When demand for products drop, as they invariably do during recessions, firms do not simply hold their inventories stable. Firms instead cut inventories (keeping their sales to inventory ratio relatively stable), which amplifies the economic effect of reduced demand. Therefore, production is not just reduced by the actual drop in demand, but is further reduced by the desire to hold less inventory, which takes a huge bite out of GDP.
Incidentally, the opposite happens when demand increases: production is increased to a level higher than that of demand, resulting in a glut of product when demand starts to wane. We saw this process in action when we looked at the history of housing production, for example.
Here's a look at US manufacturing inventory over the last several decades, as compiled by the US Department of Commerce:
Notice that during economic down cycle years (e.g. early 80s, early 90s, early 2000s), inventories can be reduced by upwards of 10%. On the other hand, boom times result in tremendous inventory increases.
This chart takes us to Q3 of 2008. As demand continued to wane in the fourth quarter of 2008, companies have been focusing on cutting production and reducing costs. As such, it is likely we will see a large drop in inventories when we see look at chart again once data from Q4 of 2008 is included.
When you look at the balance sheets of the companies you are analyzing, take a look at their inventory levels and you will likely see this process taking place at a micro economic level.
When demand for products drop, as they invariably do during recessions, firms do not simply hold their inventories stable. Firms instead cut inventories (keeping their sales to inventory ratio relatively stable), which amplifies the economic effect of reduced demand. Therefore, production is not just reduced by the actual drop in demand, but is further reduced by the desire to hold less inventory, which takes a huge bite out of GDP.
Disagree with some of the government's decisions with respect to the bailout? The Bailout Game lets you chart your own course through this economic downturn. Banks and industries come to you for help, and you decide which ones are worth saving in order to help save the broader economy!
The authors have their own ideas of what the government should have done, and they will score you accordingly for each of your decisions. A wrong move on your part can destroy other companies, while a right move keeps the recession at bay.
This interactive tool is also a fun way to learn or re-visit some of the events of the last year that have put us in this position.
Play it here.
The following summary was written by Frank Voisin, who regularly writes for Frankly Speaking. Recently, Frank sold four restaurants and returned to school to complete a combined LLB/MBA.
Step 2 Analysis: In-Depth Analysis of Individual Companies
Now that you have a hit list of potential value plays, consider the following:
- Reasoning for Stock Price: Here, you try to determine why the company is trading a such low multiples. If the company has simply fallen out of favour with the market, that may present a great opportunity! If the company missed estimates, that is no problem, because those are short term and good companies will tend to focus long term. Consider historical growth and check whether the estimates it missed were its own or the street’s. If the company is doing poorly because it is heavily tied to the economy as a whole (e.g. homebuilding), that may be alright too, IF it can survive until the economy rebounds - consider the next thing in determining this:
- Debt: Look at your candidates and consider how much debt they have. The more debt they have, the less likely they can weather potential storms (or black swan events). Don’t invest if the company has a D/E ratio of greater than 0.5 (i.e. look for companies with at least twice the amount of equity as debt). Consider also the debt coverage ratio and interest-only coverage ratio. Compare all of these figures to other companies in the industry, to get an idea of how much debt the industry as a whole tends to hold. Also, remember to consider its pension liabilities!
- Liquidity: Consider its current ratio (Look for 2+ minimum), compare to its industry, and to the same company over time. What is the trend? Look for stable or increasing current ratios, or better than average for the industry. Consider its working capital - what is the trend over time? Consider also the Acid Test.
- Earnings: Compare the company’s sales trends, by division if possible. Compare to itself overtime, as well as the industry as a whole. Consider also the profit margin trends (You want the gross profit margin to be stable or increasing). Remove all extraordinary events (and be careful about what you call extraordinary. Is this company having extraordinary events every year? If so, they are ordinary!).
- Earnings Per Share: Look at the difference between diluted and undiluted. If diluted is significantly lower, this indicates that a potential purchase may not be as good as deal as you think, because if the company does improve, options will be exercised in which case your proportionate ownership will decrease.
- Product/Service: Compare this company’s product or service to its competitors. Is it obsolete? Does it do a poor job in its core products/services? If so, this will negatively affect its ability to operate in the future. Beware!
- Inventory: Has its inventory been increasing over time or stable? What are its revenue recognition policies (look for conservative policies, rather than fudged imaginary sales figures)?
- Value Funds: Check out Morningstar.com to see if any of the companies on your hit list are also held by value funds. This is a good indication that other investors are seeing value too. This is a double-edged sword though: If the stock IS held by other value funds, it may indicate the value no longer exists. If the stock IS NOT held by other value funds, it may have already been picked over and determined to not be the value it seems. Be careful to not let this be the sole determinant!
- Insiders: Buy when insiders buy (this is a strong indication of perceived value by those that know the most about the company) and watch for any sudden sell-offs. If there are sell-offs by insiders, look at what the reasoning is (e.g. Is it just one member selling, and is his daughter getting married?). Share buy-backs by the company are also good signs that the company thinks it is being undervalued (Consider whether the shares outstanding are declining)
Monster Worldwide (MWW) is best known for its monster.com website which matches employers and job seekers over the web. The company has grown quickly in the last decade, stealing share from traditional job placement advertisements and offering more efficient ways for employers and workers alike to find each other. But thanks to the economic slowdown, the stock now trades at a six year low, and sits at a P/E of just 9. But whether it represents a good long-term value investment comes down to the investor's circle of competence.
Before investing in any company, investors must understand competitive threats. In the case of Monster, this is not an easy task. In the high technology space, changes can occur very quickly, rendering business models obsolete. While right now Monster appears to have a solid share of the market, there are many possibilities that could change this in a hurry.
