The Financial Crises Ten Years Later

Much has been written in recent days about the financial crises ten years ago. The major themes of the articles are: (1) what caused it? (2) can it happen again? and; (3) when will the next market crash come? From the crises low during March 2009 through September 4, 2018 the S&P 500 has increased approximately 186% ex dividends, which is equivalent to an approximate annual return of roughly 10.86% ex dividends. For much of the same period, 10 year U.S. Treasury Notes have largely traded in 2% the 3% yield range, which implies an equity risk premium of 8% to 9%. See the charts below for SPY ETF prices as a benchmark for the S&P 500 and ten year treasury yields between January 2009 and September 2018.

Investors prescient enough to be out of the stock market before the crash who then jumped into the S&P 500 index as a passive investor in March 2009, at the crises lows would have earned the market return of 10.86% ex dividends per year. Investors who parked investment dollars in a fund that was invested in the S&P 500 and managed by a professional money manager at the March 2009 lows had about a  90% chance of being beat by the market, so their S&P 500 holding period return (net of fees) was likely less than 10.86% ex dividends.

The odds of putting money to work at the march 2009 low and holding on for a decade for professional fund managers or individual investors is extremely low. Looking backward, we know that the market beat 90%+ of small, medium and large cap money managers during most of the ten year period since the crash.[1] We also know that investors putting money into the stock market at the crises lows faced an unprecedented level of uncertainty looking ahead into the future. Investors who stayed out of the stock market in the U.S. after early 2009, missed a long bull market and part or all of a of a 186% gain, which was a much higher return earned by those who played it safe by buying  2% to 3% yield to maturity ten year treasury bonds or staying in cash equivalents.

Today, ten years after the crash there are a steady stream of opinions about the next crash or not, put out by investors on main street and Wall Street. The reality is that the "next crash or not," is very difficult to, if not impossible to reliably predict in terms of timing, effect and magnitude. Simply put, this kind of certainty does not exist in the markets, in my opinion.

Some of the most sophisticated and successful professional investors (pros) I know spend little if any time predicting the future of the economy or markets in an effort to time the market. They also stay invested and tend not to be focused on timing their entry or exit from markets. Pros are constrained by factors such as investing mandates, flow of funds in and out of their funds at suboptimal times and benchmark tracking, that can hurt their performance. The professional investing community is a talented hardworking group of people with the skills and resources that have an advantage over individual investors but tend to cancel each other out, making it very difficult for them to beat the market in any given year or series of years.

Markets are dominated by pros that have advantages over less sophisticated individual investors in terms of training, research and knowledge of how to use information flow among other factors. Despite this, pros cannot reliability time the economy, the market or other factors that may affect the financial markets. Individuals who try to compete head on with the pros have little chance of beating the market. On the other hand individuals do have some legitimate advantages over the pros that include, self defined and theoretically unconstrained investment horizons, personal discretion to be in the market or not, asset allocation discretion and investment strategy flexibility, among other factors.  

Similar to the pros, individual investors have no advantage or edge in terms of practicing market timing. Anecdotally speaking, I have yet to meet an individual investor who has been successful and beat the public markets over time through market timing based on economic or market forecasts. In other words trying to jump in and out of the market around recession and economic forecasts is difficult to bordering on impossible and therefore is not a viable investment strategy.

Ten years after the crash the best investors that I follow and mimic, spend little time trying to predict the next one as their and my investment strategy is not based on market or economic forecasts. I have had little success in the past trying the time the market or attempting to figure out its direction day-to-day and month-to-month, etc. based where I think the economy might go. The lesson from previous market crashes and dislocations is that forecasters do not accurately forecast them as to timing and severity. The case can be made that top down predictions of future recessions and market collapses will be no better than past predictions.

