investment: 2009

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.")

Perpetual Income Generation

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.

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

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.

The Impact of Sidelined Cash in Disequilibrium on the Stock Market

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.

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).

Commodities are back incase you haven't noticed already

Oil, gas, gold. Everything that has actual value as opposed to currencies.

The devaluing of the US dollar and massive injections of credit of the Obama administration to curb the downturn means the commodities trade is back on with a vengence.

Further, China is stockpiling oil and coal and other raw materials at current depressed prices.

With these two tail winds, I am long on oil and natural gas. I am playing oil with AET.un and USO. Gas, I am playing with UNG and KWK.

Two stocks on China

The two stocks I want to focus on today is FXI and OCNF

FXI, a play on H-shares Chinese stocks listed in Hong Kong. The Hang Seng index has broken out past 16000 two days ago in a beautiful cup and handle chart formation. The 20dma is above the 50dma. All this on the back of strong economic data coming out of China. I am adding to my FXI holdings on pullbacks.

OCNF is a dry shipping company with a fleet of ships. This is a play on the China recovery story. Yesterday saw heavy volume over 20M shares traded on average volume under 2M. This is a $1.85 stock at the moment and extremely risky.

Messrs. Buffett and Munger on Math and Theories

Excerpt from the Wallstreet Journal:

Messrs. Buffett and Munger made clear their complete disdain for the use of higher-order mathematics in finance.

"There is so much that's false and nutty in modern investing practice and modern investment banking, that if you just reduced the nonsense, that's a goal you should reasonably hope for," Mr. Buffett said. Regarding complex calculations used to value purchases, he said: "If you need to use a computer or a calculator to make the calculation, you shouldn't buy it."

Said Mr. Munger: "Some of the worst business decisions I've ever seen are those with future projections and discounts back. It seems like the higher mathematics with more false precision should help you, but it doesn't. They teach that in business schools because, well, they've got to do something."

Mr. Buffett said: "If you stand up in front of a business class and say a bird in the hand is worth two in the bush, you won't get tenure....Higher mathematics my be dangerous and lead you down pathways that are better left untrod."

Trading is like Farming

An analogy I just thought about is farming. Being a trader and investor is very much like a farmer.

We only have so many seeds to sow (capital). We need to constantly decide where to sow our seeds.

Trader - Invest in short term or long term securities (short swing trade or longterm investment)

Farmer - Plant crops that grow quickly or slowly

Trader - Buy and sell at what price based on information and speculation

Farmer - Buy and sell seeds at what price, will the seed prices rise or fall? Sell your crops now because you think prices will fall, or sell later because you think prices will rise?

Trader - Take a percentage of annual gains away from trading account into savings account. For spending and for a rainy day

Farmer - Take a percentage of crops and keep it stored. Wheat, rice can be eaten should you expect a draught to feed the family.

Trader - Mr Market forces are strong. Many things you cannot control and can get wrong. The markets can be brutal and trades can always go against you

Farmer - Always at the mercy of Mother nature. The climate, floods, droughts, pests. All can destroy your hard work and leave you devastated.

Adding to shorts

I have added a number of short yesterday. I am now net short. My biggest short positions is skf (long the bear financial) and tna (short the bull 3x etf). TNA is my favorite because it has been in a one month upward channel where it has been bouncing off a beautiful ascending channel. Further, it also hit a resistance of about $28 set 2.5months ago. The bottom of this channel is at $23.5.

Two Hedge fund managers I have the greatest respect for Doug Kass and Eric Bolling have also been selling into this strength in the markets and adding to shorts. This in addition to what I see in chart formations of what looks to be a temporary top on the markets (SPX 890) gives me additional confidence with my decision to go short.

The next leg down to 860 on the SPX is the near term target. Ideally, I would like to see the SPX start to form a downtrend. I don't expect the fall to be quick but also don't expect 760 to be breached.

For currencies, the EURUSD would be a great short should it fall below 1.3212 the 20dma line.

Getting a little short

I haven't been making major trades and also have been staying low in trading.

The markets have been meandering back and forth. A terrible environment to trade except for scalping small hourly gains. Without any real trending in the broad markets, this environment has been very unfriendly for gains.

I am however getting a little short putting on small positions in skf and sds. The SPX rallied past resistance at 876 today after the FED announcement but the rally quickly faded. The risk/reward is now pointing slightly more to the down side.

I would caution however that the markets are churning back and forth. Put tight stops on positions and don't be worried about small losses if they are triggered.

Big money is made on the big moves and they will more than cover the small losses.

Stress test results are coming up on May 4. And I expect a sell off on the banks before the news from fear that some of them will required more funding.