Will employers switch their allegiances to free sites like Craigslist? Will Hotjobs or other competing sites offer services at better value? Will new technologies make it easier for employers to recruit without Monster's help? Will a brand new competitor offer a new gimmick or a new way of matching seekers and employers that takes the industry by storm? Investors who are qualified to answer these questions and who believe Monster's competitive threats are benign may see value here. Investors who blindly invest in companies without understanding their competitive environments are destined to get burned every now and then.
For most high-tech companies, there is even more of a downside to not correctly anticipating competitive threats: there are no hard assets to fall back on. Monster is no exception. While many of the other companies we like have inventories or properties that can be sold even if the company's future viability should turn grim, Monster offers no such downside protection. Intangible assets represent 70% of MWW's book value; its price to tangible book is 4, whereas we're used to working with P/B's close to 1. Monster's inventory is just a concept, not an asset that can be converted to cash!
The company is certainly not going anywhere anytime soon. With ample cash of over $600 million versus just $250 million in total debt, along with its positive operating cash flow, Monster appears to have been discounted by the market. However, it is a long-term value investment suited only to those who have the expertise to determine if Monster can stay on top of its technological mountain.
While unemployment has been rising across the US in the last several months, we saw here that female workers have been able to hold onto their jobs with much more proficiency than their male counterparts. One labour group that has performed markedly worse than both of these groups are teenager workers. Here's a look at teenage unemployment compared to national unemployment:
With their limited experience and skills, teenagers command much lower salaries than their adult counterparts. So shouldn't companies be more willing to hire this group during recessions, as they shed their more expensive workers? Not so much, and the reason comes down to the artificial wage rate for teenage workers.
For adult workers, wages are mostly set by the market. That is, employers and employees agree to a rate based on their available alternatives, with little in the way of government intervention. However, for workers with little skill and experience, a category in which most teenagers fall, it's minimum wage that sets the cost of labour. Since the cost of this labour is higher than what the market would set it at, demand for teenage workers is kept artificially low. (For a more detailed explanation of this phenomenon, see this article.)
So is the solution to this problem abolishing minimum wage? This will almost certainly increase the number of employed workers, but will also reduce wages for many. For a discussion on the effects of removing the minimum wage, see here.
Bernard Madoff has been charged with perpetrating what might be the largest investment fraud ever committed. Investors may have lost up to $50 billion in the now outed ponzi scheme previously known as Bernard L. Madoff Investment Securities LLC. But in 2007, Madoff made the following comments, which are shocking in retrospect:
Considering the regulators appear to have missed quite a bit when it came to this firm, for Madoff to say that it is impossible to violate the rules is truly astounding! As more information about this case becomes available, it will be interesting to see what exactly went wrong with respect to oversight. For those interested in seeing some of the firm's red flags, Wikipedia has a terrific article detailing the findings to date.
The following summary was written by Frank Voisin, who regularly writes for Frankly Speaking. Recently, Frank sold four restaurants and returned to school to complete a combined LLB/MBA.I recently had an opportunity to read Christopher Browne and Roger Lowenstein’s The Little Book of Value Investing. I am a big fan of the Little Book series, and this book continues the trend of superb introductions to finance topics. In this post, I will highlight the key points from the book, derived from the notes I took while reading it.
Step 1 Analysis: Generate a Hit List
- Earnings: Look for low Price-to-Earnings (P/E) multiples, as these tend to perform better over time (My friends at Barel-Karsan have been investigating this, with exciting results!)
- Assets: Look for low Price-to-Net Market Value of Tangible Assets, as these tend to perform better over time. You are looking for stocks trading at less than book value (ideally less than 2/3 BV). Market value is important because it reflects what the company’s assets are today (so some things might be written off or increased). Tangible assets are better because their value is more readily recognized (whereas something like Intellectual Property or a Brand is more difficult to monetize and more subject to sudden deterioration in value. Always use Net values (removing liabilities) so that you can tell what amount of equity the company has in the asset.
- Cash Flow: Look for low Price-to-EBITDA multiples. This gives an idea of the short-term profitability of the company outside of depreciation and other non-cash expenses. Depreciation can be altered by changing depreciation accounting policies, so removing these is important.
Run those three things through a stock screener (Google Finance or Yahoo Finance). the output will be a hit list of potential value investments. Then, look more closely at each company on the list, starting with those companies or industries you are most comfortable with.
As we've seen in previous posts, looking at a company's price to book (P/B) value can be a useful indicator as to how favourably the market is looking at a particular stock or group of stocks. Low P/B values can also offer investors downside capital protection in case earnings dry up. But investors must be careful of putting too much faith in the actual book values of companies in which they are considering investing. Consider Circuit City.
A few months ago, Circuit City sought bankruptcy protection. Last week, the company declared that it is liquidating its stores. The company shows a book value of over $1 billion. So how much should equity holders expect following liquidation? According to acting president and CEO James Marcum:
The Company does not anticipate any value will remain from the bankruptcy estate for the holders of the Company's common equity, although this will be determined in the continuing bankruptcy proceedings.
The shares trade for just $5 million, despite the $1 billion value shown on the books! This represents a great example of how what's important is not what the book value is but rather what's in the book value. Circuit City's cash, accounts receivable, and inventory add up to $2 billion. While investors may have confidence in the value of these items for the most part, the value of the company's property, plant and equipment booked at $2.5 billion is much more uncertain. This number represents the company's historical cost for these items minus depreciation - it is not an indicator of what these items should sell for under liquidation.
The lesson here is that when looking for tangible downside capital protection in stock investments, a low P/B value itself does not guarantee protection. It's important to dig into the components of a company's book value to determine whether there are indeed assets that can be converted into cash. Ben Graham recognized this by estimating the liquidation values of companies by ignoring all fixed assets (i.e. current assets - all liabilities).
Site traffic continues to grow! In order to accommodate the site's growing number of readers, we will undertake some changes to improve the usability of the site. Based on some reader feedback we have received, we endeavour to better organize the site's now large library of articles and at the same time make the site more visually appealing. Before we implement the new look though, we'd like to get feedback from our existing readers.