As a bottom up individual investor I do not focus on market and economic or market collapse forecasts as my primary lens is a focus on buying small pieces of equity of public companies that can be held onto for many years, if not longer. I have also been a buyer of debt, commodities and real estate, among other asset classes. I have not used leverage in my accounts. I typically invest in companies that are reasonably financed, have a competitive advantage and the potential to earn high ROIC’s well above their weighted average cost of capital. I have invested in small, medium and large cap stocks in Asia, Europe and the United States and also in ETF’s from time to time. My portfolio has been weighted toward large cap U.S. companies that do business in the U.S. and abroad.  I identify investment targets through my own primary research and the research of others.  Most of my current equity positions were purchased when the company I invested in was out of favor on Wall Street due to worries, concerns and company difficulties at the time of purchase. In recent years I have also invested alongside select activist investors that I follow. My portfolio typically consists of no more than 10 to 15 positions and typically includes heavy concentration in 3 to 5 positions.  I attempt to reduce the correlation between the positions through security selection and by running several investment strategies at once, e.g. growth, value and special situations investing in equity; debt and commodity investing; and event driven bets such as the Greek debt crises and the Japanese tsunami disaster, among others.

I have not managed the portfolio against benchmarks, but for illustration purposes below I compare my results against the S&P 500 index due to the large proportion of large cap U.S. stocks in my portfolio. In recent years my returns have approximated the S&P 500 while holding significant liquid cash equivalents (i.e. 20% to 30% of the portfolio). The portfolio has outperformed the S&P 500 in the current year and the last 12 months due to the performance of stocks that I purchased several years ago as well as a reduced cash weighting. I have made no effort to time the market and held several stocks for years with my biggest bet held more than a decade (i.e. before the previous market crash).

Total return	YTD
At 8/31/18	2018	1 yr	3yr	5yr	8yr
Portfolio - A	15.78%	30.45%	16.89%	13.95%	14.48%
Portfolio - B	21.00%	39.00%	16.30%	14.00%	19.60%
Combined total	17.14%	32.67%	16.74%	13.96%	15.81%
weighted average return
S&P 500 return	9.94%	19.66%	16.11%	14.52%	10.60%
Excess return - A	5.84%	10.79%	0.78%	-0.57%	3.88%
Excess return - B	11.06%	19.34%	0.19%	-0.52%	9.00%
Return above S&P 500 index	7.20%	13.01%	0.63%	-0.56%	5.21%
- combined

---

[1] Per "Risk-Adjusted SPIVA Score: Evaluation of Active Managers' Performance Through a Risk Lens" research published by S&P Dow Jones Indices, for year-end 2017.

Business Growth and Liquidity

An owner of an IT consulting firm spoke to me the other day about his business. His chief concern was finding and growing revenue so he can grow his business. He indicated that in some years he has generated more fee revenue than others, which caused him to take-out or contribute funds to his business. Business has been good of late, so he was struggling trying to figure out which projects to take on (e.g. large projects with deferred fee collections and average realization rates or small projects that would cash flow sooner at lower estimated realization rates). His decision will impact how large his business will grow into the future. His problem of determining how fast he can grow his business is similar to other business owners and CEO’s I have advised and worked for. I listened to his dilemma and responded to him by indicating that I understand his problem. I congratulated him on his success and also commented that it is possible he ends up in a liquidity crises or worse by growing revenue too fast given his liquidity profile and financial model. With a look of disbelief, he asked me how. My answer is as follows.

While most public and private businesses I have worked in, modeled and followed, desire and are typically focused on growth, a smaller number actually perform financial planning in a manner that, explicitly focuses on the limits of sustainable growth (also known as known as the sustainable growth rate (SGR). The definition of the term is as follows.

SGR is the maximum amount sales can increase without depleting financial resources which means that there is a limit to revenue growth based on a given company financial model. For an owner/operator consultant/CEO trying to grow a practice to growing Fortune 500 businesses, it generally takes resources (i.e. more assets that must be paid for) to increase sales.

