Demystifying Beta

It has often been said that “the market loves certainty.”  Most investors (excluding those who seek to capitalize on volatility) would love it if stocks grew in a nice, linear way that was easy to predict and explain.  Alas, stocks don’t do that. They grow in an up and down pattern that is reminiscent of an EKG readout. All that up and down movement overwhelms the brain, and makes it hard to figure out what is going on over the long run.  Since we can’t get stocks to grow in value as a nice, elegant linear function, we tend to look at trends.   

On graphs, we can often use lines to show what the trend of a particular stock’s value is over time.  One particular method of doing this is a statistical technique called linear regression.  It essentially takes the average of all the ups and downs and draws a line based on those averages.   You could do the same thing with a ruler by “eyeballing it,” but the results wouldn’t be as precise as the trend line and associated equation that is mathematically generated by a computer.  

That last line may have made you cringe a little; I used the words “mathematically” and “equation” in the same sentence.  If you had flashbacks to your high school algebra class, I apologize. But you needn’t be afraid; all of the math is done by computers these days.  All you need to remember from algebra class is that equations can be shown as a line on a graph. Regression analysis capitalizes on this idea in predicting the average movement of data points (stock prices) that don’t move in a nice, straight line like those homework problems from algebra class.  Regression analysis has gotten a bad reputation because of its association with math. Try to forget that; regression is a very useful tool for the investor. All the hard work is done behind the scenes. All you have to do is interpret the results. There are very easy rules of thumbs for interpreting that information.  Feel free to write those down; this isn’t algebra class, and you can’t get in trouble for cheating.

If you were to ask an economist, she would probably say something like “a particular stock’s beta is calculated by dividing the covariance the stock’s returns and the returns of a specified benchmark by the variance of the benchmark’s returns over a specified period.”  My guess is that you didn’t find that very helpful. Let me break it down for you; it’s an easy concept to grasp once we translate the statistical jargon into trader jargon. When we measure anything (such as a stock price) over time and we get different results, we call that thing a variable as opposed to a constant.  Stocks are certainly variable!  

That movement of the measurement from value to value is called variation.  Statisticians measure this variability with a number called variance (closely related to standard deviation).  Simply put, variance is a particular statistic that measures the variation in something that varies, such as a stock price.  In the case of stock prices, low variability (as measured by variance) means that the stock’s price doesn’t move much. A high variance means that the stock’s price is bouncing around all over the place.  Traders don’t often use the word variability; they talk about the amount of movement in a stock’s price in terms of volatility.  It may not be precise, but you will probably be okay thinking of variance as a measure of volatility.

Enter the idea of covariance.  As you’d expect, “co” is a prefix meaning “together.”  So the idea of covariation is the idea that two measurements will vary together and, if we generate a scatterplot, the dots will form a line.  For example, we’d expect a high degree of covariance between a stock’s market price and its price to earnings ratio. If the PE ratio was the only factor in determining stock prices, then all of the dots would fall on the line perfectly.  Statisticians would refer to this is a bivariate (meaning two variables) problem, because there are only two variables being considered.

Stock prices are a multivariate (meaning many variables) problem. There are dozens of potential factors that influence stock prices, and only some of them are quantifiable (If this weren’t the case, I could come up with an equation to model future growth and have retired already).  Note that the idea of covariance is conceptually identical to the idea of correlation.  

So, the big idea of regression analysis is to demonstrate as precisely as possible how two things systematically vary together.  We can apply this idea to see how much the variability (volatility) of a particular stock matches the variability (volatility) of a benchmark.  That is what Beta is. While any benchmark can be plugged into the equation, most often the variance of the S&P 500 is used with stock prices. Beta, then, is just a ratio of the volatility of a particular stock and the volatility of the S&P 500.  The math tweaks (standardizes) the results for easy interpretation. A Beta of 1.0 indicates that the particular stock you are evaluating moves precisely with the benchmark—it goes up and down exactly as does the S&P 500. A Beta less than 1.0 suggests that (at least in the past) the stock was less volatile than the S&P.  A Beta above 1.0 suggest that the stock is more volatile than the S&P.

Consider the idea that volatility is only a bad thing when it goes against the way you bet. If you are long in a stock, and it shoots past the S&P 500 average, then you picked an awesome stock! If it, however, plummets below the level of the S&P 500, then you are a much bigger loser than the overall market.  Beta assesses volatility objectively. What you ultimately decide to do with that information depends on how risk averse you are. Super conservative investors that are willing to tolerate very little risk will look for stocks with a Beta less than one, such as many utility stocks (often referred to as bond market equivalent stocks).

