio is outside of its "normal" range of 33% to 67% shown in Stage 6 of our model.

How Both Views Can Be Right

First, although our model is very simple, it exhibits important monetary, fiscal and economic trends in the U.S. economy:

• The amount of cash in the economy increases over time (from 0 to 75 in our model) as the economy grows and the Fed prints money to provide a currency to accommodate transactions among consumers and producers;
• The amount of government debt increases over time (from 0 to 125 in our model) as the Treasury issues bonds to fund the government's growing budget deficit;
• The value of the stock market rises secularly (from 0 to 100 in our model) as innovation, population growth and economic growth drive aggregate earnings of companies higher;
• Also, stock prices are prone to fluctuations (from 75 to 150 in our model), due to changes in market participants' perceptions of the future business prospects and earnings potential of companies within the economy.
  

This situation is hardly one of steady equilibrium. On the contrary, our economy is a dynamic system, continually evolving from one point of instantaneous and imperfect equilibrium to the next. Population growth, innovation and technological change drive secular increases in the amount of cash, bonds and stocks, and government monetary and fiscal policy alters the money supply, bond issuance and tax revenues in a Keynesian attempt to influence the course of the economy. The result is an economy in perpetual disequilibrium, wherein apparently the only constant aspect is change itself.

Within a framework of disequilibrium, let's now examine the situation at the end of Stage 8 of the scenario presented above. Given the new infusion of cash (from a sudden increase in the money supply), the stock market (along with other assets such as real estate) is arguably likely to rise, consistent with the Sidelined Cash view, as investors chase higher returns by buying stocks with the new portion of their "sidelined cash" (now 75, up from the recent figure of 50 in our model). The idea here is that, when enough newly printed aggregate cash from fiscal stimulus makes its way into consumers' and investors' hands, some combination of more consumption and more investment will (eventually) push asset prices higher. Though ostensibly at variance with the Equilibrium view he espouses, Hussman points out that a probable outcome of current government policy is "a near-doubling of the U.S. price level over the next decade," citing Nobel economist Joseph Stiglitz's characterization of the government's strategy as "trying to recreate the bubble [in a way] [t]hat's not likely to provide a long-run solution . . . [but instead] says let's kick the can down the road a little bit."

To sum up:

• The Sidelined Cash view correctly points out that "cash on the sidelines" can drive stock prices higher; however, by failing to distinguish between aggregate cash in the economy and cash held by individual investors, this view leaves too much room for (mis)interpretation;
• The Equilibrium view is right in pointing out that the aggregate amount of cash in the economy does not change when investors trade stocks with each other; however, this view fails to incorporate the disequilibrating impact of new cash creation by the Fed (and the banking system).

I offer the following combined "sidelined cash in disequilibrium" view as a synthesis of the two views: The private sector of our economy operates, not in equilibrium, but in perpetual disequilibrium, due to the impact of our government's deficit spending using money printed by the Fed and accounted for as borrowing by the Treasury. New cash created by this dynamic process (which drives additional cash creation via fractional reserve banking) enters the economy through fiscal stimulus and becomes the "sidelined" component of aggregate cash that is forever chasing new opportunities and effectively encourages future economic growth.

So, we might say that cash is continually rolling off the printing presses at the Fed as our government's deficit expands and the economy grows. This capacity of our government to print money, constrained at any moment but secularly unlimited, provides a large pool of sidelined cash that can jump-start a recessionary economy and, in practice, has an inflationary impact on stock and other asset prices. The ultimate long-run outcome of our government's deficit spending policy and its influence on the relative strength of the U.S. economy versus that of other countries is debatable but, in my opinion, a correct prognosis will involve both a) interpreting "sidelined cash" to include the capacity of the Fed to print new money and b) recognizing that our economy is always in disequilibrium.

Hey, Baseball Fans: Winning Takes Money

Investing and professional sports have a lot in common--competition, winners and losers, uncertain outcomes, lots of data, and a wide range of opinions among participants, spectators and analysts. During a conversation the other day with a friend, I casually mentioned what I thought to be an accepted truism in the sport--that, just as money is a vitally important determinant in the business world, Major League Baseball teams with higher payroll (hence, better players by presumption) ought to win more often than teams with lower payroll.