The concept was developed by Professor Robert Higgins of the University of Washington. Put another way, what he describes in general, is the maximum rate of sales expansion an enterprise can undertake without issuing debt or equity in a given unaltered capital structure. Since all company balance sheets must be comprised of total assets that equal the sum of total liabilities and equity, equity growth allows for growth in liabilities which determines the rate in which assets can expand, which in turn determines the growth rate in sales, as sales bear a relationship to the asset base in a given enterprise. As Robert Higgins indicated, a company’s SGR is equivalent to its growth rate in equity defined as PRAT. [i]  PRAT represents relationships between profit margins, assets turnover, leverage and earnings retention as follows:

P = profit margin

A = asset turnover ratio, (P x A = return on assets (ROA))

T = assets to equity ratio (i.e. leverage ratio)

R = retention rate (i.e. the portion of net income retained in the business)

The first three terms (i.e. P, A and T) are sourced from the DuPont ROE calculation method which is:

(Net income/sales) x (Sales/total assets) = ROA x (Assets/equity) = ROE

ROE is then multiplied with the earnings retention rate to arrive at the sustainable growth rate as follows:

ROE x (earnings retention rate) = sustainable growth rate in revenue (SGR)

Higgins points out that SGR is the only revenue growth rate that is consistent with stable values in the four ratios and that at least one ratio must change if a company grows at any other rate than the SGR. Which means that operating performance (measured by ROA) or its financial policy (i.e. leverage or earnings retention) must change? Companies with growth rates higher than SGR result in cash deficits. In response, companies can increase profit margins or asset turnover thereby altering ROA or change financial policies (i.e. leverage, equity issuance and earnings retention). Higgins indicates that for long-term sustainable growth issues some combination of debt increase, equity issuance, increased profits, divesting marginal activities or merger with a cash cow would need to take place. Listed below is a summary of the SGR:

Figure 1 - Summary of SGR (Gray boxes are ROA related components, Green boxes are financial policy components)

Source: ‘How Much Growth Can Borrows Sustain?”, George W Kester, 2002

In Figure 2 below we present the hypothetical financial statements of a professional services firm that bills time at rates that absorb payroll and other operating costs plus is sufficient to service debt and/or make investments in assets.

Figure 2 – Hypothetical Balance Sheet and P&L of Professional Services Firm

Source: “How Fast Can Your Company Afford to Grow,” Neil C. Churchill & John W. Mullins, Harvard Business School Publishing, 2001 and Gregg Carlson calculations/assumptions

Plugging numbers from the financial statements into the SGR model yields the following results:

Net Income/sales = profit margin of 5%

Sales/Assets = asset turnover ratio of $2,000/$682 = 2.93

Assets/Equity = leverage ratio of $682/$432 = 1.57[ii]

Equals ROE and SGR due to 0%/100% debt to equity = 23.00%

The model indicates that the revenue SGR is 23%, which means that growth rates above this number require better operational performance (profit margin and/or asset turnover = ROA) or changes to the capital structure (e.g. debt/equity issuance and/or increased earnings retention) in order to avoid cash deficits,  liquidity & working capital issues and/or a conversation with your banker. An entrepreneur, owner or CEO would need look at their realistic options in terms of operational performance, financing/capital structure options, asset sales/divestitures or mergers. On the other hand, entrepreneurs, CEO’s and owners who run enterprises at growth rates that are less than their sustainable growth rates face issues of slow growth, cash buildup and underutilized resources.

As an advisor to entrepreneurs, CEOs and business owners I have also used other model-analytical tools to address the above issues such as building explicit forecasts of company financial statements (P&L/Cash Flow/Balance Sheet) and  cash receipt/disbursement models(daily/weekly/monthly/annual)  to calculate liquidity needs and cash flows.

In addition to SGR model described above and explicit forecasts, I have found the operating cash cycle model to be a useful companion to explicit forecasts as well as a logical framework as a management and communication tool. 