For example, as of this writing, the Beta for Procter & Gamble Co. (PG) is 0.6. Risk takers seeking big rewards will often look for stocks with a high Beta and the accompanying possibility of big returns—and huge losses.  Note that Beta is neutral as to evaluating great returns or terrible returns. As of this writing, the Beta for Goldman Sachs Group Inc. (GS) is 1.6. Owners of GS are springing for the good stuff this Christmas! Apple Inc. (AAPL), on the other hand, has a Beta of 1.3 and that volatility is unwelcome by investors.

To really get any useful information from Beta, there must be a correlation between the stock you are evaluating and the benchmark used in the computations.  To evaluate this, we can turn to another byproduct of regression analysis known lovingly by economists as R-squared. Think of R-squared as a percentage of covariation.  The closer to 100 you get, the more the stock traces the benchmark’s performance. The closer to zero you get, the less correlation there is between your stock and the benchmark.

More advanced measures have been developed since the advent of computer technology, such as the Sharpe Ratio. The bottom line is that Beta and other measures of volatility are useful tools (among many) that you can use to help you pick a stock that meets your investment needs and form realistic appraisals of how high it can go, and how low it can sink.


Demystifying Market Corrections

When the market starts trending down, many investors tend to panic.  They see volatility as dangerous and formulate a belief that the market is just not for them.  These panicked investors perceive the correction as something wrong with the market as a whole and lose sight of the fact that for every stock listed, there is a company behind it.  Veteran investors have come to expect these periodic “corrections” to what can be considered inflated prices. Corrections happen all the time. After “big runs,” you should anticipate them.  It is a terrible mistake to pull out of the market when they happen.

Jim Cramer teaches that a particularly profitable strategy for dealing with corrections is to avoid the trap of being 100% invested in the market at all times.  At times when the market is tanking, cash that makes nearly nothing can look like a great investment. As Cramer put it, “Nothing feels as good as cash when the market is coming down.”  This is actually a critical element of his axiom of “selling strength and buying weakness.” When the market is surging upwards, the strategy dictates that you “trim” here and there to generate cash to be in a position to buy during the next correction.  

If you don’t do this trimming and hold on, you may fall into the trap of selling your winners to subsidize your losers. This naïve practice can wreck a portfolio by filling it with junk because all of the blue chips have been sold off. When you realize that a stock is junk, then sell it and take the loss.  Use what’s left to reposition into something great. The real key to all of this is to differentiate between bad companies with deteriorating fundamentals and good companies with deteriorating stock prices.

Don’t forget that companies with good bottom lines can go bad because of larger forces that are outside of management’s control.  Geopolitics, exchange rates, fed policy, and a host of other factors can make cause a once great company to lose traction. Don’t let your emotions get in the way of making rational decisions based on shifting fundamentals.  In a slowing economy, for example, you may see a consumer shift from premium brands to store brands that can hurt the bottom line of once great premium product companies. Drug companies that have been making fortunes for years can suddenly see their bottom line drop out of sight when a family of important drugs goes off patent.  If you confuse the shifting fundamentals with a market correction and buy more while the stock is “on sale”, you can lose big.

If your portfolio is composed of great companies with great fundamentals, don’t fear the market corrections.  Those great stocks will bounce back, ready to ride the next upturn.

Demystifying Market Sectors

With all of the hoopla over various stock indices, it is sometimes easy to forget that the stock market is a market for individual stocks and not a singular entity that eats fortunes.  These stocks are not merely little pieces of paper (or the digital equivalent); they represent discrete pieces of ownership in living, breathing companies. These companies, taken collectively, do everything under the sun for which people will pay money.  Some stocks represent banks and other financial companies. Some stocks represent restaurants. Some represent clothing stores. Some represent mining, and some represent drilling for oil. When investment experts talk about sectors, they are talking about groups of stocks that have underlying businesses engaged in the same sort of income generating activities.

Because these companies do the same basic thing, they are subject to similar economic forces.   Sectors tend to rise together when economic conditions are good for those types of companies and fall together when economic conditions are bad.  For the investor, this means that poor sector performance can mean poor portfolio performance if you are not diversified across not only different stocks but different sectors of stocks.  Take the financial sector for example. If interest rates are on the rise and all of your investments are in bank stocks, then your whole portfolio will likely rise. If interest rates are cut, then your whole portfolio stands to plummet.  For the individual investor, the best advice is probably to buy the best of breed stocks across as many different sectors as you can.

