January 2018 Data Update 10: The Price is Right!

In my first nine posts on my data update for 2018, I focused on the costs that companies face in raising equity and debt, and their investment, financing and dividend decisions. In assessing those decisions, though, I looked at their actions through the lens of value creation, arguing that investing in projects that earn less than their cost of capital is not a good use of shareholder capital. While this may seem like a reasonable conclusion, it is built on the implicit assumption that financial markets reward value creation and punish value destruction. As any market observer will tell you, markets have minds of their own, sometimes rewarding companies for bad behavior and punishing companies that take the right actions. In this post, I look at market pricing around the world, and point to potential inconsistencies with the fundamentals.

Value vs Price

In multiple posts on this blog, I have argued that we need to stop using the words, value and price, interchangeably, that they not only can be very different for the same asset, at any point in time, but that they are driven by different forces, require different mindsets to understand, and give rise to different investment philosophies. The picture below summarizes the key distinctions:

Understanding the difference between value and price, at least for me, is freeing, because it not only makes me aware of the assumptions that I, as an investor who believes in value and convergence, am making, but also makes me respect and recognize those who might have a different perspective. The bottom line, though, is that the pricing process can sometimes reward firms that take actions that no tonly have no effect on value, but may actually destroy value, and punish firms that are following financial first principles. Even though I believe that value ultimately prevails, it behooves to me to try to understand how the market is pricing stocks, since it will help me be a better investor.

The Pricing Process

I will begin with what sounds like a over-the-top assertion. Much of what we see foisted on us as valuation, including those that you see backing up IPOs, acquisitions or big investment decisions, are really pricing models, masquerading as valuations. In many cases, bankers and analysts use the front of estimating cash flows for a discounted cashflow valuation, while slipping in a multiple to estimate the biggest cash flow (the terminal value) in what I call Trojan Horse DCFs. I am not surprised that pricing is the name of the game in banks and equity research, but I am puzzled at why so much time is wasted on the DCF misdirection play. There are four steps to pricing an asset or company well, and done well, there is no reason to be ashamed of a pricing.

1. Similar, Traded Assets

To price an asset, you have to find "similar" assets that are traded in the market. Note the quote marks around similar, because with publicly traded stocks, you will be required to make judgment calls on what you view as similar. The conventional practice in pricing seems to be country and sector focused, where an Indian food processing company is compared to other food processing companies in India, on the implicit assumption that these are the most comparable companies. That practice, though, can not only lead to very small samples in some countries, but also can yield companies that have very different fundamentals from the company that you are valuing.

1.1: With equities, there are no perfect matches: If you are valuing a collectible (Tiffany lamp or baseball card), you might be able to find identical assets that have been bought and sold recently. With stocks, there are no identical stocks, since even with companies that are close matches, differences will persist.

1.2: Small, more similar, sample or large, more diverse, sample: Given that there are no stocks identical to the one that you are trying to value in the market, you will be faced with two choices. One is to define "similar" narrowly, looking for companies that are listed on the same market as yours, of similar size and serving the same market. The other is to define "similar" more broadly, bringing in companies in other markets and perhaps with different business models. The former will give you more focus and perhaps fewer differences to worry about and the latter a much larger sample, with more tools to control for differences.  

2. Pricing Metric

To compare pricing across companies, you have to pick a pricing metric and broadly speaking, you have three choices:

Post on differences in value

The market capitalization is the value of equity in a business, the enterprise value is the market value of the operating assets of the firm and the firm value is the market value of the entire firm, including any cash and non-operating assets. While firm value is lightly used, because non-operating assets and cash can skew it, both enterprise value and equity value are both widely used. In computing these metrics, there are three issues that do complicate measurement. One is that market capitalization (market value of equity) is constantly updated, but debt and cash numbers come from the most recent balance sheets, creating a timing mismatch. The second is that the market value of equity is easily observable for publicly traded companies, but debt is often not traded (if bank debt) and book debt is used as a stand in for market debt. Finally, non-operating assets often take the form of holdings in other companies, many of which are private, and the values that you have for them are book values. 

2.1: When leverage is different across companies, go with enterprise value: When comparing pricing across companies, it is better to focus on enterprise value, when debt ratios vary widely across the companies, because equity value at highly levered companies is much smaller and more volatile and cannot be easily compared to equity value at lightly levered companies.