Backing and filling

I am not trading this market.

I am holding my core positions in oil and ag. aet.un and VT.

I also hold a trading position in gold. In kgc and au. Gold has taken a bit of a beating the last 3 days but I believe it is oversold and any meaningful pullback in the markets will see a big rebound in gold.

Otherwise trading in this market has been difficult. I have been trying to play the short side with SKF but the market has refused to go down so far. Last hour of trading has also seen much program trading pull the markets up. I've been taking small losses on SKF daily as I don't want to hold it overnight, but I am ready to pull the trigger and long SKF whenever there is indication that the market is ready for a fall.

Bulls power over the bears

The markets gapped up in the morning and continued moving up until the afternoon until what looked like there might be a sell off. The markets tried to push through 845 on the S&P and when failed seesawed in to the close. A mild sell off in to the close about 15 minutes before close.

A rather tough day for me. I held small positions on two ultra shorts overnight and they both gapped down after the announcement that Mark to market accounting was going to be eased. SKF and SRS. I managed to half my losses in SKF by doubling down on dips. With SRS however I was not as lucky as it kept falling losing 9% when I had to cut my losses. SKF had resistance as financial firms tried to sell off.

On a day when financials are the reasons the market is up. The financials themselves sold off which everything else powered up.

On a brighter note. I sold my GOLD in KGC and AU just before market close the day before. I noticed weak volume in the GDX as it reached the top of the recent trading channel. This morning, GDX sold off hard to the bottom on that very channel where I picked up my shares in KGC and AU again.

After market, RIMM announced earnings and it was better than expected. The shares powered to $60 after market. I think this is way over done and suspect RIMM may have 'stuffed the channel' with products. They have also been aggressively pushing products such as the CURVE for free with contract. I am going to start a short on RIMM when markets re open.

S&P holds 780

The S&P held 780 an hour before market closed. But the bounce off that level was weak. There has been some heavy put buying on WFC (Wells Fargo) and the weakness in financials prevented the S&P from making a stronger showing.

If 780 doesn't hold tomorrow, look for 750 to be the next strong support.

My holdings are minimal at the moment.

Core holdings of AET.un, VT, KGC and AU.

Trading position in spwrb and UWM.

Sold SKF today for 14pt gain from Friday.

I want to see the S&P test and hold 780 again tomorrow before building my positions again.

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.

Hey, Baseball Fans: Winning Takes Money

A real fight today beneath the surface

The market may have looked calm or even too quiet today if you only looked at the one day chart of the S&P. But there was a real battle going on beneath the calm surface between the bulls and the bears.

All day, the S&P fought to break the strong resistance at 827. It broke it finally around midday only to fall back to 820. Financials started to fall and it looked from aspects that the S&P might retest 790 (which is the number I was hoping to see).

However, 820 has become staunch resistance and in the last hour of trading, the markets gained steam and finished the day firmly above 827 at 832. This is a fantastic showing for the bulls. The S&P is good for another 50-60pts to about 880 is my expectation at this point.

Solar stocks rocked up today with my single digit solar stocks gaining upwards of 40%. There was a report out on Bloomberg about China providing subsidies to people who wish to install solar systems. As I have written in the past, I have been holding SPWRB. I sold off some near the one day peak at $26.44 and a bit more as people took profits. I have now added back my position seeing how well the S&P has ended. I am anticipating a multiday rally should this rumor turn out to be true. I may however bail should this rumor turn out to be ...well, only a rumor.

I am holding tight to my gold (KGC and AU) at this point. My holding of FXI is also showing nice gains. These are core holdings.

I have no holdings outside the core holdings. I want to have better entry points before loading up on the financials again. They have been great winners for me this year and I must refrain from getting overly greedy. Never a good thing.

Current trade

The markets powered higher on Monday followed by a light sell off yesterday.

I sold 2/3 of my SKF on Friday for about a 15% gain. The remaining 1/3 got stopped out on Monday in the 500pt DOW runup. I also covered a short on Baidu after it showed unwillingness to go down. This was a great exit as Baidu rocked to over $195.

I also sold a number of longs into the strength including UVM Ultra Long Russell 2000 ETF. It went up over 10% in a day and when making money becomes seemingly too easy and quick in the markets, its a sign that you need to slow down.

My plan is to ease back into the markets on pullbacks such as the one yesterday.

I am still about 40% long. Long in gold, oil, agriculture and China.

I am trading the FXI in and out. Holding a core position but buying on weakness and selling on strength.

I have no holdings in financials at the moment, but looking to get back into Wells Fargo WFC and Financial ETFs. Morgan Stanley showed great strength yesterday.