To my surprise, my friend, who is a baseball fanatic, retorted that money and winning are not as intimately linked as one might presume, and proceeded to recite from his encyclopedic memory a number of examples of World Series play over the past 10 years--the Arizona Diamondbacks over the New York Yankees in 2001, the Los Angeles Angels over the San Francisco Giants in 2002, and the Florida Marlins over the Yankees in 2003--all cases in which teams with significantly lower payroll took the championship from their more generously compensated opponents. All right, I had to admit, I take "strike one" against my follow-the-money presumption.

After getting off the phone, I did a quick web search to check further. The first study I came across stated that "results from the two years of data [2002 and 2003] indicate that there is no real correlation between a team's salary and its win percentage." In other words, higher salaries do not significantly boost win percentage. Hmm--strike two, I mused. . . .

Wanting to avoid striking out, I resolved to find the data and run numbers myself.

Team Payroll and Win Percentage Data

The USA Today Salaries Database gives MLB payroll figures for all 30 pro baseball teams in both the American and National leagues going back to 1988. The ESPN MLB standings database shows seasonal win percentages from 2002. Combining the data for the seven years from 2002 to 2008, we can generate the scatter plot shown below.



A least-squares analysis of team payroll versus win percentage gives the "best fit" regression line:

Win Percentage = 0.426 + (Team Payroll in $ Millions) x 0.00097,

indicating that approximately each one million dollars of team payroll adds about 1 point out of 1,000 (i.e., 0.001) to the win percentage. The t-statistic for the regression is 6.96, which means that we can state this relationship between payroll and win percentage with an extremely high degree of confidence (in fact, the likelihood of a false positive is less than one in ten billion!).

It is also instructive to look at the data on a team-by-team basis for the same seven-year period from 2002 to 2008. Notice how the New York Yankees and the Boston Red Sox have not only the first and second highest average team payrolls ($181 million and $122 million) but also the first and second highest average win percentages (0.600 and 0.580), respectively. At the other extreme, the three teams with the lowest average win percentages--Kansas City Royals at 0.410, Tampa Bay Rays at 0.423, and Pittsburgh Pirates at 0.431--are among the five Major League teams with the lowest average team payroll (each less than $50 million).



I also provide a table showing the payroll of baseball teams playing in the World Series over the past 20 years (actually from 1988 through 2008, with the exception of 1994 when, as baseball fans will recall, the Series was cancelled due to a player strike), assisted by data from Baseball Almanac. The results reveal that in 14 out of the 20 years, or 70% of the time, the team with the higher team payroll defeated the team with the lower payroll in the World Series. This result is consistent with the strong relationship between team payroll and win percentage shown in the graphs above.



What I conclude is that money does matter in professional baseball. Teams that have higher payroll generally do win more games, both during the regular season and during the World Series. Suffice it to say: the correlation between performance and pay is surely at least as high in baseball (and, in all likelihood, in other profesional sports as well) as it is in the business world. On a related though distinct topic, I would conjecture that, based on the relationship between payroll and win percentages, it is undoubtedly much easier to predict outcomes in Major League Baseball than in the stock market and other financial markets.

A Note on Statistical Analysis

In case anyone is wondering why my conclusion differs so radically from the study I mentioned as being my "strike two," I provide an explanation here. Warning: Only those interested in statistical analysis should continue reading, since the discussion becomes somewhat technical. However, I encourage anyone who at least occasionally spends time looking for patterns in data to read on, since an important lesson in applying the right tools to the job at hand will arise from the detail.

The author of the study I cited chose to analyze that data using a multiple regression, in an effort to determine how each of three variables--starting pitchers' salaries (P), fielders' salaries (F) and closing pitcher's salary (C)--affects a baseball team's win percentage. For example, for 2003, the study produced the following regression result,

Win Percentage = 0.406 + 0.0022 x P + 0.0015 x F + 0.0018 x C,

along with corresponding t-statistics of 1.72, 1.46 and 0.41 for the significance of the regression coefficients corresponding to independent variables P, F and C, respectively. With all t-statistics less than 2.00, the study was unable to discern at the standard minimum of 95% confidence any dependence of win percentage on the three payroll variables.