2.2: With financial service companies, stick with equity: As I have argued in my other posts, debt to a bank, investment bank or insurance company is more raw material than source of capital and defining debt becomes almost impossible to do at financial service firms. Rather than wrestle with his estimation problem, my suggestion is that you stick with equity multiples.

3. Scaling Variable

When pricing assets that come in standardized units, you can compare prices directly, but that is never the case with equities, for a simple reason. The number of shares that a company chooses to have will determine the price per share, and arguing that Facebook is more expensive than Twitter because it trades at a higher price per share makes no sense. It is to combat this that we scale prices to  a common variable, whether it be earnings, cash flows, book value, revenues or a driver of revenues (users, riders, subscribers etc.).

3.1: Be internally consistent: If your pricing metric is an equity value, your scaling variable has to be an equity value (net income, book value of equity). If your pricing metric is enterprise value, your scaling variable has to be an operating variable (revenues, EBITDA or book value of invested capital). 

3.2: Life cycle matters: The multiple that you use to judge pricing will change, as a company moves through the life cycle.

Early in the life cycle, the focus will be on potential market size or revenue drivers, since the company's own revenues are small or non-existent and it is losing money. As it grows and matures, you will see a shift to equity earnings first, since growth companies are mostly equity funded, and then to operating earnings and EBITDA, as mature companies use debt, ending with a focus on book value as a proxy for liquidation value, in decline.

4. Control for differences

As we noted, when discussing similar companies, no matter how carefully you pick comparable firms, there will be differences that persist between the company that you are trying to value and the comparable firms. The test of good pricing is whether you detect the variables that cause differences in pricing and how well you control for the differences. In much of equity research, the preferred mode for dealing with these differences is to spin them to justify whatever pre-conceptions you have about a stock.

4.1: Check the fundamentals: In intrinsic value, we argued that the value of a  company is a function of its cash flows, growth and risk. If you believe that the fundamentals ultimately prevail in markets, you should tie the multiples you use to these fundamentals, and using algebra and a basic discounted cash flow model will lead you to fundamentals drivers of any multiple.

4.2: Let the market tell you what matters: If you are a pure trader, who has little faith that the fundamentals will prevail, you can can take a different path. You can look at other data, related to the companies that you are pricing, and look for correlation. Put simply, you are trying to use the data to back out what variables best explain differences in market pricing, and using those variables to price your company.

To illustrate the differences between the two approaches, take a look at my pricing of Severstal, where I used fundamentals to conclude that it was under priced, and my pricing of Twitter, at the time of its IPO, where I backed out the number of users as the key variable driving the market pricing of social media companies and priced Twitter accordingly.

Pricing around the Globe

Assuming that you have had the patience to get to this part of the post, let's look at the pricing numbers at the start of 2018, around the world, starting with earnings multiples (PE and EV/EBITDA), moving on to book value multiples (Price to Book, EV to Invested Capital) and ending with revenue multiples (EV/Sales).

1. Earnings Multiples

Earnings multiples have the deepest roots in pricing, with the PE ratio still remaining the most used multiple in the world. In the last two to three decades, there has been a decided shift towards enterprise value multiples, with EV/EBITDA leading the way. While I am skeptical of EBITDA as a measure of accessible cash flow, since it is before taxes and capital expenditures, I understand its pull, especially in aging companies with significant depreciation charges. If you assume that depreciation will need to go back into capital expenditures, there is an intermediate measure of pricing, EV to EBIT.

In the chart below, I look at the distribution of PE ratios globally, and report on the PE ratio distributions, broken down region, at the start of 2018.

I know that it is dangerous to base investment judgments on simple comparisons of pricing multiples, but at the start of 2018, the most expensive market in the world on a PE ratio basis, is China, followed by India, and the cheapest market is Eastern Europe and Russia. If you would like to see the values for earnings multiples, by country, please click at this link.

If you are more interested in operating earnings multiples, the chart below has the distribution of EV/EBIT and EV/EBITDA multiples:

China again tops the scale, with the highest EV/EBITDA multiples, and Eastern Europe and Russia have the lowest EV/EBITDA multiples. Earnings multiples also vary across sectors, with some of the variation attributable to fundamentals (differences in growth, risk and cash flows) and some of it to misplacing. The sectors that trade at the highest and lowest PE ratios are identified below:

Download industry spreadsheet

You can download the full list of earnings multiples for all of the sectors, by clicking on this link. 