It is well known that businesses require cash and growing businesses typically require more cash to fund working capital, operating expenses and investments in facilities and equipment. A key concern of growing businesses is to achieve a balance between generating and consuming cash. I have found that focusing on the operating cash cycle to be a useful approach to managing liquidity and determining the self financing revenue growth rate. The discussion here is based on an analytical framework described by Neil C. Churchill and John W. Mullins in a framework they developed for calculating the self financeable revenue growth rate of a business.[iii]

Churchill and Mullins state that a growing business can find itself out of business by outgrowing its cash resources. They address the issue by developing a calculation known as the self financeable growth rate (SFG). They develop a framework to determine what growth rate its current operations can sustain and define three model factors as follows:

1)      Operating cash cycle – the amount of time company money is tied up in inventory and other current assets before a company is paid for the goods and services it produces;[iv]

2)      Amount of cash needed to finance each dollar of sales, including working capital and operating expenses; and

3)      The amount of cash generated by each dollar of sales.

Like the Higgins SGR model described here, the Churchill and Mullins SFG framework goes beyond the calculation of sustainable revenue growth rates as a tool that provides insight into how operational efficiency, profit margins, product lines and customer segments can fuel revenue growth or not.

The operating cash cycle is a calculation of how many days cash is tied up in working capital before money is returned to the company in the form of customer payments for goods or services sold. The shorter the cycle the faster a company can redeploy its cash and growth from internal resources. In other words, the fewer days in receivables and inventory, the higher the turnover and the larger the number of days in payables, the better the SFR.

In addition to working capital, the SGR framework addresses how much cash is tied up in operating expenses by calculating how much is invested in operating expenses per dollar of sales and how long  the cash is tied up in the operating cash cycle.

The SGR framework also considers how much cash per dollar of sales flows to the bottom line and is available to fund the next operating cycle after being consumed by cost of sales and operating expenses.

Based on the above, an operating cash cycle (OCC) growth rate and the number of OCC’s can be calculated to arrive at an annual self financeable sales growth rate (SFG). In Figure 2 – Hypothetical Balance Sheet and P&L of a Professional Services Firm, I show the calculations described here as follows:

1)      Cash tied up per revenue/sales dollar in COS and operations adjusted for time (.40 +.08 =  .48);

2)      Cash generated per revenue/sales dollar (.05);

3)      Self financeable growth rate (SFG) calculation (cash generated by sales divided by cash tied up in operations) (.05 divided by .48 = 10.39% (SFG);

4)      Calculation of number of OCC’s per year (365 divided by OCC 166 = 2.198;

5)      Annual SFG is SFG (10.39%) x OCC’s per year (2.2 rounded) = 22.83%

The SFG is the sustainable rate at which sales/revenue can grow. If the business grows revenue at less than this rate, with all other variables held constant, the business will produce more cash that it will need to fund its growth. On the other hand, if its revenue growth rate is higher than its SFR, it will be strapped for cash.

Levers that the entrepreneur, business owner or CEO have for speeding up cash flow in a way to allow for increased SFR growth rates  while avoiding the use of external financing fall within the three areas and include; speeding cash flow through higher receivable and inventory turnover, reducing operating expenses and/or increasing prices and margins. In this model example I have not made adjustments for taxes, depreciation, asset replacement, major investments in R&D and marketing as well as differing cash and operating characteristics for different product lines within a business. In real life the entrepreneur, business owner or CEO will need to do so.[v] The model is capable of handling these inputs.