In the United States, the most common system that you will see for sector classifications is the one used by Nasdaq.   Nasdaq uses the ICB (Industry Classification Benchmark) which is maintained by the FTSE Group. This system uses a hierarchical approach in which there are ten “industries” at the topmost level, 19 “supersectors” below that, and 41 “sectors” below that, and the fourth level with 114 “subsectors.” (You can download an Excel spreadsheet of this information from  http://www.icbenchmark.com/structure)  Be aware that these sector classifications may change depending on which information service you use.  When I look up the symbol TST on TD Ameritrade, it tells me that it is classified as “Financials: Capital Markets.”  When I look it up on Yahoo! Finance, I find that it is classified as being in the “Internet Information Providers” industry and in the “Technology” Sector.

There are several indices and ETF (Exchange Traded Funds) that are sector based, allowing you to invest across a wide swath of stocks in a particular sector.  The sector ETFs are like broader index funds that only provide exposure to one sector rather than the entire market. Understanding a particular sector is important when picking stocks.  Different businesses measure success in different ways, and if you don’t know how to tell if a particular breed of business is successful, you obviously shouldn’t speculate in that sector’s stocks.  

A great way to find information about investing in a particular sector is to read the research done by high-quality research and investment firms, and of course by following the sector on TheStreet. Always remember that the fortunes of individual stocks are tied to sector evaluations, largely because of these behemoth sector funds.  Perfectly solid companies with a stellar trajectory can take a huge hit if investors (especially the big institutional ones) dump the entire sector, just as they can when there is an overall market decline like the Great Recession. If you have done your homework, evaluated the fundamentals, and have conviction about the company’s story, then sector selloffs present an important buying opportunity.

Demystifying Price Targets

One of the most important predictors of short-term stock prices is the backing of market analysts in the form of buy, sell, and hold ratings.  Many analysts include a price target in their reports on particular stocks. These target prices are merely an analyst’s best guess as to the future price that a stock will reach.  Your online brokerage account will usually link to several such reports. It is important to realize that different analysts determine price targets in different ways. Some are purely quantitative and use regression analysis and other more advanced empirical techniques to predict future prices.  

An important consideration when considering price targets is the timeframe that the analyst is using.  Most analysts are not catering to the day trader; they are usually looking at least a year into the future.  Most analysts will use some form of value approach where the earnings and growth of the underlying company are the critical factors.  This means that sector fluctuations, overall market conditions, and market sentiment are not factored into the price model. If a particular stock rises to the analyst’s target, it will usually have many ups and downs before it gets there.  

Many investment experts agree that a buy and hold strategy is not a smart investment strategy.  Even the greatest companies wane over time. You have to keep an eye on the fundamentals of the stocks you own.  Price targets provide one method of helping you determine when a company may have reached its zenith and your portfolio would be better served by taking profit and reinvesting in a stock that still has “room to run.”  Note that price targets are often updated by the analysts, and analysts may not update a price target as quickly as they perhaps should. When a stock reaches its current price target, then it should be evaluated as a possible sell.

Value investors will seek to identify companies that are selling at a price that is too low given the fundamentals of the underlying company.  Analysts trying to establish price targets must make predictions based on past performance and future potential. Some of the most commonly cited factors that influence a stock’s valuation include its expected growth rate, dividend yield, and financial health.  The idea of “earnings visibility” often comes into play. Earnings visibility refers to the likelihood that projections about a company’s numbers are correct. Factors that make the analyst’s crystal ball cloudy, such as regulatory uncertainty, hamper earning visibility.  Older companies that have weathered economic downturns are often regarded as safer bets based on this idea of visibility.

Many analysts also include whether or not a company pays a dividend when evaluating the market value of a stock.  As you would expect, when all else is equal a company that pays a dividend should trade at a premium to a company that pays no dividend.  Dividends provide investors with tangible growth. Some companies have such a long history of paying stable dividends that they are considered to be the equity market equivalent to bonds.  Proctor and Gamble is the quintessential example of such a stalwart company.

A company’s financial profile must be considered when valuing a stock. Earnings and earnings growth only tell part of the story.  The best of breed companies will have a high return on equity and a high return on invested capital. They will also have good “margins,” which are the proportion of income that’s left over after all of the bills are paid.  The adage that “you have to spend money to make money” is true. Great companies have mastered the art of turning cash into even more cash. Some companies have to spend huge sums to generate cash, and the market punishes companies that have a track record of doing this.

