Welcome to the Liquidity Surge

I've been trying to reconcile the apparent mixed signals in credit markets relative to stock markets in the past 2 months.

Inflation expectations implied by the 10-Year TIPS breakeven rate broke an intermediate-term downtrend on Monday, suggesting that investors are not overly concerned with deflation at the moment. However, a broken downtrend is not the same as an up-trend.

10-Year TIPS Breakeven Rate (Implied Inflation Expectations)

Source: Bloomberg

Meanwhile, rates have declined substantially all along the curve, signaling that bond market investors have no fear of inflation anywhere.2-year rates are breaking down around the world.

 Global 2-Year Government Bond Yields

Source: BMO CM Research

Longer-term rates broke their intermediate-term downtrend line in August, but have broken back above their short-term downtrend. A break of 3.265% on the US Ten-Year would signal a new intermediate-term downtrend. This might give equity investors pause, but in light of the relentless, mindless bullishness currently extant, lets not hold our breath.

Ten-Year Treasury Bond Yield

Source: Stockcharts.com

 Stocks, copper and gold have moved to new bull market highs, with oil close behind.

streetTRACKS Gold Trust ETF

Source: Stockcharts.com

The only explanation that seems to make sense is that this is the beginning of the next liquidity surge as the banks start to make use of those reserves at the Fed. They are moving out the curve (from zero duration) and driving risk capital out the risk spectrum. Even 88bps in the 2-year is better than 25 bps or less for funds on deposit at the Fed.

Source: FRB

 As the banks move into notes they will drive 2-year yields down. Investors will then move out the curve looking for yield, which will push longer maturity bond prices higher. This is the only explanation I can come up with for the coincident rally in bonds, stocks, copper and gold.

We’ll drive stock multiples back into the stratosphere, as the economy is clearly not supportive of the assumed risk premia.

Watch the TIPS BE rate (USGGBE10:IND in Bloomberg) for a signal of trend reversal. Until then, we are firing on all cylinders.

Welcome to the liquidity surge.

1930's Redux

David Rosenberg quoted from a September 1930 Wall Street Journal editorial in this morning's 'Breakfast with Dave'.  With Spiritus Animus bubbling to the surface today, wise investors would be well served to keep things in perspective. The following piece should put even the most bullish data and comments in context:

August 28, 1930: 

"There’s a large amount of money on the sidelines waiting for investment opportunities; this should be felt in market when “cheerful sentiment is more firmly entrenched.” Economists point out that banks and insurance companies “never before had so much money lying idle.” 

September 3, 1930:

"Market has now reached [the] resistance level where it ran out of steam on July 18 (240.57) and July 28 (240.81). Breaking through this level would be considered a highly bullish signal. General confidence that this will happen based on recent market action; many leading stocks have already surpassed July highs. Further positive technicals seen in recent volume pattern (higher on rallies and lower on pullbacks), and in continued large short interest.  

Some wariness based on recent good rally recovering all of drought-related break; some observers advise taking profits on at least part of long positions, to be in position to rebuy on good pullbacks. 

Most economists agree business upturn is close; peak in business was reached July 1929, so depression has lasted about 14 months. “Those who have faith and confidence in the country and its ability to come back will profit by their foresight. This has also been the case over the past half century.” 

Harvard Economic Society points to steady rise in bond prices as favorable for stocks. Says there is “every prospect that the [business] recovery ... will not long be delayed,” although fall period may not be strong as expected. Notes worldwide decline in business, but 1922 recovery demonstrates U.S. due to “great size, natural advantages, and diversity of conditions ... can lift itself out of depression without the stimulus of improved foreign demand.”

Rosenberg concludes with the ominous, "We only know now with perfect hindsight what these pundits did not know back then — that there was another 80% of downside left in the bear market."

Low Quality Rally

Many Advisors and fund managers have been complaining about how difficult it has been to beat their stock market benchmarks since the March 9th bottom. It turns out that, for active managers with a rigorous process for selecting the highest quality stocks, it has been quantifiably frustrating. This post will shed some light on this topic, to the delight of disciplined stock-pickers everywhere.

Over long periods (> 2 years) 'high-quality' stocks outperform 'low-quality' stocks by a substantial margin. A stock's 'quality' in this sense is defined by its relative standing among factors such as earnings growth and momentum, earnings stability, debt-to-equity, trading liquidity, return-on-equity, credit rating, analyst earnings estimate revisions, price level and price momentum, etc. However, since March 9th, an investor who stuck to a discipline of choosing only 'high-quality' stocks for portfolios would have substantially underperformed North American benchmarks.