So if you can spare the time, we'd love to hear your thoughts on a possible new layout for the blog, which can be viewed here. There's a simple poll on the new site which asks your opinion of that look relative to the current look, but if you have specific comments or suggestions please feel free to leave us a comment on this post or send us an e-mail. Thanks in advance for helping us improve the site!
Thanks a lot to Brad for his help in setting up the new look!
In order to determine if a company's debt load is over burdensome, investors often use interest coverage ratios. One such ratio is found by dividing operating income by interest due, in order to determine how easily the company is able to meet its interest requirements. However, investors must keep in mind that interest coverage ratios only demonstrate what has occurred in the past. Therefore, it's imperative to consider such information only when simultaneously considering what may occur in the future.
For example, six months ago we considered the interest coverage ratios of several public auto retailers. Since then, the bottom of the auto market has fallen out, resulting in massive sales drops. One may therefore expect companies with high interest coverage ratios to be in the best position to weather the storm. However, below is a chart depicting each company's stock performance in the last six months relative to its interest coverage:
The "safer" the company appeared by the interest coverage ratio six months ago doesn't seem to have had any bearing on the stock performance of the company. The reason? The companies have managed their way through this downturn with differing levels of success. Some have been overexposed in the worst performing segments for example, while others were able to streamline costs better than the competition. As a result, the chart below depicts how interest coverage ratios have changed since the snapshot we looked at six months ago:
Clearly, relying on interest coverage data has the limitation that none of the information is forward looking. Investors who do not consider more than past data are doomed to fall into traps from which recovery is very difficult.
Notice how one company's interest coverage actually improved despite the dire economic circumstances in this industry! We'll explore why in a future post.
Previously, we discussed some of the registration requirements for investment funds looking to raise capital. The purpose of these requirements is to protect investors from unscrupulous issuers looking to prey on those who fall for scams. But regulators have deemed that certain classes of investors do not require protection from themselves. As such, those looking to raise funds can take advantage of the following exemptions if they apply:
- $150,000 minimum investment. The thinking goes that those willing to invest this amount will do their due diligence before investing, and therefore don't require the same protections as those who make smaller investments
- Investors who make over $200,000 annually, or control over $1 million. Such people can afford to lose their investments, and therefore don't require protection
- Friends or family of the issuer. Issuers are less likely to rip off their friends and family
- Private Investment Club. Investor groups of 50 members or fewer are free to sell securities without being regulated.
Note that this is not a legal document, but rather an oversimplification of certain securities rules. Those wishing to raise capital using these means should endeavour to familiarize themselves with their local securities regulations. (These exemptions in particular form part of National Instrument 45-106, which is what governs in my jurisdiction of British Columbia.)
Microsoft has constantly come under fire in the last several years. It has ventured into less profitable areas, used monopolistic business practices, and is receiving a public thrashing from Google in search technologies. However, no one can dispute the fact that this company makes money hand over fist.
Despite the economic downturn, businesses and individuals alike require Microsoft software to increase their productivity. Both revenue and operating profits in 2008 were almost 20% higher than they were the previous year. But the company's stock price hasn't been this low since early 1998. It's P/E has never been lower, as shown by the following chart:
The company carries no debt and holds over $20 billion in cash. Even though PC sales may slow in the short-term, it's hard to believe that a company with the low financial risk and the global reach of Microsoft can have a P/E under 10.
The following summary was written by Frank Voisin, who regularly writes for Frankly Speaking. Recently, Frank sold four restaurants and returned to school to complete a combined LLB/MBA.
In his final chapter, entitled The Future of Intuition (and Expertise), Ayres makes the case for why statistical thinking will not replace expertise and intuition. Rather, decision makers will toggle between statistics and intuition.
Intuition will guide the questions asked, statistics will answer the questions and test hypotheses derived from intuition. Statistics will complement intuition rather then act as a substitute.
Not only will experts be switching between intuition and statistics, but so will average folk. We’ll use statistics to quantify our intuitions, learning how to think more accurately than in the past. We’ll all be forced to become more critical thinkers just to keep up.
Some key terms to understand:
- Random Sample
- Standard Deviation
- Normal Distribution (And, perhaps more importantly, associated probabilities of data falling within standard deviation)
- Chebyshev’s Inequality (Like the probabilities for normal distributions, but apply to all data distributions)
- Bayes’ Theorem
Midway through 2008, we looked at the closed-end funds that trade at the highest discounts to their net assets. But the discounts we saw then pale in comparison to the discounts we see now. Consider the largest discounts according to The Closed-End Fund Association (CEFA) now vs 6 months ago:
We also saw that near the end of 2008, the median discount for closed-end funds rose dramatically, so the rise in discounts we see in the table above shouldn't come as a large surprise.
Of course, this doesn't mean these funds are automatic buys. While investors may appreciate the fact that they can buy assets for a discount in the form of closed-end funds, they should always do their homework (i.e. read the fund's quarterly reports) to ensure they understand what they are buying. For example, if fund holdings are out of date (due to declines in market value) or illiquid, the book value may not be an accurate assessment of the value of the fund's underlying holdings.
So how would you have done had you owned these heavily discounted closed-end funds through the market turmoil that took place in the latter half of 2008? We'll explore that in a future post.
December employment data recently revealed that the US unemployment rate had risen to 6.8% from just 4.4% two Decembers ago. But certain groups of workers have fared better than others. One of the most successful groups at getting and keeping their jobs during this downturn is women, who make up over 45% of the work force. Here's a chart showing the number of employed women over the last two years (in thousands):
Interestingly, there are more women working now than there were 2 years ago, when the general unemployment rate was 33% lower than it is now!
This is actually a common theme during recessions. Women are disproportionately in positions which are relatively stable, such as health and education. Women also tend towards part-time positions, which are not cut as drastically by companies looking to slash costs. As a result, the unemployment rate for adult women is more than a point lower than it is for adult men!