I caution not to chase this rally though. Earnings season is coming up around the corner starting about 2 weeks away. This period is usually very volatile and stocks that have fun up prior is likely to sell off.

I am sitting on 20% gains this year. So I am going to sit tight and and be more selective in my entry points for equities at this point.

The reinstatement of the Uptick rule may be around the corner. If it passes through, we could see the markets melt up 20%+.

Signs of financial exhaustion

Financials have begun to sell off timidly today. A healthy sign after the massive runnup over the last 7 trading days.

Taking profits on my financial longs was a great decision in hindsight. Although I missed 5 points on my POT as it gapped up today! (can't win them all)

I am now shorting the financials by being long the SKF. Looking for 30% profit target on this that should happen within the next 2-3 trading days. Plan to get back in Long with WFC and IYF near support levels.

Also long gold with Kinross gold. Canadian company KPC. Another 7%+ gain today. It has ramped so fast I am feeling a bit shaky on this wanting to take profits. I'll see how it goes tomorrow but the FED's decision to massively print money has ignited a bull run on GOLD like I've never seen before. I'll probably sit tight on my holdings and look to continue to add positions on weakness. Added some AU today on weakness to my gold holdings.

Solar also up nicely today with my holdings of SPWRB, up almost 10% today. This one is very volatile so buyer beware.

Markets melted up after FED announcement today

Big up day today after comments from the FED.

This was take action day and as the S&P hit 800, I took profits on over 2/3 of my longs.

I took profits off the financials which have seen massive gains the last few days. I think short term, they have run their course. Pigs get slaughtered in the markets and I have sold all my IYF and Wells Fargo for over 25% gains in less than a week. Even after the melt up, C and MS did not ramp and could not break the highs. This was a sign for me to sell the financials for now and get back in later.

Gold is up big and I continue to hold gold with my KGC (Kinross gold) holdings up over 10% in one day. The FED's announcement to buy treasuries is going to push gold to new highs. Watch Gold carefully and buy on dips.

Some technology shares also did not follow the rally. GOOG, RIMM, BIDU were mostly flat for the day. This was also a red flag for me to take profits.

I am still long on KFC, SPWRB, FXI, VT

SKF is also nearing $100 from a high of $267 just 5 days ago. Wish I held my short on this until now, sold out too fast. But financials have come up too fast too soon and I am looking at going long SKF below $103 (to short the financials at 2X leverage)

Exhaused from the rapid action and trading today, going to get some much needed rest....

DOW loses 200pts in afternoon trading

The DOW sold off 200pts in afternoon trading yesterday. This sell-off is healthy and is necessary for any sustained rally.

I have added some long positions this morning on the dip.

Most hedge funds are still very poorly positioned for this rally. And if the bears are unable to push the markets down any more in a significant way (additional 200pt+ down days for the DOW). Look for more short covering and rapid change of sentiment from the investment community.

Asian markets also closed strong today. Japan was up nicely and my 7&i holdings made some nice gains.

Hong Kong also did very well with no major sell-off. Basically a flat day to take a breather after the recent run up.

Possible resistance S&P 793

I'm watching the S&P at 793 to hit some resistance at its 50 day moving average.

Markets are having much resiliance so far but the bears won't let go this easy. Cramer had a piece out this weekend that most Hedge funds are very underinvested at this time and would certainly gun for a correction to load up on equities.

I am still firm on expecting a 200pt drop in the DOW very soon.

So I'm watching the 793 level on the S&P to take profits.

In the meantime, financials are strong but many have hit some hard resistance such as WFC at $15.

Friday close

We are ending Friday slightly in the green.

A positive sign for the days ahead.

But I can't help but feel this might be a bull trap. If you look at the charts today, we were very range bound and traded almost perfectly to trend lines. No real big buyers in the market today, just traders yanking the markets back and forth.

Careful of a big pull back next week. Don't chase stocks. But the next big sell off will be the time to back up the truck and go long.

Have a great weekend.

investment

Perpetual Income Generation

Perpetual Income Generation

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

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

The Impact of Sidelined Cash in Disequilibrium on the Stock Market

The Impact of Sidelined Cash in Disequilibrium on the Stock Market

Commodities are back incase you haven't noticed already

Two stocks on China

Messrs. Buffett and Munger on Math and Theories

Trading is like Farming

Adding to shorts

Getting a little short

Backing and filling

Bulls power over the bears

S&P holds 780

Hey, Baseball Fans: Winning Takes Money

Hey, Baseball Fans: Winning Takes Money

A real fight today beneath the surface

Current trade

Signs of financial exhaustion

Markets melted up after FED announcement today

DOW loses 200pts in afternoon trading

Possible resistance S&P 793

Friday close

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