Interestingly enough, when I perform the analysis using the same 2003 data, but formulating the problem as three separate one-variable single regressions (instead of one comprehensive three-variable multiple regression as employed in the study), I arrive at t-statistics of 2.93 for dependence of win percentage on starting pitchers' salaries, 2.77 for dependence on fielders' salaries, and 1.49 for dependence on closing pitcher's salary--all higher than the t-statistics for the multiple regression given above. Further, if I combine starting pitchers', fielders' and closing pitcher's salaries into a single variable (i.e., P+F+C) and again run a one-variable regression, I find an even higher t-statistic, namely, 3.49.

In other words, by "zooming out" and viewing the data using an effectively lower resolution microscope, we actually find a more robust statistical pattern--this is reminiscent of the proverbial necessity of stepping back from the individual trees in order to view the grander forest. But, you might be wondering, how can this be? How is it possible in a regression to see a pattern at a lower resolution that essentially disappears at a higher resolution?

To understand the mechanism behind this paradoxical statistical behavior, consider a very simple regression example. Suppose we are trying to understand the relationship between a dependent variable, z, and two independent variables, x and y, based on five data points:

Data point 1: x = 1, y = 1 and z = 1
Data point 2: x = 2, y = 2 and z = 2
Data point 3: x = 3, y = 3 and z = 3
Data point 4: x = 4, y = 5 and z = 4
Data point 5: x = 5, y = 4 and z = 4.

Graphically, three plots are relevant:

a) Multiple Regression: Three-dimensional plot of x and y versus z,
b) Single Regression: Two-dimensional plot of x versus z (same as y versus z), and
c) Single Regression: Two-dimensional plot of combined variable, x+y, versus z.



In the multiple regression, the t-statistics are 3.3 for each of x and y. Observe the "dispersion" of data points 4 and 5 in the three-dimensional plot, with each of these points offset in a different direction from the straight line that can be drawn through data points 1, 2 and 3. This dispersion adds extra error to the regression, creating a relatively poor regression fit to the data.

In the single regression of x versus z (or, symetrically, y versus z), four of the five data points are collinear, and only the fifth data point introduces error into the otherwise perfect linear fit. This tighter fit of the data to a straight line yields a t-statistic of 6.9, higher than in the multiple regression case.

Still better yet, if we regress on the combined variable, x+y, we end up with a t-statistic of 17.9, substantially higher than in either of the other cases. By combining x and y into a single variable, we eliminate the oppositely directed "dispersive meandering" of x and y. The combined variable allows the regression analysis to reveal a closer correspondence between the independent variable (x+y) and the dependent variable (z).

Back to Baseball . . . and a Lesson

In an analogous way, the baseball statistics study relying on multiple regression produces a poorer picture of the relationships between variables than does the single regression. Behind the scenes is probably a mechanism akin to the following: Owners and managers of a given baseball team work within budget constraints during any particular season, so that the total amount of money available to pay all players on the team may be viewed effectively as a fixed quantity for that year. If more money is spent paying starting pitchers, then less money is available to hire and pay fielders and closers. Similar to how in the simple example above, x is less than y at data point 4, but y is less than x at data point 5, a particular baseball team may decide to spend less of its budget on starting pitchers than fielders, while another team may decide to flip the allocation the other way around, with less of its budget going to fielders than starting pitchers.

When the salaries of the all pitchers and fielders are combined, a more meaningful variable results against which to regress the win percentages. For this reason, the single regression using the combined salaries produces a higher t-statistic and better fit to the linear regression model.

The basic lesson here is that, when analyzing problems, it helps always to look for simpler relationships, explanations and solutions first, before implementing more sophisticated analytical tools. In working with scientific, financial, economic, sports or any other type of data, we are often warned against fabricating false patterns (artifacts of the analysis) by overfitting data to a model. In a similar vein, our discussion shows how it is also sometimes possible to overlook robust patterns by forcing an overly complicated model onto an intrinsically simpler set of data.