Of course, this doesn't suggest women are better off now than they were 24 months ago. For one thing, this data does not describe income levels for the employed. Furthermore, there are more women (and men) in the labour force due to population growth and other demographic factors. So although there are more workers employed, there are many more looking for work.
As you can tell by this point in the book, super crunching is having a profound effect on our lives, whether we like it or not. Ayres gives examples in this chapter of who is losing out due to super crunching. Doctors and other intuitivists are losing out as the status of these professions decreases in relation to the awesome power of super crunching.
The problem is that experts tend to give settled answers that leave us feeling a sense of closure. Super crunching gives odds, which leave us unsettled and unclear about what will happen. This is more accurate, but people aren’t used to this.
We should see statistical decision making as the rise of meritocracy. Intuitivists are often praised for their historical record, and earn high fees on their future performance even though this is unreliable (See my review of Nassim Nicholas Taleb’s Fooled by Randomness for further discussion of the problems of confusing past performance with skill!), whereas statistical decision-making minimizes the chances of failure - let the best ideas (statistically) succeed, regardless of who put them forward!
For most companies, recessions reduce P/E ratios, as investors withdraw money from the market and become stingy with their purchases. We saw this pattern emerge when we looked at the historical P/E of the S&P 500. We also saw examples of companies trading at their historic P/E lows here and here. But strangely, some companies actually see their P/E's increase during economic downturns, and not only those which sell cheap or defensive products. Consider Fedex (FDX).
Fedex is often considered a bellweather for the economy, as when the economy is going well/poorly, Fedex will often see a pickup/dropoff in deliveries. As such, when the economy tanks, one may expect the P/E of FDX to deflate. But here's a look at what happened to FDX's P/E during the last comparable recession:
So what's going on here? The price component of the P/E value did drop to $40 in 1990 from $64 in 1987. But the earnings dropped even more. When this occurs, the P/E may look extremely large, but the company may still be cheap: FDX rose through $76 just 3 years later.
For this reason (and many others which we discussed here), investors should use average earnings when trying to determine a company's P/E, since earnings of one particular year (particularly a recessionary year such as this one) can be misleading.
The recession of 2001-02 is considered a relatively mild economic contraction. In a previous post, we saw evidence of why that might be by comparing unemployment data across several recessions. Another interesting way to compare recessions is by looking at bankruptcy data. Here's a look at business bankruptcies each year (year end: June) for the last quarter century:
Once again we see that while there was a slight uptick in business bankruptcies in 2002, it was nowhere near levels of previous recessions.
While the current bankruptcy level seems low, recall that the year end for this data is June, and things took a dramatic turn for the worse after that. It will be interesting to see quarterly data as it comes out, and it should not be surprising to see 2009 levels reach those not seen since the early 1990s.
This data doesn't tell the full story, however. The magnitude of the bankruptcies are not shown; for example, a Lehman Brothers bankruptcy has far more impact than that of a small business, but this data does not account for this. Furthermore, changes to bankruptcy laws over time have change incentives for businesses to file, and therefore makes the data more difficult to interpret. Finally, this only includes business bankruptcies, and excludes consumers bankruptcies, which we will look at in a future post.
When Warren Buffett, Francis Chou and other great value investors started their investment funds decades ago, there was little in the way of securities regulation. Since those times, however, members of the public have fallen victim to a plethora of scams from less honest entrepreneurs. As such, securities regulations have evolved to a state where some of the great investors we recognize today may never have gotten their start had these rules existed back then. In order to protect the public from themselves, here are just some of the requirements* of those who are looking to raise capital from the public for investment:
- File a prospectus which includes various required categories of information such as financial statements, management discussion, articles, certificates etc.
- Hire an auditor to certify financial statements reported
- Pay to the regulator $2500 annually for the right to apply to register
- Pay to the regulator $250 for each officer of that company
- Maintain a minimum working capital of $100,000
- Place a bond with a financial institution for $200,000 for insurance purposes
- Pass several securities courses, as specified by Instrument 31-601
- Work for five or seven years at a firm that is already registered
Regulators do recognize, however, that some of these requirements are over burdensome for many companies. Therefore, there are exemptions available when, in the regulator's opinion, investors do not need the same level of protections as are outlined above. (For example, most hedge funds take advantage of exemptions in order to avoid much of the regulatory pain.) We'll explore some of these exemptions in future posts.
* These are requirements for funds based in my jurisdiction of British Columbia, but are very similar to those in jurisdictions across North America.
One of the major reasons for the increase in super crunching is Moore’s Law, Kryder’s Law and their relatives. Processing power, Bandwidth and Storage keep increasing exponentially, while their costs keep decreasing (Chris Anderson discusses other implications in Free: Why $0.00 is the Future of Business). These trends are making it easier, cheaper and more efficient to super crunch. More and better data are available online every day because of the increasing ease of both collection and transmission.
Conclusion: Expect to see more super crunching in the future. This is just the beginning.
When we looked at the historical book values of FedEx (FDX) and UPS, it was clear that UPS has always traded at a significant premium to its book value as compared to FDX. To understand why, one only has to compare the relative returns on equity* for the two companies: UPS 16.6%, FDX 11.6%. But how UPS manages to generate a higher return on equity may come as a surprise to many.
To demonstrate how UPS generates the higher return on equity (ROE), it's useful to examine the following equation: ROE = Net Income / Equity
ROE can be further broken down into (Net Income / Assets) * (Assets / Equity).
In other words, we can break down a company's return on equity as a combination of its return on assets (Net Income / Assets) and its use of leverage (Assets / Equity).
But for both FDX and UPS, return on assets sits at 6.3%! This means the major difference between the ROE for these two companies comes from differing uses of leverage. Indeed, the debt to capital ratio for FDX sits at just 13% compared to 44% for UPS. This means UPS hasn't generated its superior returns through better operations, but rather by using cheaper capital (debt) while taking more risk as a result.