This brief overview of how price targets are set demonstrates that setting price targets is as much art as science.  The simple truth is that even the best analysts get it wrong sometimes. This is an important reason that you must be diligent and do your homework.  You have to know the fundamentals of the companies that underlie your stock picks, and you must project those fundamentals into the future based on a comprehensive knowledge of what the company is doing.  Qualitative information about a company is often critically important, and cannot be boiled down into a single number that plugs into a formula.


Demystifying the Financials Sector

Stock market analysts often worry about market volatility, which is jargon for a rapid cycling of upward and downward trends in a particular stock, sector, or index. Some intrepid traders use this sort of volatility to capitalize on very quick downturns to buy and quick upturns to sell. This strategy is considered very dangerous and full of risk by most long-term investors. They view it as something akin to playing roulette.

Many day trading strategies exist to help these brave traders make these volatility based plays. The long-term investors hate volatility because it makes the market less certain and picking stocks more difficult. As you may have predicted, the financial services sector is prone to high levels of volatility. The reason that everyone doesn’t avoid high volatility stocks and stock sectors? Great risk often equates with great reward in the stock game.

If a company is in the business of handling other people’s money, then it likely fits into the financial industry. Banks, insurance companies, real estate companies, and financial service companies are the major supersectors in this industry. To get an understanding of exactly what makes stocks rise and fall in this industry, you must have a grip on each of the subsectors.

As a general rule, financials perform best in a low-interest rate environment, but that statement must be qualified. The value of long-term debt such as mortgages is higher when interest rates are lower. In periods of low-interest rate mortgages (and other long-term debt), the general rule will not hold. The complex interaction of current interest rates and long-term interest rates are part of what makes this sector so potentially volatile.

When the business cycle is on the upswing, and there is a high level of confidence in the economy, both individuals and businesses seek to expand wealth. This is often accomplished through growth, which means that these individuals and corporations need financing. Businesses build and replace infrastructure, and individuals increase personal savings and investing.

These are heady days to be invested in the financial sector! Financials make up a large portion of the S&P 500, consisting of household names like Bank of America, Citigroup, and JP Morgan Chase. If you were invested in these financials at the beginning of the Trump Rally, you fared very well! (See a chart for November through December of 2016 for Goldman Sachs Group Inc. (GS) if you are a visual learner). Investors can’t afford to become complacent given these meteoric rises in equity. Never forget the devastating losses to this sector when the real estate bubble burst in 2008.
Several investors use the Financial Select Sector SPDR ETF (XLF) to track the overall health of this sector.

The volatility of that index has been quite low over the past three years (Beta = 0.93), debunking the notion that financials is a volatile sector that should be avoided by prudent investors. History teaches us that the sector’s volatility can, however, increase dramatically during uncertain economic times. In this sector, the prudent investor will shy away from a “buy and hold” strategy. The correct strategy is to follow the advice of Mr. Cramer: “Buy and Homework.” That homework must include drilling deep into the underlying business and inspecting the balance sheets before you pull the trigger. It also means tracking the larger economy, with a special emphasis on what the Fed is doing with interest rates.


Demystifying the Oil and Gas Sector

As with most of the industries and sectors that stock investors may seek to invest in, the oil and gas sector is often intimidating because of the massive amount of jargon that is involved.  Another layer of complexity is added by the global nature of the oil market and the political nature of international relations in historically volatile regions. It is important to realize that oil and gas are commodities.  Supply and demand economics rules commodity prices. When there is a surplus of oil or gas, prices tend to go down. When demand is high, and supply is too low to meet it, then prices climb sharply. These fluctuations in commodity prices have an enormous impact on the bottom line of companies in this sector.  

Oil and gas are sometimes referred to as hydrocarbons because of their shared chemistry.  They are commonly referred to as “fossil fuels” because of the way they originated. The basic idea is that ancient plant and animal life were covered over by sediment, and this sediment later formed into rock.  Add a few million years, and presto: you get natural gas and crude oil. The first thing this tells us is that oil deposits are hard to find because they are in the ground, buried under hundreds or thousands of feet of rock.  In the case of offshore deposits, you can’t even get to the rocks without going through hundreds of feet of water. The sector that is most closely associated with finding the oil and gas in the first place is usually called exploration.   This exploration and production end of things are dangerous; if the geologists get it wrong and the hole is dry, then many millions of dollars have been wasted.  Many of these companies take the raw commodities out of the ground and turn them into the useful products, such as gasoline, that people want to buy; this is most often referred to as refining.  Some companies get involved in the retail and distribution end of oil and gas as well, and these companies are usually classified in the “Integrated Oil and Gas” sector.  