2. Book Value Multiples

The delusion of fair value accounting is that balance sheets will one day provide better estimates of how much a business in worth than markets, and while I believe that day will never come, even accountants are entitled to their dreams. That said, there are investors who still put their faith in book value and compare market prices to book value, either in equity terms or operating asset terms:

• Price to Book Equity = Market Value of Equity / Book Value of Equity
• EV to Invested Capital = (Market Value of Equity + Market value of Debt - Cash)/ (Book value of equity + Book value of Debt - Cash)

In the table below, I report on price to book and enterprise value to invested capital ratios, by sub-region of the world:

The most expensive sub-region of the world is  India, on both a price to book and EV/Invested capital basis, and the lowest priced stocks are again in Eastern Europe and Russia. If you would like to see book value multiples, by country, click at this link.  With book value multiples, the differences you observe across sectors not only reflect differences in fundamentals and pricing errors, but also accounting inconsistencies on how capital expenditures in non-manufacturing companies are dealt with, as opposed to manufacturing firms. I tried to correct for these inconsistencies, by capitalizing R&D at all firms, but that correction goes only part way and the most expensive and cheapest sectors, with my corrected book values, are listed below:

Download industry PBV spreadsheet

You can download the book value multiple data, by sector, by clicking here.

3. Revenue Multiples

To the question of why investors and analysts look at multiples of revenues, my one word answer is "desperation". When every other number in your income statement is negative, you have to keep climbing the statement until you hit a positive value. That said, there is value in focusing on a variable that accountants have the least influence over, and the heat map below captures differences in the enterprise value to sales ratios across the globe.

Unlike earnings and book value multiples, which have a pronounced peak in the middle of the distribution, revenue multiples are more evenly distributed, with quite a few firms trading at more than ten times revenues. As with earnings and book value multiples, I report revenue multiples, by country at this link and  by sector at this link. Note that there no revenue multiples reported for financial service firms, where neither enterprise value nor revenues can be meaningfully measured or estimated.

Conclusion

I am an investor, who believes in value, but it would be foolhardy on my part to ignore the pricing game, since I am dependent upon it ultimately to cash out on my value gains. In this post, I have looked at the pricing differences around the globe, at least based upon market prices at the start of 2018. Of all of my data posts, this is the one that is the most dynamic and likely to change over short periods, since markets can react to change far more quickly than companies can. 

YouTube Video

Datasets

1. Multiples, by Sector, in January 2018

2. Multiples, by Country, in January 2018

Data Update Posts

1. January 2018 Data Update 1: Numbers don't lie, or do they?
2. January 2018 Data Update 2: The Buoyancy of US Equities!
3. January 2018 Data Update 3: Taxing Questions on Value
4. January 2018 Data Update 4: The Currency Conundrum
5. January 2018 Data Update 5: Country Risk Update
6. January 2018 Data Update 6: A Cost of Capital Primer
7. January 2018 Data Update 7: Growth and Value - Investment Returns
8. January 2018 Data Update 8: Debt and Taxes
9. January 2018 Data Update 9: Dividends, Buybacks and Cash Holdings
10. January 2018 Data Update 10: The Price is Right!

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Superman and Stocks: It's not the Cape (CAPE), it's the Kryptonite(Cash flow)!

Just about a week ago, I was on a 13-hour plane trip from Tokyo to New York. I know that this will sound strange but I like long flights for two reasons. The first is that they give me extended stretches of time when I can work without interruption, no knocks on the door or email or phone calls. I readied my lecture notes for next semester and reviewed and edited a manuscript for one of my books in the first half on the trip. The second is that I can go on movie binges with my remaining time, watching movies that I would have neither the time nor the patience to watch otherwise. On this trip, however, I made the bad decision of watching Batman versus Superman, Dawn of Justice, a movie so bad that the only way that I was able to get through it was by letting my mind wander, a practice that I indulge in frequently and without apologies or guilt. I pondered whether Superman needed his suit or more importantly, his cape, to fly. After all, his powers come from his origins (that he was born in Krypton) and not from his outfit and the cape seems to be more of an aerodynamic drag than an augmentation. These deep thoughts about Superman's cape then led me to thinking about CAPE, the variant on PE ratios that Robert Shiller developed, and how many articles I have read over the last decade that have used this measure as the basis for warning me that stocks are headed for a fall. Finally, I started thinking about Kryptonite, the substance that renders Superman helpless, and what would be analogous to it in the stock market. I did tell you that I have a wandering mind and so, if you don't like Superman or stocks, consider yourself forewarned!