Should UPS pay down its debt so that its risk level isn't so high, or should FDX take advantage of cheaper capital in order to generate more returns for shareholders? We'll explore these questions in a future post.
*To smooth out fluctations, ratios in this article were taken using the average of the last two fiscal years of each company.
As brought up by a comment from Matias, it is sometimes interesting to compare the historical P/E ratios of market competitors to understand how Mr. Market thinks. The Home Depot (HD) and Lowe's (LOW) have been competing in the home improvement retail space for decades. Here's a look at their P/E's over the last few decades:
Clearly, HD has been the market's favourite for most of the last 30 years. HD was growing its store count and thus its revenue at a faster rate than LOW, and this is a major reason why. However, as we discussed here, investors tend to overpay for growth. The fact that HD has not been near its 1999 high of $70 suggests this may have ocurred here as well.
In the last few years, however, it is LOW that has enjoyed a more generous valuation as far as P/E's are concerned. With HD's declining retail operating metrics (relative to LOW) and growth into other businesses like building wholesale, the market's taste for this company soured. HD has since sold its supply business, ousted its much maligned CEO (who is still maligned at his new company, as we saw here), and brought a stronger focus to its retail operations. As such, the P/E's of these two companies are now quite close.
What is most clear from the chart, however, is that this industry is currently out of favour with the market. Last time these companies saw these valuations was during the last real-estate crash (which we explored here). As such, investors are not asked to pick a winner, but are instead offered both companies at low historical prices, allowing for the possibility of long-term returns in the home improvement retail space, without the risk of reliance on a single company.
Disclosure: Author owns a long position in both HD and LOW
It seems very obvious at this point in the book, but Ayres uses all of Chapter 5 to show dozens of examples to prove that traditional experts are not up to par with super crunching. One problem is that most experts are overconfident, ignoring their potential faults at the expense of further investigation. Another problem is that many problems are too complex for the human brain to accurately crunch - we just aren’t good at permutations and combinations and statistical modeling! We are “damnably overconfident about our predictions and slow to change them in the face of new evidence”
Evidence shows that human judges are “not merely worse than optimal regression equations; they are worse than almost any regression equation”! Regression is not only more accurate, but it is upfront with the proportion of the time the prediction is going to be true.
However, regressions only work in the aggregate, and individual occurrences may cause certain cases to become outliers. These are not statistically significant enough to affect a regression output, but are important enough in certain situations that would warrant human oversight. Though, this must be weighed with our human biases that are overconfidence in our ability to outperform the system.
Conclusion: Statistical tools are extremely useful in guiding the decisions of experts, but should not obliterate expert discretion. To surrender discretion to the machines, we will lose the ability to take things into account which, while not statistically significant, DO play a role in individual cases. The greatest potential lies in situations where machines guide the discretion of experts based on statistical probabilities toward the best outcome (This is where my previous post, Occam’s Razor, comes into play). We have some use after all!
When considering a company for investment purposes, investors must be wary of managements that over promise and under deliver. One symptom of such a situation is over-optimism from managements in their quarterly reports and conference calls. Consider Rite-Aid (RAD), a US drugstore chain. Deep down in the company's press release, management noted reduced profit expectations going forward from an already negative $500 million to a more negative $700 million. But the company's press release headlines read as follows:
- 8.5% EBITDA increase over prior year (as if debt, taxes, and depreciation are meaningless, all of which are higher than they were the previous year. Here are Buffett's thoughts on the practice of focusing on EBITDA.)
- "Sales Trends In Acquired Stores Improved" which means sales still dropped, but not by as much as before.
- I am pleased to report a significant improvement in our operating results this quarter
- Our team has been totally focused on delivering profitable sales and taking unnecessary costs out of the business, and it showed
Meanwhile, as we discussed here, the company has to undergo a 10:1 reverse stock split just to maintain a stock price above $1 so that it can stay on the NYSE. The company is also trying to sell its stores and lease them back in order to pick up some short-term cash, despite the current dire real estate market!
Be wary of managements that can find a glass half-full in an empty glass.
Due to slack demand, the price of oil has come down drastically in the last few months. To temper the price drop, OPEC cartel members have been slashing production in order to reduce supplies. Officially, OPEC member countries have each agreed to production quotas. However, from an economic point of view, each member has an incentive to produce as much as possible unofficially, resulting in an actual oil price not very far from a cartel-free oil price.
To understand this incentive, consider a duopoly where both firms (A and B) have decided to collude to control the price of the product they sell. Suppose if both firms cooperate, they will each benefit by $1 million in extra profits. But if one firm decides to cheat by producing more than what was agreed upon, it will earn $3 million while the other firm will lose $1 million. If both firms cheat, they are in competition as before and therefore derive $0 in benefits from their collusion.
While this is a simplification of the economic theory, the economics of a cartel do boil down to incentives of this nature: if a firm decides to comply, it can make either $1 million or lose $1 million, depending on the decision of the other party. If a firm decides to cheat, it can make either $3 million or $0. As such, assuming the other party will make the decision in its best interest, cheating provides the more appealing option.
While OPEC countries do have quotas, it is in the best interest of individual firms to "cheat" by selling as much oil as possible (as long as revenue is greater than variable costs), as per the discussion above. As such, announced production cuts do little to quell drops in the price of oil, as member countries will usually* do what is in their individual country's interest in order to maximize profits.
*When financial interests are not the chief concern of the member countries, such as during the oil embargo of the 1970s, a cartel of this nature can prove to be quite effective at controlling prices!
Evidence-Based Medicine was developed by two Canadians (Gordon Guyatt and David Sackett). The central premise is that treatment should be based on the best evidence (which, in turn, should be guided by statistical research). Just as super crunching is controversial in other fields, this caused an uproar in the medical community, which largely believes that medicine should be treated by doctors’ instincts.