Another important sector in the oil industry is the “Oil Equipment, Services, and Distribution” sector.  Getting millions and millions of gallons of oil and natural gas refined and to retail markets is a massive undertaking.  Many companies provide tools, equipment, chemicals and so forth to the oil exploration and production companies. E&P companies often farm out the actual drilling of the wells to drilling companies.  Drilling companies earn profits based on contracts and are not tied directly to the price of oil as are the E&P companies. Most such companies get lumped together into the “Oil Equipment and Services” subsector, but “Pipelines” are such a big deal that they get a subsector designation.

Most of the companies that explore for oil and gas also drill down to find it and bring it to the surface, a process called production.  Exploration and Production (E&P) company stocks sell at a premium when oil prices are high, and tend to sell at a discount when oil prices are low.  The balance sheets of these companies are composed of line items directly related to drilling for oil and gas and getting it out of the ground once it is found.  This means that investors in this sector must be familiar with the terminology and jargon of E&P as part of their homework on investing in the “oil patch.” As with any commodity, profits are made by volume of sales.  Wheat and corn sell by the bushel, and oil sells by the barrel (42 U.S. Gallons). Natural gas, on the other hand, is sold by the Cubic Foot (at a standard temperature and pressure).

Another important set of jargon you need to understand before investing in the oil patch is the difference between upstream, midstream, and downstream.  The term “upstream” is used to refer to the source of the oil or gas; the E&P side of things. The midstream is focused on storage and transportation. Finally, the downstream side refers to the refining and distribution of refined products.  For example, a drilling rig in Alaska would represent an “upstream” activity. The transportation of the oil from that well via a pipeline would be midstream activity. The refining and sale of gasoline would be downstream activity. These distinctions are important because they provide different potential risks and rewards for the investor.       

Just as with any other company, the value of an E&P company stock is directly related to its predicted future earning capacity.  These companies have a finite amount of oil or gas that they can pull out of the ground given all of the wells they have currently producing.  These still in the ground reservoirs are key to the valuation of E&P companies. Oil companies must always be exploring for new reserves or face bankruptcy.  Note that reserves in the oil patch are different than a company’s expected earnings.

Curiously, oil patch investors pay close attention to the “netback.” or profit per barrel of a particular production operation.  That is what it costs to get a barrel of oil to the retail market is subtracted from what the products sold for. Companies with a higher netback tend to sell at a premium while companies with a low netback tend to sell at a discount.  Netback rises when costs can be cut at any point from initial exploration to the final sale at the gas pump. These factors have historically been very predictable, with the American oil industry suffering when the sale price of a barrel of oil was low.  If it takes an American company $75 to get a barrel of oil to market and the price of oil is at $50, then obviously these companies cannot be profitable on the domestic side of the business.

Technology has already played a major role in improving the viability of American E&P companies.  We have become better at finding oil and gas, we’ve gotten better at getting it out of the ground, and we’ve become more economical at getting it to market.  When American E&P CEOs are telling investors that they can make a comfortable profit in the $45 per barrel range and oil is selling at $50, then it is a potentially exciting time for investors.

Note that the “Oil and Gas” industry would probably have been better named the “Energy” sector, and that’s what a lot of investors call it.  One reason for this is the fact that the “Alternative Energy” sector is within the “Oil and Gas” sector, creating an oxymoron. When we talk about “Alternative Energy” we are talking about alternatives to oil and gas.  The two major subsectors in this sector are “Renewable Energy Equipment” and “Alternative Fuels.”

Most companies tied to solar and wind will be tied to the equipment subsector, and oil and gas alternatives such as ethanol and fuel cells will be tied to the fuels subsector.  Most of the companies in this sector are very speculative and not suitable for the long-term value investor. So long as crude is selling for $50 or less, then the alternative sector has a long way to go before it can become broadly competitive. During periods of “environmentally friendly” politics and policy, government incentives make this sector seem more attractive.  During periods of pro-business policy and deregulation, oil and gas will be king, at least for the foreseeable future.


Demystifying “You Can’t Beat the Market”

As you know, economists are scientific types that study how money flows and grows. They study many different aspects of this very broad concept, including how stock market prices behave. Being scientific types, they love to develop theories that explain many different “phenomena.” One particularly important theory that has been the foundation of America’s retirement strategy since the invention of the 401K is the Efficient Market Hypothesis (EMH).