It may seem intuitive that stocks that dropped the most during the bear market (worst momentum, smallest market cap at the bottom, lowest price at the bottom) have shown some of the greatest returns off the bottom. This intuition is faulty however, for several reasons. First, those who own the stocks that dropped the most - owned the stocks that dropped the most. Very few investors were able to time the purchase of these cataclysmic names, like Citigroup, Bank of America, and AIG so that they avoided the bloodbath before experiencing the ecstasy of rebirth. Even the bravest value investors like Bill Miller, whose Legg Mason Value Trust had one of the strongest 10-year track records of any mutual fund until late 2007, saw his fund value drop from $85 to $22, a drop of 74% (!!) before seeing his fund rebound by almost 100% since March 9th. His fund is still down over 50% from its peak.

Another reason why it makes little sense to try to buy the stocks that have dropped the most during bear markets is that these stocks usually underperform over the duration of the subsequent bull market. The 2000 - 2003 bear market is a great example. The stocks that went down the most in the bear market - JDS Uniphase, Nortel Networks, Mindspring, Cisco, etc. were very weak performers from 2003 - 2007. The strongest performers throughout the 2000 - 2003 bear market - energy, materials, and gold companies - were enormous winners during the following bull market. This is the rule, not the exception.

Myles Zyblock, Chief Institutional Strategist for RBC Capital Markets wrote the following in his September 1st note to clients:

"North American stock-specific leadership, regardless of sector membership, has been characterized by a type of constituency that most analysts refer to as “low quality”. This has been a rather unnerving shift for managers who follow a discipline that emphasizes particular attributes such as earnings quality or profitability. Many mandates have not allowed managers to enter this low-quality style box, to the detriment of relative performance. Strict adherence to a process more often than not leads to investment success, but the market can and often does move against a winning long-term strategy for brief time periods. Keep in mind that low quality cycles, even in up markets, tend to be relatively short-lived and our best guess is that there are only another 1-2 quarters of life left in this one.


One way to get a sense of what the low quality rally has been all about is to view the performance of stocks since the March low sorted by a few simple metrics that isolate the impact of quality factors including size/liquidity, valuations and profitability. Based on this methodology, it’s pretty clear that the smaller, less liquid, relatively inexpensive and more fundamentally broken companies have been the big outperformers over the past five months. " (See Table 1.)

Table 1. S&P 500 Returns Since March 9th By Decile Rank

Source: RBC

The next chart shows the performance of North American stocks, with S&P performance on the left, and TSX performance on the right. The grey bars represent the performance of highest quality stocks in each of the four major investment styles - Momentum, Predictability, Growth, and Value - while the blue bars show the performance of the lowest quality stocks. All performance is from the March 9th bottom.

Source: RBC

High quality U.S. stocks underperformed low-quality stocks in every category, though the outperformance in the Value category is minor. This makes sense, as at the bottom many of the low quality stocks were priced well below book value, on the assumption that many would be liquidated as non-viable businesses. Of course, without unprecedented government intervention, many of the worst performing stocks would have collapsed, and these numbers would look quite different. 

In Canada, high-quality outperformed low-quality Value stocks quite substantially. Canadian Value managers have had the most prospective stock-picking environment in generations, while growth and momentum managers have dramatically underperformed.

Overall, the above charts show that rapidly declining companies with highly unpredictable financials and significant earnings contraction as of March 9th very significantly outperformed stocks with predictable financials, strong earnings growth, and which were already in positive price trends.

History shows that this dynamic is not that unusual in frequency, but that it doesn't last for very long. According to RBS research, low-quality stocks have outperformed high-quality stocks during 8 periods in the past 30 years, and this performance advantage tends to persist for about 6 to 9 months. So low quality stocks may continue to dominate for another three months or so.

To further illustrate the point of low-quality dominance, I have included two tables below describing the performance of several style models from Canada's Computerized Portfolio Management Services (CPMS). The top table shows U.S. models, and the bottom table shows Canadian models. 

Each style model (Asset Value, Earnings Value, Earnings Momentum, etc.) tracks a portfolio of stocks chosen using different high-powered factors, such as earnings momentum, earnings predicability, analyst estimate revisions, price-to-book value, price momentum, etc. The 'Dangerous' model in each table tracks the performance of a portfolio of stocks which the system suggests would make good short candidates. These are the lowest quality stocks, with poor earning growth and quality, negative analyst estimate revisions, high debt levels relative to equity, etc. 

Note that over the past year the 'Dangerous' models have outperformed every model except the Canadian 'Earnings Value' model. This makes sense, as the Dangerous portfolio closely approximates a low-quality value portfolio, while the 'Earnings Value' model replicates a high-quality Value portfolio.

The Momentum portfolio in Canada, and the Earnings and Price Momentum portfolios in the U.S. have demonstrated the best performance since inception (1985 and 1993 for the Canadian and U.S. models respectively) by a wide margin (see far right column). However, these models have been terrible under-performers since the beginning of this year.