Doctors should behave more like pilots. Pilots have significantly less discretion, and correspondingly there is less deviation from the norm. When doctors deviate from the norm (the proper procedures), people die. Statistical evidence shows that less discretion for doctors would save lives (this is the heart of Evidence-Based Medicine)
Statistics have also shown several well-ingrained practices (listening to the heart during annual medical exams) and beliefs (Vitamin B12 deficiencies must be treated with shots because pills are ineffective) to be incorrect. Yet, old habits die hard.
The key will be to make it easier for physicians to retrieve concise, high quality reports of the results of statistical research. It is currently too difficult and time consuming to find relevant information.
Those who have dealt extensively with online brokerages know that there is a lot of room for improvement. Brokerages make their fair share of mistakes, with little offered in the way of restitution. One man, however, didn't take his brokerage's lack of remorse lying down, and successfully sued it for delaying his trade!
Peter Phipps issued a buy order for 3000 shares of Research In Motion (RIMM) that did not execute until the following day. While his order was delayed, Phipps made numerous unsuccessful attempts to lift a block that was erroneously placed on his account. While the block was in place, RIMM stock increased by a couple of bucks, costing Phipps a few thousand dollars.
The judge ruled that the brokerage should have removed the block within 20 minutes, which in the judge's opinion is a reasonable time within which to act for a company where its clients can lose or gain thousands of dollars within a matter of minutes. The Bank Of Montreal was ordered to pay Phipps $4400, which recoups what he would have made if not for the delay which was over and above 20 minutes.
For those who have experienced similar issues, take heart in knowing that you may be able to pursue legal means to claim back losses if your brokerage messed up! For those interested in finding the full text of this case, it can likely be found in your local law library using the following header:
Phipps v. Bank of Montreal Nesbitt Burns (2005), M.J. O'Hara Adjud. (N.S. Small Cl. Ct.) [Nova Scotia]
Harry Winston (HWD) is a retailer and producer of diamonds, with high-end stores restricted to New York, Paris, London, Beijing, Tokyo and Beverly Hills. The stock has dropped from over $40 to its current price under $5, despite earning $1.17 per share last quarter. It has a book value of almost $800 million (including over $350 million in inventory), but the market values it at just $300 million. Does this stock offer investors a margin of safety? While the company looks great on the surface, this is a classic example of why investors must dig deeper than the surface numbers in order to truly understand and value a company.
First of all, most of the company's sales and profits come from its mining operations, not its retail business, which lost $4 million last quarter, on par with the comparable quarter one year ago. This means the company's profits will be heavily dependent on the commodity price of diamonds, which is a situation value investors prefer to avoid.
Furthermore, NWD operates just one mine, located in northern Canada. As discussed in Security Analysis, reliance on one location or one supplier or one customer is always a high risk. In the case of NWD, the investor must rely on highly subjective estimates of the lifetime productive capacity of the mine. Even short term production is hard to predict: last quarter, diamond production at the mine was down over 25% because of lower grade material in the portion of the ground currently mined.
Finally, while the company's book value looks terrific, a closer examination reveals that much of its value is in the name of intangible assets. Removing these assets results in a tangible book value 25% lower than the stated book value.
This company's reliance on uncertain output from just one mine combined with the fact that the value of any units of output is highly uncertain due to volatile commodity prices results in a highly uncertain earnings power for this company. In addition, the value of intangibles is also highly uncertain. As a result, despite the great value this company appears to be on the surface, it's not the worth the risk.
Walgreen and CVS are the largest retail drugstore chains in the US. As such, their financials are often compared. With a P/E of 13.50 for CVS versus just 12 for WAG, the investment community gives CVS the edge due to its faster growing sales and profits. But such a superficial approach to determining the better investment ignores the most important question when it comes to selecting an investment: returns on invested capital.
Any investment a company is required to make is less money in the hands of shareholders. Therefore, if one company can generate the same profits as the other but using much less capital, its shareholders will benefit. For a full discussion of this concept, see the discussion here.
In the case of WAG and CVS, here are the return on invested capital numbers for 2008:
Note the major difference in ROIC for these two companies. A dollar invested in WAG appears to go much further. One caveat to note is that these are only 2008 numbers, and as we've discussed before, to properly analyze a company and its management, it makes more sense to consider several years worth of data to remove the effect of unusual items. (For example, CVS has experienced integration costs due to a recent acquisition.)
As a result of its strong returns and lower capital requirements, WAG was able to pay a dividend higher than that of CVS in 2008 despite lower net income levels. If this difference in returns is persistent, CVS may show higher profits, but would nevertheless be the inferior company for shareholders.
The US Government has been one of the biggest supporters of the randomization approach discussed in Chapter 2, using it to drive many public policy making decisions, reducing partisan politics (it is less politically-sensitive to agree to the results of a randomized test rather than agree to something on principle).
Ayres has many examples, both American and international, that show the powerful and positive effect randomization can have in evaluating policy and government programs.
Conclusion: Governments should be adopting conditional cash transfer programs (conditional on evidence from randomized trials), because they have been proven more effective.
Reyer and I started this site about 8 months ago, with the idea of exploring and discussing various value investing related topics. We're pleased to note that we recently hit our 300th subscriber, and continue to grow! (If you're interested in subscribing, you can automatically receive our posts for free by e-mail or through an RSS reader; just follow the instructions on the right frame.)
If you're an existing subscriber, you'll also notice we've added advertisements to the top of our feed. We receive advertising dollars each time a user clicks on one of those ads, and so with our growing subscriber count it made sense to open up this revenue stream. Hopefully these ads aren't getting in the way, but let us know if you have any concerns!
We also decided to dig through some of our site statistics in order to present links to some of our more popular posts. In this way, those who are new to the site can get a look at the favourite pages of those who have been coming here for a while:
1) Our trip to meet Warren Buffett
2) Panic of 2008
3) Home Depot vs Lowe's
4) Examples of value companies that reached intrinsic value
5) Our chapter-by-chapter summaries of Security Analysis
6) Lunch with Francis Chou
7) Build-A-Bear On Its Death Bed?