Blind Men and the Elephant: On the Urgency of Asset Price Reflation

You've surely heard of the six blind men and the elephant. If we adapt the traditional story to our current financial and recessionary crisis, the key role-players become:

1. The Fed, who figures that the money supply and interest rates are what matter, and proceeds to lower short-term rates all the way to zero percent, while starting open-market purchases of commercial paper and mortgage securities to reel in credit spreads;
2. The Treasury, who decides that weak banks are the problem, and spends $350 billion of TARP funds recapitalizing banks and financial institutions, and deliberates over details of how to deploy the remaining $350 billion;
3. The FDIC, who feels that confidence in the financial system matters most, and boosts deposit insurance limits to $250,000 to help prevent runs on the banks;
4. Democrats in the House and Senate, who are sure that our problems will go away if the government spends more without worrying so much about the deficit, and quickly assemble a massive $900 billion stimulus package;
5. Republicans, who are certain that only tax cuts matter, and refuse to support the Democrats' proposal; and
   
6. President Obama, who believes that jobs and working together matter most, and pushes to get his stimulus package passed to jump-start creation of the 3 million jobs being forecast by his economic advisers, while reiterating his willingness to compromise for the sake of expediency.

That's six governmental players and six differing viewpoints, each of which may be construed as complementing the others, but together still falling short of definitively identifying the beast they are touching. In the traditional story, the six blind men do not realize that it is an elephant; and in the case of our economy, the elephant that everyone is touching but not seeing is an obvious truth that has gotten lost in the debate.

You see, the publicly spoken solution to our economic crisis--which seems like it ought to go away if only interest rates were lower, if the banks had more capital, if depositors and consumers had more confidence, if the government were to spend more to stimulate demand, if we had lower business and personal taxes, or if we could replace lost jobs--is really missing one essential ingredient. The elephant that everyone is touching but not quite comprehending (or at least not openly acknowledging) is the pressing need for a reflation of assets, home prices in particular.

In what now seems like quaint history, our economic woes began with a "minor" subprime mortgage problem in the middle of 2007. Through an unfortunate combination of regulatory leniency, misplaced incentives, financial irresponsibility and sheer Wall Street greed, a sizable number of underqualified, overleveraged borrowers began to have difficulty paying their mortgages and, as home prices fell, found themselves "upside-down" with negative equity, holding mortgages exceeding the value of their homes. Mortgage problems quickly spread to other highly leveraged borrowers as well, and over the ensuing year and a half have precipitated a downward spiral of plummeting real estate and stock prices, loan defaults and foreclosures, deteriorating bank balance sheets, abnormally tight credit markets, depressed consumer demand, a rising number of layoffs, etc.

Some wisdom may be gleaned by going further back in history to the last time our economy faced a crisis of this magnitude. As described by Irving Fisher in 1933, the basic problem we are experiencing is over-indebtedness, which leads to price deflation, which in turn makes matters only worse:

"[I]n great booms and depressions [the] two dominant factors [are] over-indebtedness to start and deflation following soon after. . . .

"Debt liquidation leads to distress selling and to . . . contraction of deposits and of their velocity . . . [which] causes . . . [a] fall in the level of prices, . . . [a] still greater fall in the net worths of businesses, precipitating bankruptcies and . . . [a] like fall in profits, which . . . leads . . . to . . . [a] reduction in output, in trade and in employment . . . to [p]essimism and loss of confidence, which in turn lead to . . . [h]oarding, . . . [all of which] cause . . . [c]omplicated disturbances in the rates of interest.

"[I]t is always economically possible to stop or prevent such a depression simply by reflating the price level [bold added] up to the average level at which outstanding debts were contracted by existing debtors and assumed by existing creditors, and then maintaining that level unchanged."

(Irving Fisher, "The Debt-Deflation Theory of Great Depressions," Econometrica, 1933, pp. 337-357)

Indeed, it is curious that, although we all recognize our over-indebtedness and are suffering through painful dislocations because of it, no policymaker is placing front-and-center the glaring need for asset price reflation.

In addition to the Fed's policy of keeping inflation moderate, which is a long-run strategy to stabilize the rate-of-change of prices, current crisis-oriented policy must target a short-run higher absolute price level, if we are to steer ourselves out of the mess we are in. Essentially, we need to re-create wealth by reflating asset prices, as quickly as possible, up to a high enough level to make our bad debt problem go away. When the relationship between home prices and indebtedness returns to a more manageable level comparable to where it was prior to the onset of our current crisis, we will find that those underwater mortgages are not so underwater anymore, that the banks are no longer on the verge of bankruptcy, that consumer confidence and retail sales are rising again, that companies are no longer laying off workers, and that our economy is finally on the road to recovery.

