Archive for Most Recent Stories

Chart of the Day: Is the Expansion “Long in the Tooth”?

This was a useful chart from the WSJ over the weekend.  It puts the current economic expansion in perspective:



We’re in month 58 of the current expansion, which is right in-line with the post-war average.  I’ve said that the current expansion is a little long in the tooth, but that it’s important to keep that in the right expansion.  While we’re probably closer to the next recession than we are to the beginning of the recovery, it’s also important to remember that the business cycle seems to be getting longer and longer.  As I noted earlier this year:

“it’s also interesting to note that the expansion phase of the business cycle appears to be getting longer.  You’ll notice that 3 of those 6 long recoveries occurred since 1982.  Are these anomalies or are they signs of a changing economic landscape?  I think they’re probably signs of a changing economic landscape and that means that a lot of the data that exists before the post-war era probably doesn’t apply.”

So yes, we’re long in the tooth.  But that doesn’t mean we can’t get longer in the tooth.

Has US household Deleveraging Ended?

By Bruno Albuquerque, Ursel Baumann, & Georgi Krustev (via VOX)

Household deleveraging in the US has impeded consumption and market activity in recent years, holding back the recovery. Despite substantial progress in balance sheet repair, a key question is whether deleveraging has ended or whether further adjustment is needed. This column presents time-varying equilibrium estimates of the household debt-to-income ratio determined by economic fundamentals. Taking into account the latest available data, the estimates suggest that the household deleveraging process may have ended at the end of 2013.

The balance sheet adjustment in the household sector has been a prominent feature of the last US recession and subsequent recovery. The beginning of the economic downturn in late 2007 broadly coincided with a sustained reduction in household liabilities relative to income – that is, household deleveraging – which contrasted with the strong build-up of debt before the crisis. From a peak of around 129% in the fourth quarter of 2007, the household debt-to-income ratio fell by 26 percentage points to around 104% in the fourth quarter of 2013, led by sustained declines in mortgage debt. While there is broad-based agreement that household deleveraging has acted as an important drag on the recovery, the lack of an obvious benchmark to which the debt ratio should converge makes the assessment of progress on balance sheet repair quite challenging. History appears to be of little guidance regarding the adjustment needs in the current cycle, as the recent swings in the household debt-to-income ratio are unusual by the standards of previous recessions (Figure 1).

Figure 1. Developments of the household debt-to-income ratio over current and past business cycles


Source: Federal Reserve Board and authors’ calculations.

Notes: Zero marks the start of each recession. According to the NBER, there have been 10 recessions in the United States since 1950, with the last one starting in 2007Q4.

New methodology to model household equilibrium debt

In a new paper we propose a novel approach to examine the question of how far US household indebtedness stands from its sustainable level at any point in time, by estimating a time-varying equilibrium household debt-to-income ratio determined by economic fundamentals (Albuquerque, Baumann, and Krustev 2014). This approach allows us to assess whether household indebtedness moved beyond what was suggested by its fundamentals during the recent credit boom, as well as to track progress in household deleveraging in the current phase of balance sheet adjustment.

We model the US household debt-to-income ratio in a panel error correction framework. We employ the Pooled Mean Group (PMG) estimator developed by Pesaran, Shin and Smith (1999) – adjusted for cross-section dependence – for a panel comprising the 50 US states (plus the District of Columbia) over the period 1999Q1 to 2012Q4. The data come from the Federal Reserve Bank of New York’s (FRBNY) Consumer Credit Panel, a nationally representative sample drawn from anonymised Equifax credit data. In line with the related literature, the long-run dynamics of the household debt-to-income ratio are modelled as a function of:

  • wealth (proxied by the house price-to-income ratio),
  • the cost and availability of credit (proxied by the nominal interest rate on conventional mortgages and the loan-to-value ratio),
  • the collateral available for borrowing (proxied by the homeownership rate),
  • income expectations and uncertainty (proxied by the unemployment rate), and
  • the demographic structure of the population (where we use the share of 35–54 age group in total population).