8) Jim Cramer buys high and sells low
9) How good are analyst predictions?
10) Why airlines are bad investments
Please stay in touch by continuing to let us know what you like or don't like about the site! For instance, what are your favourite types of articles?
Few would dispute the fact that the housing market is undergoing an unprecedented downturn. But stocks in this industry may have been punished far more than is warranted. Investors with a long-term outlook can seek to profit by buying such beaten down stocks, and holding them until the market's current bout of pessimism erodes. Consider The Home Depot (HD). Below is a graph depicting it's P/E over the last few decades:
Due in large part to the macroeconomic environment, the stock is trading at historic lows compared to its earnings. But we can see from the chart that sentiment does vary dramatically when it comes to this stock. The changes in market sentiment that lead to the peaks and troughs of HD's P/E are quite dramatic!
However, one cannot make a purchase based only on this analysis. It's important to consider debt characteristics and the future viability of this business. HD has grown to be quite a bit larger than it was when its P/E was hitting 60, and so growth prospects may not generate the same kind of returns as they have in the past. Furthermore, Lowe's (LOW) has taken steps in recent years to become a strong competitor. (We've compared these two companies across several metrics here.)
Nevertheless, despite the downturn, HD is quite profitable, and not in any danger of defaulting on its loan obligations (as discussed here). As such, HD may prove to be a value purchase for investors with long-term horizons.
Companies that have taken to super crunching have begun generating their own data by running randomized experiments for new products and marketing approaches. They randomly split prospects into two groups and check which approach works best, then use regression to find the relationships.
Why do this? Causation! By looking at historical data, it is difficult to determine causation (many variables). By looking at a large random study, you don’t need to control for causation if the groups are equally representative (and you have a sufficient sample size). When you see one group reacting differently, you know the cause is the different approach taken with that group.
Conclusion: Use the randomized data approach to bring your customer’s voice into marketing decision making; remove the gut instinct or intuition of the marketing department and consultants. By listening to the consumers themselves, you will make the most profitable decisions.
Williams-Sonoma (WSM) has been thrashed by the market. As a retailer of specialty home products, it has seen revenue declines on the order of 20% from last year thanks to the deflating housing bubble. The stock, however, has been beaten down by over 80% from its high at the height of the boom. With a price to book value under 1 and a P/E of 6, this stock appears to offer value at its current price.
The company has earned an average of $1.75 per share annually in the last four years, while the stock trades at just $8.31. While we may not see earnings return to those levels for some time, depending on the length and magnitude of this downturn, there are several reasons to believe the company can survive and be profitable in the coming years.
First of all, its debt to equity ratio sits at just 2%. While the company does have operating lease commitments, many of them expire in the next 1-3 years, giving the company the flexibility to either close cash negative stores, or negotiate costs downward.
Furthermore, the company's sales channels are not limited to retail locations. Almost half of WSM's revenue comes from catalogue sales. Since such sales require less in the way of assets, it is much easier to scale down costs in this business as compared to the bricks and mortar model employed by most retailers. Costs of a variable nature (rather than fixed) can be a tremendous strength when the economy is contracting.
The company also has a wide array of brands and store concepts, including Pottery Barn and West Elm, in addition to the Williams-Sonoma brands. This diversity reduces the risk that one brand or store concept that goes out of fashion will permanently impair the company.
While there is no current end in sight for the housing industry drought (which we've expored most recently by looking at inventory numbers), WSM looks like a stock that can outlast the downturn, and represents a great value opportunity for those with a long-term outlook.
Magna International (MGA) is a global auto parts supplier. The stock was flirting with $100 last year, but due to the collapse of the auto industry it now trades at just $26. It has a debt to equity of just 8% and produces a diversified plethora of parts in plants across the world. Does this stock represent a great value opportunity for long-term investors who expect auto sales to return in the long run?
Unfortunately, despite its low debt to equity ratio, the company is still a high risk. How? As we discussed here, one of the most important elements in determining a company's risk level is the concentration of its revenue by customer. For MGA, this is what it looks like:
The chart above clearly demonstrates the high risk nature of this company. The loss of any of these major customers reduces the value of this company tremendously. Also note that the auto parts industry is characterized by high fixed costs, and therefore any changes in revenue have a magnified effect on the bottom line. In other words, while the loss of GM as a customer (to bankruptcy or to a competitor for example) would reduce revenues by 24%, it would reduce earnings by even more.
For a recent example we've discussed of a beaten-up auto industry stock that offers value without the concentration of customers, click here.
The Wisdom of Crowds allows groups to help find things that are best for individuals. By telling Amazon what books you like, it can tell you what groups of people who have bought those books have liked as well. This kind of data mining - from group behaviour to create individual recommendations - has been shown to be more effective than regular book or movie reviews (in that individuals report greater satisfaction with the recommendations).
Regression: A statistical tool that looks at raw data (what happened) and derives relationships between variables to help make predictions about the future. This is one of the most powerful tools in the arsenal of modern analytics practitioners. The output of regression is an equation of the line that best fits the raw data. This equation is then used with different inputs to generate the output of theoretical scenarios.
Finding these relationships is important for business: helping companies assess demand and move to just-in-time inventories, assess the true characteristics of good employees and thus reduce turnover, and determine which customers are likely to leave and how this can be prevented.
Conclusion: Companies won’t survive as their competitors become super crunchers, learning how to extract more profitability from their customers while preventing them from defecting and simultaneously learning how to most efficiently steal your best customers. As a businessperson, you need to learn how to become a supercruncher, just so you can survive. As a customer, you need to be vigilant in your dealings with companies that are soliciting your business (this is an indication you’ve been overpaying!) or offering you extra features at a price (these are often not a good deal!).