In its simplest form, the theory holds that the price that stocks sell for factors in all available information, and thus no trader can have any real advantage over the other. The idea of efficiency comes into play because the market has already priced each stock given all of the relevant information. If stocks are priced to reflect this efficiency, then it is impossible to pick undervalued stocks to buy and overvalued stocks to sell because those things cannot exist in an efficient market.

This translates into the following investment advice: Stick all of your money into a low-cost mutual fund that reflects the entire market and hope that the overall economy grows. This is the strategy that many 401K “experts” dole out to folks hoping to have enough money to retire one day. Put some in an Index Fund, put some in bonds, and put some in annuities, then wait for retirement. Any scientist (I classify economics as a social science) will tell you that it is much easier to disprove a theory than it is to prove one.

To disprove a theory, all you need are some examples of it not working. The EMH doesn’t hold up in the face of short-term performance legends like Jim Cramer. It doesn’t hold up well in the long run when we consider the mind-boggling success of the long-term value plays of Warren Buffet. Unless you believe that Mr. Cramer and Mr. Buffet are magical creatures, then you must reject the EMH as an absolute law of economics.

In fairness to the supporters of the EMH, it must be acknowledged that any randomly selected portfolio has a very small chance of beating the market by a substantial margin. The laws of probability are clear on that one. Any fund managers that beat the market for a quarter or even a year may well have random chance to thank for their success. In everyday language, this probabilistic growth would be a case of “getting lucky.” Another law of probability tells us that improbable events occurring in a long series become very, very improbable.

Take poker as an example. If we are playing and you get a full house, I’ll say that you got lucky. If you get a full house twenty times in a row, I’ll say you are cheating because that happening by chance is just too improbable—nobody is that lucky. When I look at the careers of great investors like Jim Cramer, Warren Buffet, and Peter Lynch, I must reject the efficient market hypothesis. There are other lines of attack on the theory, such as the impossibility of a “market correction” if the hypothesis is true, but I hope I’ve made my point.

My ultimate conclusion is that you can indeed perform better than the overall market. I would be remiss if I didn’t point out that doing so is not easy. While I’ve argued against the EMH, I will say that it is mostly accurate most of the time. Most stocks do trade right around where they should. Finding an undervalued stock is wonderfully hard work. Identifying a catalyst that will send it upward is more work still. Even so, with a little luck and a lot of homework, you can beat the market.


What’s Wrong with My Savings Account?

For the sake of argument, let’s say you have $1000 in your bank savings account.  Let’s further assume that your money is earning 1.00% Interest. As crazy as it may seem, that is a good rate for a savings account in the 2017 market.  Interest rates for savings accounts are at rock bottom. We’ll use this meager return as an example of why the Magic of Compounding Interest is both impressive and desirable.

How The Magic Works

In a simple world where math is infrequent and universally disdained, you would simply let your money sit in the savings account, and, at the end of the year, the bank would deposit $10 interest into your account.  In that simple case, you would then have $1,010 in your savings account. In that scenario, your gains are due to simple interest, which the bank only pays on the principal (your original $1000). The mathematical complexity arises when we consider that banks usually don’t work like that.  More often than not, you make money on your principal as well as on the interest that you have already earned. That is what Jim Cramer would call a “high-quality problem!”

When banks pay interest on the principal plus the interest already earned, we call it compounding.  When choosing an account, it is important to know how often the bank compounds the interest.  As a general rule, the more frequently the bank compounds your interest, the faster your money will grow.  Some banks compound daily, while others do so monthly or quarterly. Obviously, I’d prefer my money to make me money every day and not just once per month or once per quarter.  Note that this works against you when you hold credit card debt; most credit card companies compound what you owe them daily. In the case of daily compounding, your money will earn 1/365th of the 1% annual rate each day you leave it alone and let it grown.  This quirky calendar may sound like a small detail, but over a ten year period, daily compounding can add about 10% more profit than you would earn with simple interest.

Savings Accounts are Terrible Investments

At the end of 10 years, then, your $1,000 investment would grow to an immense value of $1,105.17 with compound interest. Even with the miracle of compounding interest, that is still depressing.  There are two lessons here. The first may not be so obvious: Compounding interest is amazing, and you want every dime you can get invested so it can contribute to the compounding process that will make you wealthy.  The second lesson is that 1% is a terrible rate of return, and you will never grow rich tucking your money away in a bank savings account.