The model estimates point to a stable long-run relationship between the debt-to-income ratio and the explanatory variables. The difference between the actual and estimated equilibrium debt-to-income ratio (determined by the long-run relationship) is interpreted as deviations from ‘sustainable/equilibrium’ levels, the so-called debt gap.


Our results show that the evolution of the debt gap went through a number of stages (Figure 2). The debt-to-income ratio in the US household sector was broadly in line with what was suggested by equilibrium debt up to around 2002–2003. Since then, a positive debt gap started to emerge as actual debt rose at a faster pace than equilibrium debt. After mid-2007, the widening of the debt gap was reinforced by a decline in equilibrium debt reflecting deteriorating fundamentals, such as lower house prices, higher uncertainty, more pessimistic income expectations, and reduced collateral availability. These factors were partially offset by lower mortgage rates. The debt gap reached its peak in late 2008, broadly coinciding with the peak in the actual debt-to-income ratio. Thereafter, the gap began to shrink due to stronger deleveraging undertaken by households that outweighed the decline in the equilibrium debt ratio.

More recently, in the course of 2012 and 2013 the gap has shrunk not only due to on-going household deleveraging, but also reflecting a gradual stabilisation and subsequent rise in the equilibrium debt-to-income ratio. The latter is due to improving fundamentals – particularly rising house prices – and a declining unemployment rate. By the end of 2013, the gap between actual and equilibrium debt stood at less than three percentage points, suggesting that the deleveraging process may have ended or is about to end (given the uncertainty around the estimate of equilibrium debt).

Figure 2. Actual and equilibrium debt-to-income ratio and implied gap


Source: FRBNY/Equifax Consumer Credit Panel and authors’ calculations.

Note: Last observation refers to 2013Q4.

The aggregate results mask some heterogeneity across US states. At the time when the national debt gap was at its peak (2008Q4), all US states had a debt gap above zero, although with different deleveraging needs (Figure 3). The synchronised balance sheet adjustment across states carried out since then implied that, by the end of 2012, the number of states with severe household debt imbalances diminished markedly, in particular in those states with pronounced boom-bust cycles in their housing markets (Arizona, California, Nevada, and Florida), while several other states appeared to no longer face deleveraging pressures (shown in light blue). Heterogeneity across states, however, continued to be present.

Figure 3. Debt gaps across US states


Source: Authors’ calculations.

Note: The debt gap measures the difference between the actual debt-to-income ratio and the estimated equilibrium ratio for each state. A positive debt gap indicates a need for balance sheet adjustment due to the actual ratio being above the estimated equilibrium ratio. The states of Alaska and Hawaii are not shown for convenience.

Concluding remarks

The build-up in indebtedness in the US household sector since early-2000 – and the subsequent balance sheet adjustment that began later in the decade – are unprecedented by the standards of previous business cycles. After roughly 5 years of balance-sheet adjustment, the process of deleveraging in the US household sector appears to be broadly completed as of the end of 2013. Although the household debt ratio has started to increase again in the last two quarters of 2013, as evidenced in the FRBNY’s Household Debt and Credit Report, this will not necessarily lead to a widening in the debt gap. In fact, provided that the increase in the debt ratio continues to be accompanied by a rise in equilibrium debt, supported by the on-going US economic recovery, the debt gap could remain largely unchanged. On the other hand, a normalisation of monetary policy and a return to a higher interest rate environment might pose some challenges to the deleveraging process in the future by pushing down the sustainable debt-to-income ratio.

Disclaimer: The views expressed in this column should not be reported as representing the views of the European Central Bank (ECB) or of the Eurosystem. The views expressed are those of the authors and do not necessarily reflect those of the ECB or of the Eurosystem. 

*  The authors are employees of the External Developments Division, Euopean Central Bank

Is There a UK Housing Bubble?

By Sober Look

Home prices in the UK continue to rise to new highs, exceeding the pre-recession peak. The price increases started in London and have now spread nationally. Many families are quickly being priced out of the housing market. Some are calling it a bubble.