Walgreen (WAG) is a retail drugstore chain that operates primarily in the US. Its industry is considered relatively stable, as prescription medication costs are unlikely to rise or fall significantly depending on the economy (unlike certain surgical procedures, as we saw here). WAG has also been around for decades, and therefore offers us the chance to examine investor sentiment towards this company over time. Below is a depiction of WAG's P/E since the early 1960s:
Clearly, Walgreen has seen many recessions come and go. But despite the stable nature of its industry, it has seen wild fluctuations in its P/E, especially in the last decade. (Incidentally, despite being in a completely different industry, Coke (KO) is also an old and stable company which therefore lends itself to the same kind of historical P/E analysis, which we looked at here.)
We can see from the above chart that WAG has not traded at such a low P/E for quite some time, which may offer long-term investors the opportunity to profit from a potential P/E expansion when positive investor sentiment returns. However, a company's P/E value does not take into account its level of debt and is furthermore affected by one-time items which may distort a company's "normal" earnings. As such, in future posts we'll compare WAG to its competition (CVS, RAD) keeping such items in mind.
The Efficient Market Hypothesis (EMH) asserts that stock prices appropriately incorporate relevant information. As such, it isn't possible to generate market beating returns because the current price reflects available information. While it's not possible to completely disprove this theory (EMH theorists attribute the success of Warren Buffett and other value investors we've looked at here to random chance), there are examples which make this very difficult to believe. Consider CVS Caremark (CVS), a provider of pharmaceutical services.
Despite economic hardships, most people will not go without their required medication. As such, one would expect this business to be stable even at the worst of times. A look at the operating margins for CVS over the last business cycle reveals this line of thought to be correct:
We can see from the chart above that CVS has maintained margins through downturns, as one would expect considering its industry. The stock price, however, tells a different tale. The stock has dropped 30% in just the last few months, despite very little change in the earnings or earnings outlook for this business.
If the market was right when the price was $43 then how can it be correct now at $27, when little has changed. Examples like this certainly offer doubt as to whether the market always appropriately values stocks. While this doesn't neccessarily mean CVS is undervalued now (as perhaps it was just overvalued before), it does suggest there are profit opportunities for those who are able to take advantage of Mr. Market's mood swings.
Shares in TAT Technologies (TATTF) rose last week as the company announced a plan to buy back around 10% of the company's shares. Shares usually do rise in response to such announcements, as they imply that management believes a company's shares to be undervalued. Since management knows the business better than anyone, the market responds positively. Unfortunately, investors cannot rely on announcements such as this in order to determine whether a company is undervalued.
First of all, because such announcements usually result in a stock price boost, unscrupulous managements can use this method to simply boost the stock price to a level higher than it otherwise would be. Furthermore, managements are subject to the same psychological forces that govern the market, and as such they can often be woefully wrong about whether a stock is undervalued. Often, there are also incentives for managements to buy back stock other than a belief that the stock is undervalued. For a discussion on such incentives, see this article discussing the terrible buyback decisions of several large companies.
To determine if a company is undervalued, the investor's best approach is still to determine an estimate of the company's intrinsic value (which we discussed here for TATTF), rather than relying on fruitless attempts to gauge management's opinion of a stock.
“It is difficult to get a man to understand something when his salary depends on his not understanding it.” - Upton Sinclair
Unfortunately, analytics doesn’t play a large enough role in decision making. Too often, the old guard has been founded on its “expert” opinion-making abilities. Wine and art critics feel scientific methods can never do what they do, let alone better. Though the proof is in the pudding: Orley Ashenfelter has proven to be more accurate with his scientific analysis of wines than Robert Parker’s “expert” senses, and Bill James proved better at picking baseball players than major league scouts, each determined on objective standards.
Experience and Intuition are losing out to analytics, and we seem to be on the cusp of major change. In the future, these techniques will become increasingly important, and so it is a valuable book to learn about the power of analytics and how it can help you do everything you do!
On to the rest of the chapters!
It's no secret that one of the main reasons Japanese automakers have triumphed over their American competition is productivity superiority. In other words, the average worker at a Japanese automaker can make more cars in a year in the same amount of time as a worker at an American automaker. When combined with the much publicized labour cost differences between the firms, a huge advantage emerges for the likes of Toyota and Honda.
What is the source of this productivity advantage? According to a paper by UCLA professors Lieberman and Demeester, a great source of the productivity advantage comes from forced reductions in work in progress inventory. When buffer inventories between manufacturing stations are kept high to ensure manufacturing disruptions are kept low, manufacturing inefficiencies are masked. With Just-In-Time inventory programs, historically implemented by Japanese companies to reduce inventory requirements because of high storage costs, firms are forced to improve manufacturing processes. The paper asserts that each 10% reduction in work in progress inventory results in a 1% gain in productivity after one year. The full text of the paper is available here.
In a related post, we've discussed how to determine if a company is managing its inventories well. We also saw that GM and Ford were both value traps back in 2004.
If a stock is delisted from its market, it will become less liquid and will likely trade at a discount to its previous price. Therefore, when considering a stock for purchase, you may want to ensure it is not in danger of being de-listed from its exchange. For example, here are the requirements for a stock to remain compliant with the NYSE.
However, just because a company does not meet the requirements now does not mean it will be delisted. Consider Rite Aid (RAD), a US retail drugstore chain. The stock trades at just 33 cents, which is far below the minimum $1 requirement for the NYSE as listed here. However, a grace period is granted to allow companies to regain compliancy. In the case of RAD, because it has an abundant number of shares, it can do a 10-1 reverse stock split. In this way, it will increase its share price to $3.33 and still have the minimum number of shares to remain compliant.
A rising number of companies, however, do not have the flexibility of RAD. In the first three quarters of this year, 19 companies have been delisted from the NYSE. Investors should ensure they are aware of any upcoming dangers of delisting in order to avoid unwelcome surprises with respect to any companies in which they are considering investing.