The Stock Market’s CAPE

As stocks hit one high after another, the stock market looks like Superman, soaring to new highs and possessed of super powers.

There are many who warn us that stocks are overheating and that a fall is imminent. Some of this worrying is natural, given the market's rise over the last few years, but there are a few who seem to have surrendered entirely to the notion that stocks are in a bubble and that there is no rational explanation for why investors would invest in them. In a post from a couple of years ago, I titled these people as  bubblers and classified them into doomsday, knee jerk, conspiratorial, righteous and rational bubblers. The last group (rational bubblers) are generally sensible people, who having fallen in love with a market metric, are unable to distance themselves from it.

One of the primary weapons that rational bubblers use to back up their case is the Cyclically Adjusted Price Earnings (CAPE), a measure developed and popularized by Robert Shiller, Nobel prize winner whose soothsaying credentials were amplified by his calls on the dot com and housing bubbles. For those who don’t quite grasp what the CAPE is, it is the conventional PE ratio for stocks, with two adjustments to the earnings. First, instead of using the most recent year’s earnings, it is computed as the average earnings over the prior ten years. Second, to allow for the effects of inflation, the earnings in prior years is adjusted for inflation.  The CAPE case against stocks is a simple one to make and it is best seen by graphing Shiller’s version of it over time.

Shiller CAPE data (from his site)

The current CAPE of 27.27 is well above the historic average of 16.06 and if you buy into the notion of mean reversion, the case makes itself, right? Not quite! As you can see, even within the CAPE story, there are holes, largely depending upon what time period you use for your averaging. Relative to the fully history, the CAPE looks high today, but relative to the last 20 years, the story is much weaker. Contrary to popular view, mean reversion is very much in the eyes of the beholder.

The CAPE’s Weakest Links

Robert Shiller has been a force in finance, forcing us to look at the consequences of investor behavior and chronicling the consequences of “irrational exuberance”. His work with Karl Case in developing a real estate index that is now widely followed has introduced discipline and accountability into real estate investing and his historical data series on stocks, which he so generously shares with us, is invaluable. You can almost see the “but” coming and I will not disappoint you. Of all of his creations, I find CAPE to be not only the least compelling but also potentially the most dangerous, in terms of how often it can lead investors astray. So, at the risk of angering those of you who are CAPE followers, here is my case against putting too much faith in this measure, with much of it representing updates of my post from two years ago.

1. The CAPE is not that informative

The notion that CAPE is a significant improvement on conventional PE is based on the two adjustments that it makes, first by replacing earnings in the most recent period with average earnings over ten years and the second by adjusting past earnings for inflation to make them comparable to current earnings. Both adjustments make intuitive sense but at least in the context of the overall market, I am not sure that either adjustment makes much of a difference. In the graph below, I show the trailing PE, normalized PE (using the average earnings over the last ten years) and CAPE for the S&P 500 from 1969 to 2016 (last twelve months). I also show Shiller's CAPE, which is based on a broader group of US stocks in the same graph.

Download spreadsheet with PE ratios

First, it is true that especially after boom periods (where earnings peak) or economic crises (where trailing earnings collapse), the CAPEs (both mine and Shiller's) yield different numbers than PE.  Second, and more important, the four measures move together most of the time, with the correlation matrix shown in the figure. Note that the correlation is close to one between the normalized PE and the CAPE, suggesting that the inflation adjustment does little or nothing in markets like the US and even the normalization makes only a marginal difference with a correlation of 0.86 between the unadjusted PE and the Shiller PE.

2. The CAPE is not that predictive

The question then becomes whether using the CAPE as a valuation metric yields judgments about stocks that are superior to those based upon just PE or normalized PE. To test this proposition, I looked at the correlation between the values of different metrics, including trailing PE, CAPE, the inverse of the dividend yield, earnings yield and the ratio of Shiller PE to the Bond PE) today and stock returns in the following year and the following five years:

There is both good news and bad news for those who use the Shiller CAPE as their stock valuation metric. The good news is that the fundamental proposition that stocks are more likely to go down in future periods, if the Shiller CAPE is high today, seems to be backed up. The bad news is two fold. First, the relationship is noisy or in investment parlance, the predictive power is low, especially with one-year returns. Second, the trailing PE actually does a better job of predicting one-year returns than the CAPE and while CAPE becomes the better predictor than trailing PE over a five-year period, it is barely better than using a dividend yield indicator.  While I have not included these in the table, I will wager that any multiple (such as EV to EBITDA) would do as good (or as bad, depending on your perspective) a job as market timing.