In reality, the only reason to use a savings account is the psychological barrier it places between you and your money.  Most people have trouble letting cash sit in a checking account without dipping into it. You absolutely must have an emergency fund that you will not touch except in a bona fide emergency, and most of us have the discipline not to rob our emergency fund if it is walled off from our ATM card by a savings account.  Why do we not invest it in equities so it can compound? The reason is what money managers call liquidity. You need your emergency fund hidden away psychologically so that you do not raid it, but you need to be able to access the cash quickly when an emergency arises. If your money is in your investment account, the market may be down, or it may take several days to transfer the money into your savings account.


Securities to Buy Ahead of an Economic Downturn

A growing list of prestigious individuals and financial houses are telling investors that a downturn is coming.  The market is still very bullish, but Ray Dalio and Professor Shiller point out that what goes up must come down, and they warn of a downturn in the next couple of years.  There are several strategies that investors can employ in the face of such a downturn. One is to hold the lions share of your portfolio in cash. Cash isn’t making any money, and most investors don’t feel comfortable with a potential two year period of flat returns.

Another is to invest in companies and sectors that are likely to do well if such a downturn strikes.  Bank of America, for example, is very bullish on gold. The bottom is in, and the risk curve is asymmetrical.  They’ve put a $1350 price target on gold for 2019. That’s about a 12% upside, and leveraged funds ($NUGT) can potentially double that return.  There is the strong possibility that crude oil will make advances as geopolitical tensions, sanctions, and a stubborn OPEC continue to hold sway. You can bet on crude with $OIL, and you can make leveraged bets with $UWT.

Individual stocks with very low multiples stand to weather the storm far better than those that have stretched multiples.  Symantec ($SYMC), AT&T ($T), and Micron ($MU) seem to fit the bill.

Perhaps the most dangerous position–in the short term–is to be long the major indices.  Long-term index investors will plan to stay the course by staying long and keep buying through any downturn.  I have no doubt that long-term value investors such as Warren Buffett will relish all of the discounted stocks that will be available in a widespread selloff.  My fear for the average retail investor is that panic will set in, and they will have bought high and sold low–an age-old recipe for disaster. Many of today’s investors have never traded in a severe bear market, and many will have no idea what to do when momentum reverses.  You will be fine if you change your allocations to a safety portfolio, and you will be fine if you just ride it out as Mr. Buffett and Mr. Boggle will do. You can be badly hurt if you are a panicked seller of damaged securities. The best advice is to strategize now, develop a plan, and stick to the plan when things get scary.


Is the Exuberance Irrational?

A guest on CNBC’s Power Lunch today (09/18/2018) argued that this phase of the bull market is different than similar past markets of a certain age was that this time “there is no irrational exuberance.” I take issue with that assertion. Nio, a Chinese electric car maker, IPOed at $6.00 and went up over 100% in the space of a couple of days. This despite analysts starting the stock with a sell rating and a price target below the IPO price. New rounds of tariffs on around $200 Billion in Chinese goods were levied by the president, and the DJI rose nearly a full percent the next day. The media seems to have forgotten that we already have tariffs on several of our allies from earlier in the President’s term. Tariffs are by definition inflationary, and they disincentivize consumer spending and investing.

The Fed is hiking rates, and bonds have hit the 3% level once again. The dollar keeps strengthening much to the chagrin of gold investors. One official stated that China “was out of bullets” in the trade war since they didn’t have much else that they could put tariffs on. This ignores the several nuclear options, such as dumping billions in US bonds and devaluing the Yuan such that the tariffs don’t really harm Chinese businesses and consumers. This will would have a domino effect, and many world currencies would lose strength. That would, in turn, cause the dollar to strengthen even more. These are all headwinds to corporate earnings, and tailwinds have already been priced into the market. Many investors have adjusted their portfolios to reflect some risk aversion, but holding 5% cash while bidding up the S&P 500 to insane levels does not reflect real caution.

The venerable Professor Schiller of Yale (the economist who coined the phrase “irrational exuberance”) has pointed out on several occasions that the CAPE ratio (currently at 33.27) is very high compared to the average (mean = 16.57). To get a feel for what that looks like visually, examine the chart below:

The blue line represents Professor Shiller’s inflation-adjusted P/E ratio (CAPE) over 138 years. The vertical hatch marks represent 2.58 standard deviations above the mean, which means that any part of the blue line sticking up above those hatch marks represents a very high and statistically unlikely level for the CAPE. About 99% of the time, multiples have been lower. As we can see from the chart, only the Dot-com Bubble era had a higher degree of irrational exuberance than we do today. In absolute terms, P/E ratios may seem reasonable (only 16x next years projected earnings), but when we examine them in the historical context on a cyclically adjusted basis, we see a different picture emerge. We’re just a few bullish days away from rejoining the illustrious 1% club of ridiculously stretched multiples. “Things aren’t as silly as they were during the Dot-com Bubble” is no evidence that we are not overextended now.