The Guardian: – UK house prices continued to accelerate in February, rising by 1.9% during the month and pushing the annual rate of inflation to more than 9%, according to the latest data from the Office for National Statistics.

Commentators warned of a “superbubble” and said the market was “out of control” as the official figures reported year-on-year prices rises of 17.7% in London and said first-time buyers had experienced double-digit price growth.

Just to put this in perspective, US home prices are now roughly at the levels they were a decade ago. UK home prices have risen over 40% over the same period.

UK vs US home prices


Many are blaming the Bank of England’s so-called FLS (the Funding for Lending Scheme - see overview) for flooding the market with cheap mortgages. Indeed the program has resulted in lower bank financing costs and lower mortgage rates.

FLS Chart 1 - Q2


But is all this cheap credit creating a speculative housing bubble in the UK or is there another factor at play? If you speak with British realtors, they tend to have one major complaint in common. The UK is facing a housing shortage as the post-recession home construction activity remains subdued.

England housing starts


Homes are being built at about half the rate needed to meet the pace of British households creation. But that is also partially the case in the US – so why such a divergence in house price trajectories between the two nations? The answer, according to Goldman, is that unlike the US and some other nations that went on a building spree during the bubble years, the UK was facing a housing shortage even before the financial crisis. The UK housing “bust” happened without the “boom”.

GS: – And, while the shortfall in house building has become more acute in the years since the financial crisis, the rate of house building was also inadequate before the crisis. Unlike countries such as the US, Ireland and Spain – where house building rose sharply in the years leading up to the crisis – the UK has experienced a post-crisis bust in housing supply, without having experienced a pre-crisis boom.

But with housing prices rising faster than wages, doesn’t it mean that this rally should be ending soon? Not necessarily. The acute housing shortage has put a similar upward pressure on rents as well, limiting housing options.

Purchase price vs rents as percentage of avg earnings

And while fewer people can purchase a home after the recession, those who can end up paying materially less on their mortgage than they would be paying in rent (thanks to FLS). They are jumping into the housing market and driving up prices.

Of course if the Bank of England pulls the plug on stimulus by raising rates or by imposing a more stringent lending requirement on banks, home price increases are likely to slow. The housing shortage however will still remain, resulting in higher demand for rentals. Whether paying more for home purchases or dealing with higher rents, one thing is clear: UK residents will be paying increasingly more for shelter in the years to come.

Did Market Monetarists Accurately Predict Low Inflation?

David Beckworth stated on Twitter that Market Monetarists “knew all along inflation would not be a problem”.  It’s true.  The Market Monetarists have long been predicting low inflation and even deflation.   See this 2009 piece by Scott Sumner titled “Deflation is our Biggest Worry – Not Inflation”.  So yes, the Market Monetarists nailed this one, right?  Not so fast.

If you read the actual 2009 article you see the reasoning behind the thinking:

“Banks kept the Fed’s cash
Other economists point to the Fed’s large injections of cash into the banking system as an inflationary “time bomb.” But last October the Fed began a policy of paying interest on those extra bank reserves in order to keep interest rates from immediately falling to zero. Unfortunately, this caused banks to hoard the money, which is why prices have fallen over the past 12 months despite the Fed’s large injections of cash.”

Sumner followed that up a few weeks later with an even clearer explanation:

“Ohanian points out that the Fed has done a lot already, having increased bank reserves from $40 billion to $900 billion. But this liquidity injection was not what it seems — indeed, if it was, we’d now have hyperinflation. In reality, the Fed completely neutralized the injection by starting a new policy of paying interest on reserves, causing banks to simply hoard these “excess reserves,” instead of lending them out. The money never made it out into the economy, so it did not stimulate demand.”

This is obviously a misinterpretation of the money multiplier and it’s based on an incorrect causal understanding of bank reserves and the lending process.   More recently, there’s been some revisionist history on this concept.  Obviously, the 2009 Scott Sumner believed in the Money Multiplier and the myth that banks “lend out” reserves.  But since the Bank of England demolished that myth the story changed.  2014 Scott Sumner says the Money Multiplier is still valid, but simply represents a ratio instead of a causal relationship in the lending process.

So I don’t think the victory flag can be so triumphantly waved here.  I don’t doubt David’s claim that the Market Monetarists thought the Fed was too tight and that they weren’t doing enough to generate high inflation.  In fact, I think David is undoubtedly correct there.  But it’s also crystal clear that some other components of the reasoning for low inflation were based on a total misunderstanding of how modern banking works.  And so the conclusions were right, but not entirely for the right reasons.   And this again, proves why understanding the modern monetary system is so important.  


Some Weekend Reading

Looking to catch up on some reading over the weekend?  Here’s some nerdy stuff I’ve been catching up on:

And a happy Easter chart courtesy of deflation in egg prices (via Mark Perry):


“Smart Beta” & Smart Beta Hypocrisy

Smart beta is the new buzzword on Wall Street.  No one really knows what it is because the term doesn’t have a specific definition, but the easiest way to understand what “smart beta” funds do is that they’re basically tweaking index funds to try to generate some extra return.  For instance, instead of using a market cap weighting you might use an equal weight.  Then these fund managers perform all sorts of backtests, crank out something with a heavy dose of confirmation bias and sell an ETF that’s basically an index fund marketed as something that’s superior than a broad index.

I think Burton Malkiel really nails it here on the WealthFront website when he says:

“Smart Beta” strategies rely on a type of active management. They are high cost and tax inefficient relative to traditional index funds and none have reliably and consistently beaten the market. As recent research and commentary from Vanguard Group puts it “Smart Beta” strategies are often, “active bets and not substitutes for traditional index funds.”

“Smart Beta” portfolios are more a testament to smart marketing rather than smart investing.

That’s basically right.  ”Smart beta” is basically marketed as a more efficient form of indexing.  But what’s surprising about Malkiel’s rejection of this is that his new firm, WealthFront, actually does something that’s very similar.  For instance, if you run through the WealthFront portfolio design process for a young, middle income investor with a high risk tolerance you come up with a portfolio that looks like this:

US Stocks: 35%

Foreign Stocks: 24%

Emerging Markets: 18%

Dividend Stocks: 9%

Natural Resources: 5%

Municipal Bonds: 9%

Another way of saying this is:

Stocks: 86%

Commodities: 5%

Bonds: 9%

So what Malkiel is endorsing is actually very similar to what he’s criticizing.  His firm claims that they can pick better or more efficient funds than broad indices.  And then they sell this idea as something “optimal” and back it up with all sorts of vague research that confirms some preconceived bias.  After all, if Malkiel were a true indexer and merely picked the Vanguard Balanced Index or chose three broad funds  like the Vangaurd Total Stock Index, the Vanguard Total Bond Market and the iPath Dow Jones-UBS Commodity Index then my guess is that most of their clients would ask them why the heck they need WealthFront when they can simply open up a discount brokerage account and buy ONE or THREE simple funds?   Of course, that’s where Malkiel will tell you that his firm has chosen “optimal” allocations and enhanced returns through other “active” portfolio management techniques (like tax loss harvesting or “tax aware allocation”).

And this is the problem with trying to define “active” versus “passive” approaches.  The reality is that Malkiel is actually endorsing a strategy that is more active than owning a simple Vanguard Balanced Index or the broadly diversified three fund alternative.  And they’re selling it as something different so they can differentiate their business model and justify charging higher fees than the broad aggregates do.  The reality is that we’re all active to some degree and that the closest thing to a truly passive portfolio is a portfolio that simply buys aggregates rather than pretending to know which funds will generate “optimal” returns INSIDE of specific aggregates.  In other words, as a smart man once said:

“[these] portfolios are more a testament to smart marketing rather than smart investing.”


What if we all Know Less Than we Think?

Do you think you’re a better than average driver?  Or a better than average lover?  Or a better than average trader?   Odds are, you do.  Unfortunately, we can’t all be better than average drivers, lovers or traders.  This illusion of superiority is a common cognitive bias in most things.   So what happens when we construct economic models designed around the idea that the entire economy is “rational” or even understands the information that goes into the pricing of securities, assets or even goods and services?  Well, you get things like the Efficient Market Hypothesis.

I was reading a well known paper by William Sharpe on this topic.  He describes the theory as follows:

“The key idea behind the theory is that of market efficiency.

Definition is difficult, but the idea is that a market is efficient if there are many very bright, well informed analysts constantly searching for securities that are mispriced.  As long as this force is operative, when information becomes reasonably public, it will lead to transactions that will shortly cause prices to reflect the information appropriately.  As a result, the price of a security will rarely diverge significantly for long from its intrinsic value where the latter is defined as the certain present value of the uncertain future prospects assessed by a clever, well informed analyst.”

You’ll notice a number of gigantic assumptions in this definition.  Not only does the theory assume that market participants are “bright” (ie, they understand money, the monetary system, the financial system, complex dynamical systems, etc), but it assumes that they also understand what “value” is in the first place.   But what if we don’t understand our financial system all that well?  And what if “value” is a nebulous idea much like the idea of “beauty”?  That would seem to be a rather substantial wrinkle in the ideas that underlie the Efficient Market Hypothesis and foundational economic concepts like rational expectations…..

Rail Traffic Regains Upward Momentum

Warren Buffett’s favorite indicator of economic growth continues to gain momentum here in the early spring.  The latest year over year reading from AAR shows a 9.3% increase in rail traffic.  This brings the 12 week moving averaged to 5.7%, the highest reading since January.  Here’s some more detail via AAR:

“The Association of American Railroads (AAR) today reported increased U.S. rail traffic for the week ending April 12, 2014 with 295,294 total U.S. carloads, up 7.2 percent compared with the same week last year. Total U.S. weekly intermodal volume was 264,382 units, up 9.3 percent compared with the same week last year. Total combined U.S. weekly rail traffic was 559,676 carloads and intermodal units, up 8.2 percent compared with the same week last year.

Eight of the 10 carload commodity groups posted increases compared with the same week in 2013, including grain with 20,760 carloads, up 21.7 percent, and coal with 115,403 carloads, up 11.2 percent. The commodities showing a decrease compared with the same week last year were metallic ores and metals with 22,409 carloads, down 3.9 percent, and forest products with 11,034 carloads, down 1.5 percent.

For the first 15 weeks of 2014, U.S. railroads reported cumulative volume of 4,194,072 carloads, up 1.6 percent compared with the same point last year, and 3,728,465 intermodal units, up 4.8 percent from last year. Total combined U.S. traffic for the first 15 weeks of 2014 was 7,922,537 carloads and intermodal units, up 3.1 percent from last year.”


Historical Market Comparisons Are Meaningless

By Lance Roberts, STA Wealth

As Chief Strategist for STA Wealth Management I start each and every day by consuming copious amounts of a heavily caffeinated beverage and a data feed from a litany of web and blog sites. Over the last couple of days in particular, they have been numerous articles on whether the market is currently in a bubble.   Here are a few as an example that I just grabbed from

Is This a Bubble Market? There’s One Way to Tell

Is Financial Media Warding Off Stock ‘Bubble’?

The Upside of Speculative Market ‘Bubbles’

Yellen: Bubbles? What Bubbles?

Well, you get the idea. First of all, bubbles only occur when no one is looking for them. Bubbles form when greed runs rampant and there is a mass hypnotic state that the current ride will never end. The shear fact that multitudes of articles are being written about “market bubbles” is a sign that we are likely not there, yet. (Read: Too Much Bubble Talk)

However, as a shot of caffeine hits my brain, I read with interest a recent piece on Bloomberg entitled 5 Reasons We’re Not In a 2000 Bubble Redux.” which I have summarized for you:

1) Volume of IPO’s is less than half of the first quarter of 2000

2) First-day returns of IPO’s are just 1/5th of the first 1st quarter of 2000.

3) Speculative companies carried a 43% higher valuation to dividend paying companies in 2000 versus just 26% today.

4) Cash derived from equity issuance was 20% in 2000 versus just 11% today.