As a follow-up, I ran a simple test of the payoff to market timing, using the Shiller CAPE and actual stock returns from 1927 to 2016. At the start of every year, I first computed the median value of the Shiller CAPE over the previous fifty years and assumed an over priced threshold at 25% above the median (which you can change). If the actual CAPE was higher than the threshold, I assumed that you put all your money in treasury bills for the following year and that if the CAPE was lower than the threshold, that you invested all your money in equities. (You can alter these values as well). I computed how much $100 invested in the market in 1927 would have been worth in August of 2016, with and without the market timing based on the CAPE:

Download spreadsheet and change parameters

Note that as you trust CAPE more and more (using lower thresholds and adjusting your equity allocation more), you do more and more damage to the end-value of your portfolio. The bottom line is that it is tough to get a payoff from market timing, even when the pricing metric that you are using comes with impeccable credentials. 

3. Investing is relative, not absolute

Notwithstanding its weak spots, let’s take the CAPE as your measure of stock market valuation. Is a CAPE of 27.27 too high, especially when the historic norm is closer to 16? The answer to you may sound obvious, but before you do answer, you have to consider where you would put your money instead. If you choose not to buy stocks, your immediate option is to put your money in bonds and the base rate that drives the bond market is the yield on a riskless (or close to riskless) investment. Using the US treasury bond as a proxy for this riskless rate in the United States, I construct a bond PE ratio using that rate:

Bond PE = 1/ Treasury Bond Rate

Thus, if you invest in a treasury bond on August 22, with a yield of 1.54%, you are effectively paying 64.94 (1/.0154) times your earnings. In the graph below, I graph Shiller’s measures of the CAPE against this T.Bond PE from 1960 to 2016:

Download T Bond Rate PE data

I also compute a ratio of stock PE to T.Bond PE that will use as a measure of relative stock market pricing, with a low value indicating that stocks are cheap (relative to T.Bonds) and a high value suggesting the opposite. As you can see, bringing in the low treasury bond rates of the last decade into the analysis dramatically shifts the story line from stocks being over valued to stocks being under valued. The ratio is as 0.42 right now, well below the historical average over any of the time periods listed, and nowhere near the 1.91 that you saw in 2000, just before the dot com bust or  even the 1.04 just before the 2008 crisis. 

4. Its cash flow, not earnings that drives stocks

The old adage that it is cash flows, not earnings, that drives stocks is clearly being ignored when you look at any variant of PE ratios. To provide a sense of what stock prices look like, relative to cash flows, I computed a multiple of total cash returned to stockholders by companies (including buybacks) and compared these multiples to Shiller’s CAPE in the graph below:

S&P 500 Earnings and Cash Payout

Here again, there seems to be a disconnect. While the CAPE has risen for the market, from 20.52 in 2009 to 27.27 in 2016, as stocks soared during that period, the Price to CF ratio has remained stable over that period (at about 20), reflecting the rise in cash returned by US companies, primarily in buybacks over the period.

Am I making the case that stocks are under valued? If I did, I would be just as guilty as those who use CAPE to make the opposite case. I am not a market timer, by nature, and any single pricing metric, no matter how well reasoned it may be, is too weak to capture the complexity of the market. Absolutism in market timing is a sign of either hubris or ignorance.

The Market’s Kryptonite

At this point, if you think that I am sanguine about stocks, you would be wrong, since the essence of investing in equities is that worry goes with it. If it’s not the high CAPE that is worrying me, what is? Here are my biggest concerns, the kryptonite that could drain the market of its strength and vitality.