Two recent news items are relevant here:

• Senator Johnny Isakson has proposed a homebuyer tax credit, approved last night by voice vote in the Senate for amendment to the stimulus package being worked out. The measure "would offer new homebuyers a tax credit of up to $15,000 or 10 percent of the purchase price of a house that could be spread over two years." This tax credit would create increased demand among homebuyers and is fairly direct way of supporting home prices. In my opinion, the legislation should be amended to offer even more stimulus to the housing market and economy, by both a) raising the upper limit on the tax credit to $50,000, and b) allowing the amount of the credit to be carried forward indefinitely and applied to taxes owed until used in full by the taxpayer.
• UCLA economics professor, Roger Farmer, proposes that "just as it sets the fed funds rate to control inflation, the Fed should set a stock market index to control unemployment." Targeting the price level of a stock market index, like the S&P 500 or even a broader index, would give the Fed a more direct handle on influencing performance of our economy. With our wealth as a society linked to the stock market, consumer psychology (which determines demand) is impacted more by a 10% drop in stock prices than by a substantial change in short-term interest rates. The Fed should continue to use all of the existing tools at its disposal--rate cuts, open-market operations and so on--and with an added mechanism for targeting for stock prices, policy objectives would become clearer and more effective, particularly in market environments like the present with standard interest rate easing already pinned to its zero percent lower limit.

I like to think that the actions of policymakers matter more than their words, but, particularly today with our global economy in crisis, vocalizing a credible plan with concrete and realizable objectives can make a difference. If Obama, Geithner, Bernanke or another official in a position of authority would openly acknowledge a policy objective of asset price reflation--the need to raise the prices of homes, other real estate and stocks--then we would at least be looking the elephant directly in the eye. Thereafter, the task of getting our stubborn economic elephant to move in the right direction would become more straightforward.

Needed: A Large Drop of Helicopter Money

During the past half year, the concerns of the Fed have shifted from worry about commodity-driven inflation (recall $147 oil in July) to its polar opposite--fear about the onset of deflation (coinciding with oil falling below $40 today). With short-term interest rates now lower than the targeted 1% rate, traditional monetary policy measures have become less potent and the U.S. economy is more susceptible to descending into a "liquidity trap." As mentioned by Ben Bernanke in a 2002 speech, one way out of such a predicament is a "helicopter drop"--effectively dropping money from helicopters to consumers and businesses below in order to thwart deflation, stimulate spending and prevent economic stagnation.

Consumer-Based Crisis

The financial crisis we are facing today first surfaced a year and a half ago as a consumer-based subprime mortgage problem that soon developed into an institutional credit crisis, morphed into a pervasive illiquidity dilemma, and earlier this week was, long after the fact, officially named an economic recession that began 12 months ago! As parallels with the Great Depression of the 1930s and Japan's stagnant economy of the 1990s grow more conspicuous, the gloomy predictions of NYU economist Nouriel Roubini loom larger and closer. We are now one year into a recession that, according to Roubini, will most likely extend at least another year. What began as a seemingly minor problem has expanded into a full-blown, global financial crisis that could very well extend into 2010, becoming the most severe economic downturn in the adult lifetime of anyone alive today--unless, of course, our policymakers take appropriate and sufficiently drastic measures to stabilize the financial system.

Bush, Bernanke and Paulson have tried to fix the problem with a whole series of measures--a moderately sized consumer stimulus package in early 2008, bailouts of financial institutions, successive rate cuts, capital infusions to strengthen bank balance sheets, an increased limit on bank deposit insurance, government backstops on portfolio asset losses, purchases of illiquid assets, etc. So far, nothing has worked as well as anyone would like, and our faltering economy and plunging real estate and stock markets continue week after week to drive each other lower, in a relentless asset deflation spiral that is dragging down even the endowments of elite institutions like Harvard. Come January 20, President-elect Obama (incidentally, a Harvard Law alumnus) and newly appointed Treasury secretary Geithner will replace Bush and Paulson, respectively, and we can only hope that the stimulus package in Obama's vision for the future of our economy will be large enough to usher in real change in a favorable direction.