5) Share turnover in 2000 was an annualized 89% rate versus 58% today.

While these are certainly some interesting arguments, the comparison between now and the turn of the century peak is virtually meaningless. Why? Because no two major market peaks (speculative bubble or otherwise) have ever been the same. Let me explain.

In late October of 2007, I gave a seminar to about 300 investors discussing why I believed that we were rapidly approaching the end of the bull market and that 2008 would likely be bad, really bad. Part of that discussion focused on market bubbles and what caused them.  The following two slides are from that presentation:

001-Is-This-Time-Different 001-All-Bubbles-Revolved-Around-Something


Every major market peak, and subsequent devastating mean reverting correction, has ever been the result of the exact ingredients seen previously. Only the ignorance of its existence has been a common theme.

As I discussed yesterday, the reason that investors ALWAYS fail to recognize the major turning points in the markets is because they allow emotional “greed” to keep them looking backward rather than forward.

Of course, the media foster’s much of this “willful” blindness by dismissing, and chastising, opposing views generally until it is too late for their acknowledgement to be of any real use.

The next chart shows every major bubble and bust in the U.S. financial markets since 1871 (Source: Robert Shiller)



At the peak of each one of these markets, there was no one claiming that a crash was imminent. It was always the contrary with market pundits waging war against those nagging naysayers of the bullish mantra. Yet, in the end, it was something that was unexpected, unknown or simply dismissed that yanked the proverbial rug from beneath investors.

What will spark the next mean reverting event? No one knows for sure but the catalysts are present from:

  • Excess leverage,
  • IPO’s of negligible companies,
  • Companies using cheap debt to complete stock buybacks and pay dividends, or
  • High levels of investor complacency.

Either individually, or in combination, these issues are all inert. Much like pouring gasoline on a pile of wood, the fire will not start without a proper catalyst. What we do know is that an event WILL occur, it is only a function of “when.” 

The discussion of why “this time is not like the last time” is largely irrelevant. Whatever gains that investors garner in the between now and the next correction by chasing the“bullish thesis” will be wiped away in a swift and brutal downdraft. Of course, this is the sad history of individual investors in the financial markets as they are always “told to buy” but never “when to sell.”

For now, the “bullish case” remains alive and well. The media will go on berating those heretics who dare to point out the risks that prevail. However, the one simple truth is“this time is indeed different.”  When the crash ultimately comes the reasons will be different than they were in the past – only the outcome will remain same.

My Time on the Sell Side

By Ben Carlson, Proprietor, A Wealth of Common Sense

“Wall street is the only place that people ride to in a Rolls Royce to get advice from those who take the subway.” – Warren Buffett

My first experience in the investment industry was during my senior year of college. I spent an entire semester working for a group of sell side analysts.

This is the job that entails following a group of companies in a specific industry and issuing buy, sell and hold signals on each stock (or now it’s market outperform, strong buy, market perform – they change all the time). Along with these recommendations, analysts set price targets and put out earnings estimates and revenue projections.

For the uninitiated, these are the analysts that make the upgrades and downgrades you hear about all the time on financial television.

I learned a lot from this experience, but much of it didn’t sink in for a few years until I really started to understand how the finance industry works. Here are some of my realizations from my time spent on the sell side:

It’s All Relative.  The research analysts I worked with were all extremely intelligent. They knew the companies they covered inside and out. No part of the business structure was spared its rightful analysis. Everything was dissected and restated to try to capture the true nature of the company’s operating performance.

But spending so much time focusing on any one industry or sector can blind you to what’s going on in the rest of the market. Most analysts spend more time looking for great companies as opposed to great stock prices. There’s a big difference between the two. Also, many times the companies get compared to the rest of the industry, not the entire investable universe. There wasn’t much consideration of the possibility that a particular company was being priced as the best house in a bad neighborhood.