1. The Treasury Alternative (or how much are you afraid of your central bank?)  If the reason that you are in stocks is because the payoff for being in bonds is low, that equation could change if the bond payoff improves. If you are Fed-watcher, convinced that central banks are all-powerful arbiters of interest rates, your nightmares almost always will be related to a meeting of the Federal Open Market Committee (FOMC), and in those nightmares, the Fed will raise rates from 1.50% to 4% on a whim, destroying your entire basis for investing in stocks. As I have noted in these earlier posts, where I have characterized the Fed as the Wizard of Oz and argued that low rates are more a reflection of low inflation and anemic growth than the result of quantitative easing, I believe that any substantial rate rises will have to come from shifts in fundamentals, either an increase in inflation or a surge in real growth. Both of these fundamentals will play out in earnings as well, pushing up earnings growth and making the stock market effect ambiguous. In fact, I can see a scenario where strong economic growth pushes T. bond rates up to 3% or higher and stock markets actually increase as rates go up.
2. The Earnings Hangover It is true that we saw a long stint of earnings improvement after the 2008 crisis and that the stronger dollar and a weaker global economy are starting to crimp earnings levels and growth. Earnings on the S&P 500 dropped in 2015 by 11.08% and are on a pathway to decline again this year and if the rate of decline accelerates, this could put stocks at risk. That said, you could make the case that the earnings decline has been surprisingly muted, given multiple crises, and that there is no reason to fear a fall off the cliff. No matter what your views, though, this will be more likely to be a slow-motion correction, offering chances for investors to get off the stock market ride, if they so desire.
3. Cash flow Sustainability: My biggest concern, which I voiced at the start of the year, and continue to worry about is the sustainability of cash flows. Put bluntly, US companies cannot keep returning cash at the rate at which they are today and the table below provides the reason why:

Year	Earnings	Dividends	Dividends + Buybacks	Dividend Payout	Cash Payout
2001	38.85	15.74	30.08	40.52%	77.43%
2002	46.04	16.08	29.83	34.93%	64.78%
2003	54.69	17.88	31.58	32.69%	57.74%
2004	67.68	19.407	40.60	28.67%	59.99%
2005	76.45	22.38	61.17	29.27%	80.01%
2006	87.72	25.05	73.16	28.56%	83.40%
2007	82.54	27.73	95.36	33.60%	115.53%
2008	49.51	28.05	67.52	56.66%	136.37%
2009	56.86	22.31	37.43	39.24%	65.82%
2010	83.77	23.12	55.53	27.60%	66.28%
2011	96.44	26.02	71.28	26.98%	73.91%
2012	96.82	30.44	75.90	31.44%	78.39%
2013	107.3	36.28	88.13	33.81%	82.13%
2014	113.01	39.44	101.98	34.90%	90.24%
2015	100.48	43.16	106.10	42.95%	105.59%
2016 (LTM)	98.61	43.88	110.62	44.50%	112.18%

In 2015, companies in the S&P 500 collectively returned 105.59% of their earnings as cash flows. While this would not be surprising in a recession year, where earnings are depressed, it is strikingly high in a good earnings year. Through the first two quarters of 2016, companies have continued the torrid pace of buybacks, with the percent of cash returned rising to 112.18%. The debate about whether these buybacks make sense or not will have to be reserved for another post, but what is not debatable is this. Unless earnings show a dramatic growth (and there is no reason to believe that they will), companies will start revving down (or be forced to) their buyback engines and that will put the market under pressure. (For those of you who track my implied equity risk premium estimates, it was this concern about cash flow sustainability that led me to add the option of allowing cash flow payouts to adjust to sustainable levels in the long term).

So, how do these worries play out in my portfolio? They don’t explicitly but they do implicitly affect my investment choices. I cannot do much about interest rates, other than react, and I will stay ready, especially if inflation pressures push up rates and the fixed income market offers me a better payoff. With earnings and cash flows, there may be concerns at the market level, but I bet on individual companies, not markets. With those companies, I can do my due diligence to make sure that they have the operating cash flows (not just dividends or buybacks) to justify their valuations. If that sounds like a pitch for intrinsic valuation, are you surprised?

The Market Timing Mirage

Will there be a market correction? Of course! When it does happen, don't be surprised to see a wave of “I told you so” coming from the bubblers. A clock that is stuck at 12 o'clock will be right twice every day and I would urge you to judge these market timers, not on their correction calls, which will look prescient, but on their overall record. Many of them, after all, have been suggesting that you stay out of stocks for the last five years or longer and it would have to be a large correction for you to make back what you lost from staying on the sidelines. Some of these pundits will be crowned as great market timers by the financial press and they will acquire followers. I hope that I don’t sound like a Cassandra but this much I know, from studying past history. Most of these great market timers usually get it right once, let that success get to their heads and proceed to let their hubris drive them to more and more extreme predictions in the next cycle. As an investor, my suggestion is that you save your money and your sanity by staying far away from market prognosticators.

YouTube


Datasets

1. PE ratios from 1960-2016
2. Shiller CAPE and T.Bond PE (1960-2016)
3. S&P 500: Earnings, Dividends and Buybacks (2000-2016)
4. CAPE Market Timing Test

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