Source: CPMS

Source: CPMS

Fortunately, we can be confident that the low-quality rally won't last forever. If this rally provides us with another leg up, disciplined adherents to high-quality stock picking strategies will almost certainly get their day in the sun.

The Statistics of Prediction

Given the high level of ambiguity in the economy and markets at the moment (both gold and Treasuries rallying?), I thought it might be useful to revisit the concept of forecast error. Economic forecasters, even (perhaps especially?) the top, highest paid Wall Street celebrity economists, are egregiously poor predictors of stock market levels or direction over any meaningful time frame.

Robert Prechter does an excellent job of describing the logical fallacy about economists:

From Elliott Wave Theorist, May 2009

"Although it has suddenly become fashionable to bash economists, I would like to point out that economists are very valuable when they stick to economics. They can explain, for example, why and individual's pursuit of self interest is beneficial to others, why prices fall when technology improves, why competition breeds cooperation, why political action is harmful, and why fiat money is destructive. Such knowledge is crucial to the survival of economies. 

Economic theory pertains to economics, but not to finance and so-called macro-economics. Socionomic theory pertains to social mood and its consequences, which manifest in the fields of finance and macro-economics. 

If you want someone to explain why minimum wage laws hurt the poor, talk to an economist. But if you want someone to predict the path of the stock market, talk to a socionomist. 

The two fields are utterly different, yet economists don't know it. 

How Correct are Economists Who Forecast Macro-Economic Trends? 

The Economy is usually in expansion mode. It contracts occasionally, sometimes mildly, sometimes severely. Economists generally stay bullish on the macro-economy. In most environments, this is an excellent career tactic. The economy expands most of the time, so economists can claim they are right, say, 80 percent of the time, while missing every turn toward recession and depression. 

Now, suppose a market analyst actually has some ability to warn of downturns. He detects signs of a downturn ten times, catching all four recessions that actually occur but issuing false warnings six times. He, a statistician might say, is right only about 40 percent of the time, just half as much as most economists; therefore the economist is more valuable. But these statistics are only as good as the premises behind them. 

Suppose you eat at an outdoor cafe daily, but it happens that on average once every 100 days a terrorist will drive by and shoot all the customers. The economist has no tools to predict these occurrences, so he simply 'stays bullish' and tells you to continue lunching there. He's right 99 percent of the time. He is wrong 1% of the time. In that one instance, you are dead. 

But the market analyst has some useful tools. he can predict probabilistically when the terrorist will attack, but his tools involve substantial error, to the point that he will have to choose on average 11 days out of 100 on which you must be absent from the cafe in order to avoid the day on which the attack will occur. This analyst is therefore wrong 10% of the time, which is ten times the error rate of the economist. But you don't die. 

How can the economist be mostly right yet worthless and the analyst be mostly wrong yet invaluable? The statistics are clear - aren't they? 

The true statistics, the ones that matter, are utterly different from those quoted above. When one defines the task as keeping the customer alive, the economist is 0% successful, and the analyst is 100% successful.  

When consequences really matter, difference in statistical inference can be a life and death issue. In the real world, business people need timely warnings, and realize that economists miss most downturns entirely. Would you rather suffer several false alarms, or would you rather get caught in expansion mode at the wrong time and go bankrupt?  

Focus on irrelevant statistics is one reason why economists have been improperly revered, and some analysts have been unfairly pilloried, during long-term bull markets. But economists' latest miss was so harmful to their clients that their reputation for forecasting isn't surviving it."

The following table offers a stark example of forecaster fallibility. Every December, Barron's financial journal gathers the top analysts from Wall Street, names most investors are familiar with, and asks them to forecast the value of the S&P500 on December 31st of the following year. Granted, this is an impossible task; a probable range might be more reasonable. But more importantly, it is also useless because markets can travel an infinite variety of paths to get from A to B, and the paths are important to anyone with an active view on the markets. Regardless, these analysts were off by such a large factor that it can legitimately be claimed that they offer no predictive value, whatsoever.

Source: Bloomberg, Butler|Philbrick & Associates

Note that the average estimate of 1650 from these 12 Chief Economists was 82% above the actual closing value on December 31st.

A recent study by James Montier of Societe Generale suggests that stock strategists at Wall Street’s biggest banks -- including Citigroup Inc., MorganStanley and Goldman Sachs Group Inc. -- have failed to predict returns for the Standard & Poor’s 500 Index every year this decade except 2005. Their forecasts were w rong by an average of 18 percentage points, according to data compiled by Bloomberg.

There is a mountain of evidence supporting the view that economist forecasts are statistically no more accurate than random guesses around a long-term trend. Yet most, if not all, Advisors eagerly follow the views of their favorite economist closely, and generally adhere to their recommendations. What is the definition of 'deranged'? Repeating the same mistake over and over while expecting a different result.