For an entrepreneur, business owner or CEO who must make liquidity influencing decisions such as what customer or projects to take on, where to price products/services vis-a-vis turnover/margins, what investments to make or dissolve, how large to let assets grow and what target returns to aim for, the models described here are helpful. In small businesses, I have seen the concepts described here managed by intuition in lieu of a formal process. Size, growth and complexity typically require more robust analytical and decision making processes. Bigger businesses I have been involved with have traditionally dealt with financial modeling of growth through an explicit forecasting process of profitability, cash flow and assets/liabilities/equity. In many of these cases, I used all or parts of these models to validate explicit forecasts. In other cases, I have used modeling concepts discussed here in lieu of explicit forecasts. The concepts modeled here have been used to advise and provide insight to entrepreneurs, business owners and CEO’s in support of business decision making processes.

I have used a professional services firm as an example to illustrate the concepts in the two models presented here. In the future, I will provide additional examples of how these and other related models might be used to analyze the growth rates and liquidity characteristics of businesses with varying financial models such as “asset heavy” hotels and casinos or companies with significant R&D investment in intellectual capital, among others.

For additional resources see the footnotes below.[vi]

                                                        

---

[i] Analysis for Financial Management, Sixth Edition, Robert Higgins, 2001

[ii] The model requires that beginning period equity be used for the calculation.  End of period equity of $532 and net income of $100 = $432 of beginning period equity as the model assumes no other changes in equity between the beginning and end of year.

[iii] The discussion of the operating cash cycle framework was sourced from, “How Fast Can Your Company Afford to Grow? Neil C. Churchill and John Mullins, Harvard Business School Publishing, 2001. The financial statement data and assumptions example used here are based on the article and then modified by Gregg Carlson as a hypothetical example of a professional services firm.

[iv] The components of the operating cash cycle include days of holding inventory, receivables and other current assets as well as days in accounts payable and other current liabilities to determine the length of time cash is tied up.

[v] For additional information here, see page 8 – 9 of the article, “How Fast Can Your Company Afford to Grow?, Neil C. Churchill and John Mullins, Harvard Business School Publishing, 2001.

[vi] For additional information on cash flows and liquidity issues see:

“Growth, Vitality, And Cash Flows: High-Frequency Evidence from 1 Million Small Businesses,” JP Morgan Chase Institute, September 2016;

“How Much Growth Can Borrowers Sustain?, George Kester, 2002 and was originally published in June 1991 in The Journal of Commercial Bank Lending;

“How Fast Should Your Company Grow?”, William E. Furman, Jr., Harvard Business Review, January 1984

Carson Valley Casino Market

I analyzed Nevada Gaming Control Board (NGCB) gaming abstract data between FY2013 and FY2017 for casino operators with gaming revenue greater than $1M to develop insight into the Carson valley casino market financial model. I reviewed market level financial statements and data points published by the NGCB. I also developed my own calculations as follows:

NGCB Data

Balance Sheet

Combined Income Statement

Casino Department Income Statement

Rooms Department Income Statement

Food Department Income Statement

Beverage Department Income Statement

Other Income Department Income Statement

Number of Employees by Year

Hotel Room Availability and Occupancy

Operating and Financial Ratios

My Calculations

Sources and uses of cash flow

Debt (leverage) metrics

EBITDA and free cash flow

Total labor costs as percentage of revenue

Slot volume and win trends by day and month

Overview of The Market

The market is primarily a gaming market as gaming revenue has comprised approximately 65% to total revenue for several years with the majority of gaming revenue being slot revenue (approximately 94% of total gaming revenue between January 2014 and April 2018). Within the slot department, approximately 70% of market level volume is generated by multi denominational games. Remaining revenue in FY2017 consists of room  (7.1%), food (15%), beverage (6.5%) and other revenue (6.3%). I characterize the market as a "market share market" due to the fact that overall market level revenue growth has been flat since FY2009 with the number of properties and hotel rooms being relatively stable for several years.

Profitability

For FY2017, total revenue less, cost of sales (13.1%), departmental expenses (44%) and G&A (35.4%) equaled pretax income of 7.5%. Departmental costs and margins were relatively stable between FY2013 and FY2016 resulting in pretax income of 4.8%, 2.4%, 3.8% and 5.6% indicating that operators operate in a low margin environment. The market generated positive EBITDA between FY2013 and FY2017 at a range of 10% to 13% .