As for the root cause of our economic problems, the consensus opinion among economists and laymen alike implicates overleverage, basically too much debt and too little savings, particularly among consumers. Everyone agrees that saving more would be prudent for any individual consumer facing an uncertain future, but when aggregate consumption falls our economy unfortunately enters a vicious circle, as reduced consumer demand (from saving more) leads to reduced delivery of goods and services and higher unemployment, which, in turn, reduces demand still further. To halt this vicious circle before it does further collateral damage to our fragile economy, we need to find a practicable way to provide debt relief at the consumer level--as soon as possible. This is where the helicopter money comes in.

Helicopter Money Initiative

As Bernanke pointed out in his speech, even when monetary policy by itself becomes ineffective, there are a number of alternative ways to combine monetary policy with fiscal stimulus to prevent deflation and encourage economic growth, despite being in a near-zero interest rate environment like the one we are experiencing today. These less traditional, more innovative measures are:

A. Broad-based tax cuts,
B. Increased purchases of goods and services by the government,
C. Purchase of private assets via the Treasury, and
D. Increased direct transfer of money from the government to the private sector.

President-elect Obama is already planning to provide tax cuts (measure A above) to at least 95% of Americans and some talk of reducing payroll taxes is also circulating. The large (maybe $1 trillion?) stimulus package (measure B) currently under discussion in Congress will hopefully be ready for signing by inauguration day. Purchase of private assets (measure C) is already underway in the commercial paper and mortgage-backed security markets, but practical limitations (i.e., how to price highly illiquid instruments) have prevented the proposed wide-scale purchase of toxic mortgage assets that was the main objective the initial TARP plan. Consumer stimulus packages (measure D), along the lines of the one implemented in the first half of 2008, work most directly and immediately to maintain GDP growth and, for this reason, deserve further serious consideration.

Because near-term inflation is no longer an issue, policymakers now have the luxury of taking the most aggressive actions possible to turn our economy around. With the financially stressed, heavily indebted American consumer so central to our problems, it makes sense to implement an enhanced version of measure D--this time in much larger size. Just as people suffering in the aftermath of a natural disaster need immediate and basic emergency assistance, prior to tax-related benefits and government spending to rebuild infrastructure, our severely damaged economy needs a very significant injection of helicopter money delivered directly to the overleveraged consumer.

To achieve the quickest and most direct money transfer to the consumer, here's what our government should do:

Beginning during the first half of 2009, write checks to every household filing a tax return, in the amount of, say, $10,000 per dependent (taxpayer, spouse, children, other household members), which is an order of magnitude larger than the consumer stimulus in early 2008.

Offhand, it might appear that this type of seemingly frivolous fiscal policy would be a desperate and highly wasteful use of taxpayer money that could spark a new, undesirable bubble. However, given the precarious state of our economy, such a radical measure stands a greater chance of doing more good than harm and has many benefits:

1. Immediate and Direct Impact: Helicopter money provides an immediate stimulus to consumers and businesses, directly benefiting Main Street (a refreshing change after all the prior rescue plans with trillions of dollars going to Wall Street financial institutions);

2. Reduced Consumer Leverage: Consumers will use some of the money to pay down mortgages, credit card debt, car loans, etc.;

3. Increased Consumption: Consumers will use some of the money to do what consumers do best, i.e., buy products and services, which will immediately boost sales of businesses large and small, preventing further job destruction;

4. Market Support: Some of the money will be invested in the stock and real estate markets, relieving downward pressure on asset prices and helping to create the market bottom that is so badly needed to build consumer and investor confidence and turn our economy around;

5. Global Economic Growth: Reduced consumer leverage, increased consumption and increased investment will all boost the U.S. economy, which in turn will help revive the global economy.

With the U.S. population at about 300 million, this new consumer stimulus package of $10,000 per person would total $3 trillion, which is about four times the $700 billion TARP package but less than half of the approximately $8 trillion in cumulative funds the government has already committed through all of the various measures announced. The net effect of this helicopter money plan would be to shift up to $3 trillion of debt from the consumer to the government. This would reduce leverage at the consumer level and boost aggregate demand to stave off a deflationary spiral.

As Professor Roubini points out in this interview, the basic structural problem we face is a global supply glut cannot immediately be reduced even though demand has fallen. Therefore, at least in the short run, the severity of the current crisis justifies "pulling out all stops" to create the demand necessary to meet existing supply. A large helicopter drop appears to be exactly what is needed to stabilize our economy and sidestep the negative impact that further deterioration in employment and the housing and stock markets will otherwise bring.