Garbage In-Garbage Out.  Financial models are fairly useless if you take them at face value. I dealt with extremely complex Excel spreadsheet models on a daily basis. They were a thing of beauty for spreadsheet geeks. Complex formulas and macros, linked data, pro-forma financial statements — all with the analysis spit out in a neat summary page. Every tiny piece of company and industry data was meticulously estimated or tracked down to the nearest decimal point.

Many of the analysts I worked with told me it was their modelling skills that really set them apart from their peers.  But what I found from navigating these models is that there was always one or two levers you could pull that would completely change your output (price target or earnings estimate). A minor change to a discount rate or future growth rate assumption could drastically change the end result by a wide margin.

I now know that these types of models are only good for setting ranges based on weighted probabilities. They’re made for ballpark accuracy, not precision and even if you understand this take them with a grain of salt.

Price Targets are Worthless.  Every couple of weeks the entire group of analysts from every industry in the department would get together for meetings to discuss the collective stock recommendations for the firm. There were probably 10-15 analysts that each covered 10-15 companies. So we’re talking hundreds of stocks in total. Yet when the head of research pulled up the total number of buy and sell recommendations from every analyst during one meeting, there were only 3 sell calls — in the entire firm. He was basically begging these analysts to make a sell recommendation or two. Yet they weren’t really budging because…

Relationships Matter. What I came realize is that all of the number crunching didn’t matter nearly as much as the meetings and conference calls with company management. The head analysts were constantly on the road meeting with the management team along with suppliers, competitors, going trade shows, etc. These relationships all carried much more weight than the financial models that the junior analysts toiled away at back at the office. The analysts didn’t seem to want to make a critical call against a company in fear of upsetting the management relationship where they got their questions answered.

Independence is Key.  Not all analysts are compromised or bad people. It’s just the nature of the industry. It’s a difficult balancing act to put out reports on companies that could have other financing arrangements or consulting relationships with these banks and brokerages.  Also, there was really no mention of the clients when crafting the research reports.  It was only buy, sell or hold, not risk, patience or time horizon.

I’ve learned that independence in relation to process, relationships, incentive structures and analysis are all extremely important, especially in the finance industry where conflicts abound.

I do think some investors can utilize analyst reports for certain general informational purposes. It’s just that the quarterly earnings guessing game, review mirror changes in recommendations and price targets are not the answer. The long-term industry dynamics and extensive company information can help you spot trends in the business climate. But it’s nearly impossible to use any of this information for actionable long-term investing. And good luck trying to trade on the information as the short-term reactions never go quite as expected.

I’m a believer in taking lessons from all career opportunities, both good and bad. Sometimes negative knowledge by learning what not to do is just as important as figuring out the right way to do something.

Still Buying the (Golden) American Dream…

This recent Gallup survey on expected future returns of asset prices is pretty interesting.  It shows that most Americans still think that owning a home is the best way to generate a high return in the future:



Look at those figures.  The top two assets are gold and real estate.  This shows how out of touch with reality the average American is.  According to the U.S. Census Bureau Survey of Construction single family real estate generates a 0.74% annual return over the last 30 years (this includes multiple housing booms, mind you, so the data is probably much lower if we go further back in time).  So there appears to be some recency bias here despite the housing bust.

And this doesn’t even account for many of the miscellaneous costs involved in real estate.  As I’ve shown previously, a house is basically a depreciating asset that comes with an appreciating piece of land.  But that depreciating asset is extremely expensive over its lifetime.  When you calculate the total costs that go into maintaining this asset the returns are very likely to be negative over long periods of time.  So that 0.74% figure is probably higher than you should really expect.   In fact, the returns from stocks and bonds trump real estate by a healthy margin so Americans have this one totally backwards – the American Dream isn’t quite the dream we have been sold.

Gold is more interesting.  Gold is a commodity that is widely perceived as a currency.  If you look at the long-term returns of gold in the post-Bretton Woods era the real returns are pretty substantial at 7.8%.  That’s not much below stocks at 8.4%, but substantially higher than T-bonds at 3.2% and higher than the aggregate bond index at 5.4%.   This is interesting when you consider that gold is really just a commodity and commodities don’t tend to generate real returns over the long-term.  I’ve surmised that gold has a “faith put” in its price due to the currency belief.  Whether that can last over the long-term is dubious in my view.  So I wouldn’t be surprised if that view turns out to be wrong as well….