Departmental profits are primarily generated by the casino department and essentially the slot department. Casino department profits dominate overall profitability as the casino department contributed between 91% to 95% of total property departmental income between FY2014 and FY2017. The biggest operating cost is labor cost as total departmental and G&A labor costs ranged between 21% to 22% and 9% to 10% of total revenues between FY2014 and FY2017.

Cash Flows

Carson Valley casinos generated cash flow from operations between FY 2014 and FY2017, invested in land & improvements, buildings, furniture & equipment, leasehold improvements and CIP while borrowing, as long term debt increased in FY2017 and FY2015 and decreased in FY2016 and FY2014. The market also generated free cash flow in each of FY2014 - FY2017, defined as net income plus depreciation before maintenance and general cap ex.

Balance Sheet

The balance sheet shrunk between 2007 to 2011 and remained relatively stable through FY2016 ($103.2m) before expanding to $114.2m in FY2017 primarily due to an investment in fixed assets. Working capital has been positive between FY2013 and FY2017 at a working capital ratio of 1.8 to 2.0 while cash has comprised approximately 16% to 20% of total assets. Debt to total capital has ranged between 47% to 60% between FY2013 and FY2017 while net debt to EBITDA has ranged between 1.7 x to 2.4x between FY2013 and FY2017. Interest coverage is 7.8x for FY2017 and has ranged from 5.3x to 7.1x between FY2013 and FY2016. Debt primarily consists of mortgage debt, debentures & bonds and notes.

Returns on Capital

Carson Valley casinos generated positive ROIC (8.5%, 10.3%, 14% and 17%), ROA (6.7%, 8.4%, 10.8%, and 13%) and ROE between FY2014 and FY2017. My DuPont ROE calculation (defined as net income divided by revenue x revenue to total assets x total assets to equity = ROE) indicates that between FY2014 and FY 2017 the majority of ROE is attributed to leverage based on total assets to equity levels (3x to 4x between FY2014 and FY 2017) as pretax operating margins were narrow (2.4% to 7.5% between FY 2014 and FY2017) and asset turnover declined (1.56x, 1.51x, 1.45x and 1.34x between FY2014 to FY2017).

Room Statistics

Occupancy in the market has run between 50% and 55% between FY2014 and FY2017 with trough to peak occupancy running between 32% and 72% between winter and summer periods. REVPAR has averaged $43, $38, $35 and $33 for FY2017, FY2016, FY2015 and FY2014 while the room supply has remained stable. Average slot, food and beverage revenue per room has remained stable between FY2014 and FY2017.

Recent Trends and Conclusion

Slot volume has increased since mid calendar 2017 through the latest NGCB data point, May 2018 resulting in an upward Y/Y trend in WPU creating the possibility of incremental top line revenue, flow through and margin expansion. See Figures 1 and 2 below. I will wait and see what is reported in the FY2018 NGCB abstract results. The results discussed here are based on aggregate numbers for 15 licensees with average assets of $7.5M and average revenue of $10.2M for FY2017.  Individual operators will perform better and worse than the averages and have stronger and weaker balance sheets, due to differences in business strategy, asset mix, management ability, property history and legacy issues, among other factors that affect casino financial models and results. The market has generated cash flow, pretax income, EDITDA and returns on capital despite flat top line revenue for several years. The market is expected to remain competitive and in a "market share mode." See below for FY2017 financial model data.

For a view of select data and charts that accompany this article see:

https://www.slideshare.net/GreggCarlson1/carson-valley-casino-market-financial-model-104134223?qid=7dc68030-c7ae-4a01-858f-fea9cbb3f521&v=&b=&from_search=1

Gregg Carlson

Housing Prices and Wages

The Economist magazine published a chart today that shows housing prices to average income for New Zealand, Australia, Britain, Canada and the United States (U.S.). The chart indicates that home prices are currently 30% to 60% above long-term averages for all of the countries listed except for the U.S. which appears to be close to it's long term average after hitting a low several years ago. 

The U.S. housing market is a big market with significant differences in individual cities and regions. Despite the overall market being near it's long-term price to income average, differences do exist in individual markets. Affordability and valuation appear to be issues in some markets.

Home prices to wages in Las Vegas (where I reside and write from today) have now reached 2007 levels of 8 to 9 years indicating that new homes have reached near peak historic valuation levels based on this metric. So this question is, can home prices go higher, will they go lower, etc. in the near future? The answer is unknown and bulls and bears have different opinions.

I recognize that this snapshot does not take into account the myriad of factors that affect wage growth and housing prices which include, household debt levels, population and demographic trends, consumer spending, business migration, employment trends and interest rates, among other factors. On the other hand, I have also found the relationship to be useful for thinking about valuation and forward looking expectations. I also know that housing prices have moved up at a faster rate than wages since the bottom which can continue, but not indefinitely, in my opinion.

Trump's Thesis on Jobs and Trade Restrictions

Trump says he will cancel trade agreements on his first day in office as his anti-trade approach to bring back jobs rhetoric is supported by his voters.

We live in interesting times as the Republican party has been pro trade and anti trade restriction since Ronald Reagan was President. We will see how this issue plays out as the interests of the business wing of the Republican party are at odds with Trump and his voters who believe he will bring back jobs through trade restrictions. His voters are likely to be disappointed.

In reading the research, I find no credible evidence that significant job growth will be created by trade restrictions and barriers. The research I am referring to leans Republican. I also looked at the evidence on this topic from multiple points of view. Trump's argument on this topic appears to be the least credible I can find.

For folks who lean right that are interested in learning more about free trade and jobs, I would recommend the most well known Republican leaning think tanks, The CATO Institute (CATO) and The Heritage Foundation (Heritage). These organizations extensively cover this topic and have published Republican leaning pro trade arguments and research for years.

It will be interesting to see how the battle plays out within the Republican party.

For folks who would like to go beyond CATO and Heritage on this topic, feel free to reach out to me.  

Costco - Mr. Market Miscalculates

The book title "Mr. Market Miscalculates," written by James Grant came to mind as I witnessed the strong positive market reaction to Costco's recent earnings release.(1) This came after the pros sold off Costco in earnest during recent weeks in front of the earnings release due to challenges reported by several other well known traditional land based retailers and the assumption that Costco was suffering a similar fate. The market misjudged Costco as reported results were better than expected. Costco indicated that customer behavior was unchanged.

My local store visits prior to the earnings release revealed no significant changes in visible metrics like store traffic and parking lot occupancy. Gasoline lines were also present as they have been for months. In short, I observed no change in a business with ongoing robust traffic and significant customer loyalty. Customer loyalty is apparent as evidenced by the consistent significant check out lines in my local stores and the published 90% membership renewal rate. As a customer you clearly understand why you renew each year which may or may not be the case for the professional money management crowd. If you own a piece of this business via the equity market it pays to know something about its competitive position, in my humble opinion. Being a customer is helpful on this front. If you are a friend of mine you already know that I am a customer and exhibit an obnoxious pride in ownership as I acquired my equity stake at just under $30 per share more than a decade ago. You also know that I have been a buyer in this stock for years. My latest buy before the earnings release was in the low $140's which meant that the market was pricing the equity near estimates of the intrinsic value of the company based on forward assumptions I was willing to bet on. Costco remains my biggest position.

In September 2015 I disclosed many of my holdings. I continue to hold onto most of the names mentioned although the position sizes have changed. Recent buys include Costco (discussed here) as well as Disney and Apple acquired post the most recent company earnings releases that disappointed Wall Street.



(1) James Grant, Mr. Market Miscalculates, November 2008