Interestingly, the period of the dot-com bubble had a mean CAPE of around 30. That means that average CAPE, even including the big crash, was higher than most of even the extreme scores of all other periods. If we look at the CAPE where the market bottomed out in 2003, we can see that multiples were only slightly stretched. It was still high in reference to the historical average. Logic dictates that when values are more than double the historical average, a 50% downturn results in values that are near the historical average. Market performance during the dot-com bubble was far more irrational than in any other period.

Most other bull markets followed a very similar trend. Multiples climbed high above the mean and then fell back through the mean. What makes the dot-com bubble so spectacular was the height of the mean during the time, and not the pattern of rising and falling. In the chart for the Great Depression, we can see that a boom period was followed by a rapid downward move that lasted nearly four years.

When World War II ended, euphoria was the norm, and the thrill of victory swept the nation.  Thousands and thousands of returning soldiers wanted to start families and live the American Dream.  A year after the War had ended, the economic reality of massive spending and massive destruction started to hit home, and equity values slipped.  The mean CAPE of the period was already lower than the historical averaged, that translated into a gentle drift downward in contrast to the massive and protracted sell-off of the Great Depression.  

The early sixties was a period of social turmoil inside the United States, and it was filled with Cold War intrigue and geopolitical risk.  The Bay of Pigs Invasion and the nuclear fears of the time were on the minds of all Americans, including investors.

The end of the 1960s saw a resurgence of social upheaval, and the civil rights movement was at its zenith.

Energy is the lifeblood of the economy, or at least it as in the early 1960s. Conflict in the Middle East followed by an Arab Oil Embargo did massive damage to Western economies between 1973 through 1975. In this case, the mean of the period was near the historical average and the high point in 1973 wasn’t all that stretched. The downturn would take multiples well below the historical average.

1980 to 1982 marked a time of fiscal nightmares for the government and people of the United States. The end of the Carter administration saw very high inflation, very high interest rates, and very slow growth. The bear market ended with the election of Ronald Reagan, after which the market took off with a vengeance.

Black Monday is rare in that a single day was the focus of a shockingly fast decline in the markets. The DJI shed 26.6% on that one day. Overall, the bear market lasted only three months, but the S&P 500 shed 33.5% during that short period. This chart is very instructive since it serves as a good example of the range of multiples (inflation adjusted) that stocks usually trade within.

The financial crisis happened during the middle of an elevated period of market valuations and multiples. Investors were euphoric, and the Wall Street bankers had gone insane and took on an appalling level of risk. Euphoric borrowers applied for the biggest mortgages that they could get, and underregulated banks handed out huge checks to borrowers that didn’t have a prayer of paying them back. Real estate markets were on fire, and the wisdom of the day was that property values would appreciate so fast that leverage and a positive attitude were all you needed to get rich. That worked well until 2007 when uneducated mortgage borrowers owed bankers focused on short-term profits, and that influx of risk caused the bankers to sell off that risk with financial instruments that they little understood.

From the above charts and commentary, we can see a pattern in how bull markets die.  While the nominal cause of the downturn varies, we usually find geopolitical risks, fiscal risks related to credit cycles and tax structures, and domestic strife in the list of hypothetical causes.  We also find some fairly predictable numerical patterns. The idea of “reversion to the mean”, also known as regression, always seems to be in play.

Any time the CAPE is below the mean of 16.5, we can invest knowing that the odds are very good that markets will move upward.  About two-thirds of the time, CAPE ratios will move between 10 and 23. When we get outside of those ranges, we can expect a move back toward the mean.  When scores become very distant from the mean, the tendency is to return to the mean in short order.

Given the “sideways price action” of recent weeks, it seems that investors are worried about trade wars and other geopolitical risks. They are worried about stretched multiples, but not so worried as to get out of the high flying stocks that have kept the bull market alive for this long. Given the level of the CAPE over its historical average and the lack of response to dangerous economic headwinds, I believe that we have enough evidence to call today’s level of exuberance irrational. The problem for more rational investors is that we have no way of knowing when the madness will end. History teaches us that the stretched multiples tend to snap back toward the mean like a massive rubber band–the further it gets from the point of origin, the more powerfully it snaps back. When a sufficient catalyst does occur to strike fear into the hearts of market revelers, the downfall will likely be as fast as it is dramatic.


Not familiar with the normal curve and where the percentages discussed above came from?  Check out my book chapter to learn more.