5 Good Questions with Terry Odean

By Robert Seawright, Above the Market

Terrance Odean is the Rudd Family Foundation Professor of Finance at the Haas School of Business at the University of California, Berkeley. He is a member of the Journal of Investment Consulting editorial advisory board, of the Russell Sage Behavioral Economics Roundtable, and of the WU Gutmann Center Academic Advisory Board at the Vienna University of Economics and Business. He has been an editor and an associate editor of the Review of Financial Studies, an associate editor of the Journal of Finance, a co-editor of a special issue of Management Science, an associate editor at the Journal of Behavioral Finance, a director of UC Berkeley’s Experimental Social Science Laboratory, a visiting professor at the University of Stavanger, Norway, and the Willis H. Booth Professor of Finance and Banking and Chair of the Finance Group at the Haas School of Business. As an undergraduate at Berkeley, Odean studied Judgment and Decision Making with the 2002 Nobel Laureate in Economics, Daniel Kahneman. This led to his current research focus on how psychologically motivated decisions affect investor welfare and securities prices.

Today I ask (in bold) and Terry answers what I hope are Five Good Questions as part of my longstanding series by that name (see links below).

  1. How much can we really expect to do to overcome our behavioral and cognitive biases?

Someone once said to me, “We can’t control our initial reactions, but we can learn to control what we do next.” Investors will always have cognitive biases. One approach to overcoming them is to practice recognizing biases when they manifest themselves and then adjusting our behavior. This is what Daniel Kahneman describes in Thinking: Fast and Slow as System 2 monitoring System 1. Another approach to overcoming biases is to develop practices and systems that mitigate these biases. For example, if an investor — individual or professional — tends to cling to losing investments, he or she can adopt a rule of automatically selling losers after a predetermined loss. Would this be a perfect solution? Certainly not, but it could be a considerable improvement on current behavior.

  1. Are professional money managers better at dealing with bias than everyone else?

Professional money managers have more opportunity to learn to control their investment biases than do individuals. Some learn. Some don’t. One obstacle is that professional money managers often don’t take a careful look at their own behavior. I’ve been consulting for a company in Boston, Cabot Research, that has developed tools to help professional money managers systematically analyze their past trading decisions to identify biases that are hurting performance.

  1. What are the main differences between individual investors and professional money managers?

Professional money managers devote their working lives to investing. Most individuals invest in their spare time. Professionals work in teams, build institutional knowledge, and make extensive use of computers. Individuals tend to trade on their own. They may have access to public databases, but usually lack the training to do basic analyses such as discounted cash flow valuations of companies. It is difficult for professional money managers to consistently outperform the market by enough to justify their fees. It is even more difficult for individuals to outperform through skill (as opposed to luck) by enough to justify active trading.

  1. What are the most common errors among individuals?

Underdiversification, holding onto losers, chasing winners, buying stocks that catch their attention, systematically ignoring important information, paying too little attention to fees, trading too much.

  1. What are the most common errors among professionals?

I have spent much of my academic career studying individual investors. I’ve had less opportunity to study institutional investors. One difficulty in understanding the biases of institutional investors is that apparent errors could result from biases or they could be driven by how a manager is compensated. For example, managers who have been very successful during the first part of the year often reduce the risk in their portfolio as the year winds down, while managers who have done poorly in the first part of the year tend to increase risk near the end of the year. Why? Managers who have met certain performance targets earlier in the year can often lock in pay incentives by reducing risk at the end of the year; those who are short of the target increase risk in hopes of getting there. Does this behavior make sense for the investors in their funds? No. But it can be understood if you consider the manager’s incentives. On the behavioral side, professional managers may become overconfident, particularly so when they’ve had a good run. Like individuals, many professional managers are reluctant to realize losses. Many professional managers focus most of their attention on the purchases they make and too little on optimizing selling decisions.


Other interviews in the Five Good Questions series: