Feeds:
Posts
Comments

Archive for the ‘Behavioral economics’ Category

David Tepper was on CNBC this morning arguing that stocks are historically cheap:

[Tepper] said the post showed “when the equity risk premium is high historically, you get better returns after that.” He continued, “So we’re at one of the highest all-time risk premiums in history.”

In making his argument Tepper referred to this article, Are Stocks Cheap? A Review of the Evidence, in which Fernando Duarte and Carlo Rosa argue that stocks are cheap because the “Fed model”—the equity risk premium measured as the difference between the forward operating earnings yield on the S&P500 and the 10-year Treasury bond yield—is at a historic high. Here’s the chart:

Here’s Duarte and Rosa in the article:

Let’s now take a look at the facts. The chart [above] shows the weighted average of the twenty-nine models for the one-month-ahead equity risk premium, with the weights selected so that this single measure explains as much of the variability across models as possible (for the geeks: it is the first principal component). The value of 5.4 percent for December 2012 is about as high as it’s ever been.The previous two peaks correspond to November 1974 and January 2009. Those were dicey times. By the end of 1974, we had just experienced the collapse of the Bretton Woods system and had a terrible case of stagflation. January 2009 is fresher in our memory. Following the collapse of Lehman Brothers and the upheaval in financial markets, the economy had just shed almost 600,000 jobs in one month and was in its deepest recession since the 1930s. It is difficult to argue that we’re living in rosy times, but we are surely in better shape now than then.

The Fed model seems like an intuitive measure of market valuation, but how predictive has it been historically? John Hussman examined it in his August 20, 2007 piece Long-Term Evidence on the Fed Model and Forward Operating P/E Ratios. Hussman writes:

The assumed one-to-one correspondence between forward earnings yields and 10-year Treasury yields is a statistical artifact of the period from 1982 to the late 1990′s, during which U.S. stocks moved from profound undervaluation (high earnings yields) to extreme overvaluation (depressed earnings yields). The Fed Model implicitly assumes that stocks experienced only a small change in “fair valuation” during this period (despite the fact that stocks achieved average annual returns of nearly 20% for 18 years), and attributes the change in earnings yields to a similar decline in 10-year Treasury yields over this period.

Unfortunately, there is nothing even close to a one-to-one relationship between earnings yields and interest rates in long-term historical data. Why doesn’t Wall Street know this? Because data on forward operating earnings estimates has only been compiled since the early 1980′s. There is no long-term historical data, and for this reason, the “normal” level of forward operating P/E ratios, as well as the long-term validity of the Fed Model, has remained untested.

Ruh roh. The Fed model is not predictive? What is? Hussman continues:

… [T]he profile of actual market returns – especially over 7-10 year horizons – looks much like the simple, humble, raw earnings yield, unadjusted for 10-year Treasury yields (which are too short in duration and in persistence to drive the valuation of stocks having far longer “durations”).

On close inspection, the Fed Model has nearly insane implications. For example, the model implies that stocks were not even 20% undervalued at the generational 1982 lows, when the P/E on the S&P 500 was less than 7. Stocks followed with 20% annual returns, not just for one year, not just for 10 years, but for 18 years. Interestingly, the Fed Model also identifies the market as about 20% undervalued in 1972, just before the S&P 500 fellby half. And though it’s not depicted in the above chart, if you go back even further in history, you’ll find that the Fed Model implies that stocks were about as “undervalued” as it says stocks are today – right before the 1929 crash.

Yes, the low stock yields in 1987 and 2000 were unfavorable, but they were unfavorable without the misguided one-for-one “correction” for 10-year Treasury yields that is inherent in the Fed Model. It cannot be stressed enough that the Fed Model destroys the information that earnings yields provide about subsequent market returns.

The chart below presents the two versions of Hussman’s calculation of the equity risk premium along with the annual total return of the S&P 500 over the following decade.

Source: Hussman, Investment, Speculation, Valuation, and Tinker Bell (March 2013)

That’s not a great fit. The relationship is much less predictive than the other models I’ve considered on Greenbackd over the last month or so (see, for example, the Shiller PE, Buffett’s total market capitalization-to-gross national product, and the equity q ratio, all three examined together in The Physics Of Investing In Expensive Markets: How to Apply Simple Statistical Models). Hussman says in relation to the chart above:

… [T]he correlation of “Fed Model” valuations with actual subsequent 10-year S&P 500 total returns is only 47% in the post-war period, compared with 84% for the other models presented above [Shiller PE with mean reversion, dividend model with mean reversion, market capitalization-to-GDP]. In case one wishes to discard the record before 1980 from the analysis, it’s worth noting that since 1980, the correlation of the FedModel with subsequent S&P 500 total returns has been just 27%, compared with an average correlation of 90% for the other models since 1980. Ditto, by the way for the relationship of these models with the difference between realized S&P 500 total returns and realized 10-year Treasury returns.

Still, maybe the Fed Model is better at explaining shorter-term market returns. Maybe, but no. It turns out that the correlation of the Fed Model with subsequent one-year S&P 500 total returns is only 23% –  regardless of whether one looks at the period since 1948 (which requires imputed forward earnings since 1980), or the period since 1980 itself. All of the other models have better records. Two-year returns? Nope. 20% correlation for the Fed Model, versus an average correlation of 50% for the others.

Are stocks cheap on the basis of the Fed model? It seems so. Should we care? No. I’ll leave the final word to Hussman:

Over time, Fed Model adherents are likely to observe behavior in this indicator that is much more like its behavior prior to the 1980′s. Specifically, the Fed model will most probably creep to higher and higher levels of putative “undervaluation,” which will be completely uninformative and uncorrelated with actual subsequent returns.

The popularity of the Fed Model will end in tears. The Fed Model destroys useful information. It is a statistical artifact. It is bait for investors ignorant of history. It is a hook; a trap.

Hussman wrote that in August 2007 and he was dead right. He still is.

Order Quantitative Value from Wiley FinanceAmazon, or Barnes and Noble.

Click here if you’d like to read more on Quantitative Value, or connect with me on LinkedIn.

About these ads

Read Full Post »

I’m back from the Value Investing Congress in Las Vegas. There were a number of outstanding presentations, but, for mine, the best was Vitaliy Katsenelson’s epic presentation based on his Little Book of Sideways Markets.

12 years into this sideways market, valuations are still 30% above the historical average, while in 1982 they were about 30% percent below average! Also, historically, stocks spent a good amount of time at below-average valuations before sideways market turned into a secular bull market.

Vitaliy shows that genuine 1930s-style bear markets are rare. Most of the time the market trades sideways or up.

slide-31

Since 2000, the market has traded sideways. Vitaliy expects this to continue for another decade:

slide-41

Read GDP growth has been consistent. There’s little relationship between earnings growth and stock returns.

slide-61

Real GDP growth is very similar in both sideways and bull markets…

slide-71

…the difference in returns is the change in valuation.

slide-121

Don’t chase stocks. In the absence of good stocks, hold cash.

slide-311

Sideways markets contain many cyclical bull and bear markets.

slide-321During a sideways market, asset allocation is not as important as stock selection.

slide-341

 

See the full presentation:

Order Quantitative Value from Wiley FinanceAmazon, or Barnes and Noble.

Click here if you’d like to read more on Quantitative Value, or connect with me on LinkedIn.

Read Full Post »

Chris Turner has a guest post at Doug Short’s Advisor Perspectives called When Warren Buffett Talks … People Listen examining Warren Buffett’s favored market valuation metric: Market Value divided by Gross National Product. (I’ve also examined market value-to-GNP several times. See Warren Buffett and John Hussman On The Stock MarketFRED on Buffett’s favored market measure: Total Market Value-to-GNPThe Physics Of Investing In Expensive Markets: How to Apply Simple Statistical Models)

Here Chris looks at the metric using the CPI deflator on both the numerator — market value — and the denominator — Gross National Product.

Here Chris calculates two fair values for the S&P 500. The blue line shows the historical mean and the green line shows Buffett’s 80 percent value estimate:

Chris comments:

Readers can see from the chart that based on both Buffett’s rule and the historical mean, the S&P would be trading much lower from present levels. The S&P would be sub 1000 based on the historical mean and around 1150 based on the 80% Buffett rule.

Read When Warren Buffett Talks … People Listen.

Order Quantitative Value from Wiley FinanceAmazon, or Barnes and Noble.

Click here if you’d like to read more on Quantitative Value, or connect with me on LinkedIn.

Read Full Post »

Montier Corporate Profit Margins

Source: “What Goes Up Must Come Down!” James Montier (March 2012)

In his recent piece The Endgame is Forced Liquidation John Hussman eloquently describes the reason why investors need to be wary of structural arguments intended to dispose of indicators with a very reliable cyclical record:

On the temptation to disregard proven indicators

As a side-note, it’s important for investors to be wary of “structural” arguments intended to discard indicators that have very reliable cyclical records. For example, hardly a day goes by that we don’t see an attempt to harness some long-term structural factor, such as increasing globalization of trade, to explain away the spike in profit margins over the past few years – in the hope of proving that these margins will be permanent this time. Some of these arguments are discussed in recent weekly comments. But these factors don’t explain the cyclical fluctuations in profit margins at all, and can’t be used to discard the accounting relationships and decades of evidence that corporate profits have a strong secular and tight cyclical mirror-image relationship with the combined total of government and household savings.

Investors get themselves in trouble when they embrace “new economy” theories not because those new theories can be demonstrated in the data; not because existing approaches fail to fully explain the subsequent historical outcomes; but solely because time-tested approaches suggest uncomfortable outcomes in the present instance.

The same sort of structural second-guessing is evident in the gold market here – a good example of what forced liquidation looks like, as my impression is that leveraged longs have been forced into a fire-sale in recent weeks, creating good values for longer-term investors, but with continued near-term risks.  If we look at the ratio of gold prices to the Philadelphia gold index (XAU), we do believe there are structural factors that affect that ratio (primarily the increasing cost of extracting gold over time). But these don’t explain away or eliminate the strong cyclical relationship between the gold/XAU ratio and subsequent returns on the XAU over the following 3-4 year periods. So while we don’t believe that the record high gold/XAU ratio can be taken entirely at face value, there’s no question that it is elevated even on a cyclical basis (that is, even allowing for a gradual structural increase over time), and there’s no question in the data that cyclically elevated gold/XAU ratios have been associated with strong subsequent gains in the XAU index over a 3-4 year period on average, though certainly not without risk or volatility.

As a final example, some analysts (such as the Dow 36,000 authors) have argued that the proper risk premium on stocks, relative to Treasury securities, should be zero. This line of argument was used in 2000 to suggest that stocks were still cheap despite high apparent valuations. But this “secular” argument for high valuations ultimately did not weaken the long-term evidence and tight cyclical relationship between valuations and subsequent market returns. Despite all the new economy arguments about productivity growth,  the internet, globalization, the great moderation, and the outdated relevance of risk premiums, stocks still went on to lose half their value over the next two years, and to produce negative returns over the decade that followed.

The bottom line is that it becomes very tempting – both in speculative markets and fearful ones – to discard well-proven indicators as meaningless by arguing that some “structural” change in the market or the economy makes things different this time. True, those arguments can sometimes be used to explain very long-term changes in the level of an indicator. But even then, new economy arguments are typically ineffective at explaining away the informative cyclical variations in good indicators. Be particularly hesitant about ignoring indicators whose cyclical variations have been effective even in recent data, as is true of the ability of time-tested valuation approaches to explain subsequent 10-year market returns even during the period since the late-1990’s, and the ability of government and household savings to tightly explain cyclical swings in profit margins and subsequent profit growth, even in the most recent economic cycle.

Order Quantitative Value from Wiley FinanceAmazon, or Barnes and Noble.

Click here if you’d like to read more on Quantitative Value, or connect with me on LinkedIn.

h/t Joe

Read Full Post »

Corporate profit margins are presently 70 percent above the historical mean going back to 1947, as I’ve discussed earlier (see, for example, Warren Buffett, Jeremy Grantham, and John Hussman on Profit, GDP and Competition). John Hussman attributes it to the record negative low in combined household and government savings:

The deficit of one sector must emerge as the surplus of another sector. Corporations benefit from deficit spending despite wages at record lows as a share of economy.

John Hussman spoke recently at the 2013 Wine Country conference. Here he describes the relationship between corporate profits, and government, and household savings (starting at 22.08):

Hussman’s whole talk is well worth hearing.

Order Quantitative Value from Wiley FinanceAmazon, or Barnes and Noble.

Click here if you’d like to read more on Quantitative Value, or connect with me on LinkedIn.

h/t Meb Faber

Read Full Post »

headerBkgnd

We wrote an article for the April issue of Value Investing Letter giving an overview of Quantitative Value, discussing the quantitative value model outlined in the book, and applying it to Apple Inc. (AAPL). It’s been smashed up since then, and there was also some big news yesterday — which is that AAPL is going to return $100 billion to its shareholders by the end of 2015 – so I’m highlighting it here. To put that $100 billion capital return in context, AAPL closed Tuesday with a market capitalization of $380 billion. Incredibly, its $145 billion cash pile won’t shrink because the new buyback brings its return of capital up to about the level of its current free cash flow. Weirdly, it’s now regarded as the “animal investors like least: a slow-growing tech stock.” From our earlier article:

We ran our model on March 13, 2013, finding Apple Inc. (AAPL) to be one of the highest quality stocks in the bargain bin. AAPL designs, manufactures and markets a variety of mobile devices, including the iPhone, iPad, and iPod, along with Mac products, operating systems, cloud products, related software and services, and many other products. Its devices are ubiquitous, and are catnip to consumers, driving one of the most valuable brands in the world. Why has the company shed over a third of its market capitalization since peaking near $700 per share in September of 2012?

In short, this former hedge fund darling has become the company that everyone loves to hate. iPod and Mac sales are down from last year. The media has pounced on reports of weakness in the sale of the iPhone 5 and now questions whether AAPL will be competitive with the newest smartphones. The market did not react well to AAPL’s latest earnings announcement, and dozens of analysts have reduced their price targets over the past few months. So what’s going on here? Is AAPL again headed for the technology dustbin of history? Or might this be a manifestation of investors’ behavioral bias?

Our model leads us to believe that AAPL offers exceptional franchise characteristics and is statistically cheap, with an EBIT/TEV yield of nearly 21 percent, which is among the very cheapest within the cheapest decile of stocks in the market. Below are some additional highlights from the quantitative output of our screens, which will give the reader a high-level view of the company’s profile, and then we will dig deeper on some details. Clearly, the fact that Mr. Market is offering us a company of this quality at this price should raise some questions.

AAPL Summary Statistics (As At March 13, 2013)

(Click to enlarge)

AAPL

To continue reading the article please click here.

Order Quantitative Value from Wiley FinanceAmazon, or Barnes and Noble.

Click here if you’d like to read more on Quantitative Value, or connect with me on LinkedIn.

No position.

Read Full Post »

Value Line’s Median Appreciation Potential (VLMAP) 2009

3to5year4yrchart10-8-10

Marketwatch’s Mark Hulbert has a great article Finding the best four-year market forecaster examining Value Line’s Median Appreciation Potential (VLMAP), which is the median three-to-five year gain that Value Line’s analysts estimate for the 1,700 stocks they cover.

From Value Line October 2010 update:

The estimate of the median price appreciation potential is found by first calculating the percentage change between the current price of each stock in our universe and the middle of its 3- to 5-year Target Price Range. These figures are then arrayed, and the median price appreciation potential is determined. We select the median of the array (the middle) as the most likely price, in order to play down the effect of outliers, that is, excessively large or small percentage price changes.

The chart included [above] depicts the results of those projections from 1983 to 2009, using the Value Line Arithmetic Index as our measure of the market. The actual price is taken as the average of the middle year of the 3- to 5-year forecast, so that a projection made at the end of 1983 would be compared to the average price of the index in 1987. Accordingly, we are comparing actual results to a 3 ½ year forecast.

Those who follow the VLMAP often adjust it downward when translating it into a forecast because Value Line’s analysts — like most of Wall Street (see my post on forward earnings) — are on average too optimistic. Note that the 2009 projection has turned out to be roughly right:

Our estimate for the year 2009 (made at the end of 2005) was 2683. The average price of the Value Line Arithmetic Index in 2009 was 1758. The large deviation arises from the effects of the recession that followed in the wake of the financial turmoil in late 2008 and early 2009. Meanwhile, the average deviation between the projected and actual average prices during this period was 18% (ignoring signs). The median deviation during this period was 11%. The projection for 2013 now stands at 3500. The 4-year projected price of 3500 now stands at 40% above the current level—suggesting respectable returns for patient investors.

The market closed Friday at 3,444. Why does this model work so well?

Mark Robertson, founder and managing partner of the Detroit-based advisory service Manifest Investing, also uses a version of the VLMAP. He thinks one answer lies in the willingness of Value Line’s analysts to focus on a longer-term horizon than is typical for most Wall Street analysts.

It may seem “counterintuitive,” he acknowledges, but “long-term forecasting is actually easier and more accurate than the quarterly whispering and chasing that we see from and on Wall Street.”

Because they are focusing on where the stocks they follow will be trading in three- to five-years’ time, Value Line’s analysts are less likely to get swept away by whatever mood has captured Wall Street’s attention, Robertson says.

Compared with analysts who focus on just the next couple of quarters, for example, Value Line’s are less likely to adjust their price targets based on the latest earnings. This makes them less inclined to get more bullish as the market goes higher — a tendency that leads to being excessively bullish at market tops.

Over the past five years the VLMAP has been as low as 45 percent and as high as 185 percent. It currently stands at 50 percent, which is close to the five-year low and only slightly higher than the 35 percent estimate logged in the weeks leading up to the bull-market high in October 2007.

Read Finding the best four-year market forecaster.

Order Quantitative Value from Wiley FinanceAmazon, or Barnes and Noble.

Click here if you’d like to read more on Quantitative Value, or connect with me on LinkedIn.

Read Full Post »

Ratio of Corporate Profits-to-GDP and Returns (1947 to Present)

Source: Hussman Weekly Comment “Taking Distortion at Face Value,” (April 8, 2013)

Warren Buffett, 1999

[F]rom 1951 on, the percentage settled down pretty much to a 4% to 6.5% range.

In my opinion, you have to be wildly optimistic to believe that corporate profits as a percent of GDP can, for any sustained period, hold much above 6%. One thing keeping the percentage down will be competition, which is alive and well.

– Warren Buffett, Mr. Buffett on the Stock Market (November 1999)

Jeremy Grantham, 2006

Profit margins are probably the most mean-reverting series in finance, and if profit margins do not mean-revert, then something has gone badly wrong with capitalism. If high profits do not attract competition, there is something wrong with the system and it is not functioning properly.

– Jeremy Grantham, Barron’s (c. 2006), via Katsenelson, The Little Book of Sideways Markets.

John Hussman, 2013

In general, elevated profit margins are associated with weak profit growth over the following 4-year period. The historical norm for corporate profits is about 6% of GDP. The present level is about 70% above that, and can be expected to be followed by a contraction in corporate profits over the coming 4-year period, at a roughly 12% annual rate. This will be a surprise. It should not be a surprise.

– John Hussman, Two Myths and a Legend (March 11, 2013)

h/t Butler|Philbrick|Gordillo and Associates

Order Quantitative Value from Wiley FinanceAmazon, or Barnes and Noble.

Click here if you’d like to read more on Quantitative Value, or connect with me on LinkedIn.

Read Full Post »

Butler|Philbrick|Gordillo and Associates have an interesting post called What the Bull Giveth, the Bear Taketh Away on the duration and magnitude of all bull and bear market periods in U.S. stocks since 1871.

For the purpose of the study below, we examined the S&P 500 price series from Shiller’s publicly available database to understand the duration and magnitude of all bull and bear market periods in U.S. stocks since 1871. We defined a bear market as a drop in prices of at least 20% from any peak, and which lasted at least 3 months. Bull markets were then defined as a rise of at least 50% from the bottom of a bear market, over a period lasting at least 6 months.

Chart 1 and Table 1 describe every bull market since 1871 in the S&P, including duration and magnitude information. The lesson from this analysis is uninspiring for equity bulls, as we will see. The core hurdle is that the current bull market has (through end of February) already delivered 105% of gains, against the median 124% bull market run through history (using monthly data). Of course, this means that, should this bull market deliver an average surge, investors can hope for less than 20% more growth from this cycle. Further, given that the median bull market has historically lasted 50 months, and we are currently in our 49th bull month, we are about due for a wipeout.

Chart 1. Bull Markets since 1871

Source: Shiller (2013)

Table 1. Bull Markets since 1871 – Statistics

Source: Shiller (2013)

The current bull market has already delivered 85 percent of the gains, and lasted about as long, as the median historical bull market.

Read What the Bull Giveth, the Bear Taketh Away for the bear market equivalents of the preceding bull table and chart. Butler|Philbrick|Gordillo and Associates demonstrate that, if it follows the median bear market, it will wipe out 38 percent of all prior gains.

Order Quantitative Value from Wiley FinanceAmazon, or Barnes and Noble.

Click here if you’d like to read more on Quantitative Value, or connect with me on LinkedIn.

Read Full Post »

Butler|Philbrick|Gordillo and Associates’ argue in Valuation Based Equity Market Forecasts – Q1 2013 Update that “there is substantial value in applying simple statistical models to discover average estimates of what the future may hold over meaningful investment horizons (10+ years), while acknowledging the wide range of possibilities that exist around these averages.”

Butler|Philbrick|Gordillo use linear regression to examine several variations of the Shiller PE (and other cyclically adjusted PE ratios over periods ranging from one to 30 years), Tobin’s q ratio and Buffett’s total market capitalization-to-gross national product ratio (“TMC/GNP”). They have analyzed the power of each measure to explain inflation-adjusted stock returns including reinvested dividends over subsequent multi-year periods, setting their findings out in the following matrix:

Matrix 1. Explanatory power of valuation/future returns relationships

Source: Shiller (2013), DShort.com (2013), Chris Turner (2013), World Exchange Forum (2013), Federal Reserve (2013), Butler|Philbrick|Gordillo & Associates (2013).
Butler|Philbrick|Gordillo comment:
Matrix 1. contains a few important observations. Notably, over periods of 10-20 years, the Q ratio, very long-term smoothed PE ratios, and market capitalization / GNP ratios are equally explanatory, with R-Squared ratios around 55%.  The best estimate (perhaps tautologically given the derivation) is derived from the price residuals, which simply quantify how extended prices are above or below their long-term trend.The worst estimates are those derived from trailing 12-month PE ratios (PE1 in Matrix 1 above). Many analysts quote ‘Trailing 12-Months’ or TTM PE ratios for the market as a tool to assess whether markets are cheap or expensive. If you hear an analyst quoting the market’s PE ratio, odds are they are referring to this TTM number. Our analysis slightly modifies this measure by averaging the PE over the prior 12 months rather than using trailing cumulative earnings through the current month, but this change does not substantially alter the results.As it turns out, TTM (or PE1) Price/Earnings ratios offer the least information about subsequent returns relative to all of the other metrics in our sample. As a result, investors should be extremely skeptical of conclusions about market return prospects presented by analysts who justify their forecasts based on trailing 12-month ratios.

Butler|Philbrick|Gordillo note:

Our analysis provides compelling evidence that future returns will be lower when starting valuations are high, and that returns will be higher in periods where starting valuations are low.

So where are we now? Table 1 below from the post provides a snapshot of some of the results from Butler|Philbrick|Gordillo’s analysis. The table shows estimated future returns based on an aggregation of several factor models over some important investment horizons:

Table 1. Factor Based Return Forecasts Over Important Investment Horizons

Source: Shiller (2013), DShort.com (2013), Chris Turner (2013), World Exchange Forum (2013), Federal Reserve (2013), Butler|Philbrick|Gordillo & Associates (2013)

Butler|Philbrick|Gordillo note that:
You can see from the table that, according to a model that incorporates valuation estimates from 4 distinct domains, and which explains over 80% of historical returns since 1871, stocks are likely to deliver 1% or less in real total returns over the next 5 to 20 years. Yikes.

They conclude:

[T]he physics of investing in expensive markets is that, at some point in the future, perhaps years from now, the market has a very high probability of trading back below current prices; perhaps far below.

The post is a well-researched, and comprehensive analysis of several long-term market-level valuation measures. It is a worthy contribution to the research in this area. Read Valuation Based Equity Market Forecasts – Q1 2013 Update.

Order Quantitative Value from Wiley FinanceAmazon, or Barnes and Noble.

Click here if you’d like to read more on Quantitative Value, or connect with me on LinkedIn.

Read Full Post »

Older Posts »

Follow

Get every new post delivered to your Inbox.

Join 2,328 other followers

%d bloggers like this: