Sunday, August 19, 2018

Faber, The Best Investment Writing, vol. 2

If you didn’t read the first volume of Meb Faber’s The Best Investment Writing (and you should have and of course still can), you’re got another crack at learning from a lot of smart folks who collectively manage hundreds of billions of dollars. The second volume of The Best Investment Writing (Harriman House, 2018) includes more than 40 articles, and, since the book runs about 350 pages, the articles are bite-sized. Most of them originally appeared online and were geared to a semi-distracted readership, which increasingly describes all of us.

The articles are organized under four headings: market conditions, risk and returns; investment portfolios, strategies and edges; pricing and valuation; and personal finance, behavioral biases and beyond.

Here I’ll recap two articles that appealed to me and that lent themselves to summary. The second criterion ruled out many excellent contributions. For instance, trying to summarize Barry Ritholtz’s “An Expert’s Guide to Calling a Market Top: The landscape is filled with pundits predicting the demise of the bull market. Here’s how to get in on the action” would be like trying to summarize a Letterman top-10 list. The task would simply produce a pale imitation of the original.

And so, to the two articles I chose. First, “10,000 Hours or 10 Minutes: What Does It Take to Be a ‘World-Class’ Investor?” by Charlie Bilello, originally published on the website of Pension Partners. From the title you can surmise that Bilello will debunk the applicability of the 10,000-hours rule to trading/investing. He argues that luck trumps skill in investment outcomes and that, in looking at the successes of the market wizards of years past, we can’t determine with certainty whether their performance was the result of skill or luck. More important, “even if we concluded that there was some skill involved, doing x, y, and z because a ‘market wizard’ did x, y, and z in the past is a guarantee of nothing. …the environment they operated in no longer exists. … If the wizards themselves were faced with the task of repeating their prior successes, they too would fail—Warren Buffett would not be the next Warren Buffett if he had to start over again today. Paul Tudor Jones would not be the next Paul Tudor Jones. Stanley Druckenmiller would not be the next Stanley Druckenmiller.” The average investor should simply spend ten minutes learning about controlling costs, diversification, and asset allocation. “In a field where the outcome is driven more by luck than by skill, being a master of nothing (diversifying and protecting yourself from the unknowable future) yields the highest probability of success.”

Second, Samuel Lee’s “Waiting for the Market to Crash Is a Terrible Strategy.” We hear over and over that we should be fearful when others are greedy and greedy when others are fearful. But is this really so? Lee shows that putting cash to work in the market only after a crash has been “an abysmal strategy, far worse than buying and holding in both absolute and risk-adjusted terms.” Using monthly U.S. stock market total returns from mid-1926 to the end of 2016, he simulated variations of the “buy after a crash” strategy, “changing both the drawdown thresholds [from -10% to -50% in increments of 5%] before buying and the holding periods [from 12 to 60 months] after a buy.” In all cases the strategy failed. The reasons? “First, the historical equity risk premium was high and decades could pass before a big-enough crash, making it very costly to sit in cash. Second, the market tended to exhibit momentum more than mean reversion over years-long horizons. As strange as it sounds, you would have been better off buying when the market was going up and selling when it was going down, using a trend-following rule.”

Wednesday, August 15, 2018

Bova, Growth IQ

In Growth IQ: Get Smarter about the Choices That Will Make or Break Your Business (Portfolio/Penguin, 2018) Tiffani Bova regales the reader with stories about 30 companies to demonstrate what she considers to be the only 10 paths to growth. Although this book is written for entrepreneurs and managers, it’s a worthwhile read for investors who want to assess the growth strategies of companies on their radar screen.

Without the stories, the paths to growth—customer experience, customer base penetration, acceleration, product expansion, customer and product diversification, sales optimization, churn, partnerships, co-opetition, and unconventional strategies—would seem either abstract or, in many cases, obvious. Moreover, taken in isolation, they probably wouldn’t even work. As Bova writes, “It isn’t enough to have the ‘right’ new growth strategy. You must fully understand what the current market context is prior to making any moves.” And then you need to select key actions that can positively influence outcomes and establish a priority, order, and timing to those actions. In sum, “Growth IQ is a holistic approach to finding the right path, in the right market context, in the right combination and sequence—creating a multiplier effect that is far more powerful than just focusing on one or two efforts in isolation.”

Almost all of the companies Bova writes about are publicly traded, though not all of them are stock market darlings. Some companies, such as Sears, Blockbuster, Wells Fargo, and Blue Apron, are fodder for cautionary tales. Even those that Bova selected to illustrate a particular path to growth may not have executed especially well in another domain, at another time.

Growing a company is not a mechanical exercise, as Bova points out again and again in her examples. But intelligently pursuing multiple paths to growth will pay off. “Amazon has pursued all ten possible growth paths in little more than two decades.” It is “the very embodiment of Growth IQ.”

Wednesday, August 8, 2018

Effron, 8 Steps to High Performance

We all start our careers with attributes (e.g., intelligence, personality, physical attractiveness) and socioeconomic backgrounds that are “largely unchangeable once we become adults.” These combined items “predict up to 50 percent of anyone’s individual performance” and give some people a clear advantage over others. But that leaves the other 50+ percent that people can control and shape at will.

In 8 Steps to High Performance: Focus on What You Can Change (Ignore the Rest) (Harvard Business Review Press, 2018) Marc Effron shares “scientifically proven” things you can do to help yourself be a high performer. They are, in a nutshell: (1) set big goals, (2) behave to perform, (3) grow yourself faster, (4) connect, (5) maximize your fit, (6) fake it, (7) commit your body, and (8) avoid distractions.

These behaviors have been shown to work within a corporate environment. They are not necessarily behaviors that propel people to be successful entrepreneurs, not even behaviors that top CEOs exhibit. For instance, top performing CEOs seem to be high on general ability (fast, aggressive, persistent, efficient, proactive, high standards) and low on interpersonal skills (respectful, open to criticism, good listening skills, teamwork). But, writes Effron, “if you’re not already at the top, I’d suggest that both great results and great interpersonal behaviors are essential ingredients for high performance.”

“Grow yourself faster” is a step worth pausing at. “[R]oughly 70 percent of your professional growth will come from the work experiences you have, 20 percent will come from your interactions with others, and 10 percent will come from formal education.” Formal education “that may seem critical to success often isn’t. Only thirty-nine Fortune 100 CEOs have an MBA, and many of those leaders didn’t earn them at top-ranked schools.” (And, yes, this book was published by a wholly-owned subsidiary of Harvard University that reports to the Harvard Business School.)

Growth, Effron contends, is “a cycle—perform, get feedback, perform again better…. The faster and more often you move through that cycle, the faster you’ll develop and get the next opportunity to learn a new skill, test a new behavior, and get more helpful feedback. Each cycle you move through should make you more competent and more competitive.”

Effron’s chapter on how you can prime your body to perform better at work is something of a myth buster. “Surprisingly little science,” he writes, “makes a direct link between our bodies and individual high performance at work. The science that does exist says that sleep matters most, exercise has some minor and specific effects, and diet has no direct effect. That doesn’t mean that exercise and diet don’t matter in your life, but neither has much power to boost your performance at work.” As for sleep, quality impacts performance more than quantity.

The final step, avoid distractions, is not about smart phones and email. Instead, Effron tells the reader to “avoid the fads that distract you from what’s scientifically proven to improve your performance. Many of these fads present advice that would seem to make your life easier (focus on your strengths), quickly increase your performance (adopt a growth mindset), or give you instant self-confidence (strike a power pose).” But this advice is misguided. For instance, focusing on your strengths “will help you be better at the exact same things you’re good at today, but won’t help you to be good at anything else.”

“If you want to accomplish more than you thought you could or break through a performance barrier,” the author concludes, don’t follow fads but follow the eight steps given in this book.

Wednesday, July 18, 2018

Rees, Principles of Financial Modelling

In the old days banks wanted applicants to be comfortable with Excel. Now they’re upping the ante. Citi, for instance, wants its incoming investment bank analysts to know Python. But Excel hasn’t gone the way of the dodo. It’s still incredibly useful for a range of financial tasks. The problem is that most Excel users have no idea how to go beyond basic formulas and engage the program as a high-level tool. In Principles of Financial Modelling: Model Design and Best Practices using Excel and VBA (Wiley, 2018) Michael Rees sets out to fill this void.

Rees’s more than 500-page book is divided into six parts: (1) introduction to modeling, core themes and best practices, (2) model design and planning, (3) model building, testing and auditing, (4) sensitivity and scenario analysis, simulation and optimization, (5) Excel functions and functionality, and (6) foundations of VBA and macros. As these part titles indicate, Rees first addresses financial modeling, from design to optimization, and then explains how to use Excel and VBA to implement the models. Complementary to this book is a website, which contains 237 Excel files.

Here, to give a sense of the book, I will summarize Rees’s distinction between database and formula-driven approaches to modeling.

Traditional models, for instance those used for cash flow valuation, are formula-focused. They “often have a small set of numerical assumptions, from which large tables of calculations are performed. Certainly, where a single value is used for an assumption across multiple time periods (such as a single growth rate in revenues that applies to all future time periods), arbitrarily large tables of calculations may be generated simply by extending the time axis sufficiently, even as the number of inputs remains fixed.”

Where a large volume of data is required, however, the appropriate model will use “database concepts, functionality or data-oriented architectures and modular structures. These include the structuring of data sets into (perhaps several) contiguous ranges, using a column (field)-based approach for the model’s variables (with well-structured field identifiers, disciplined naming conventions, and so on).”

Even though in practice these two approaches to modeling can sometimes overlap, with the modeler confronted with both large data sets and potentially many formulas, Rees contends that “at the design stage, the reflection on the appropriate approach is fundamental: an inappropriate choice can lead to a model that is inflexible, cumbersome and not fit for the purpose.”

Before they set out to build models in Excel, analysts would do well to read Rees’s book. With its help, they will avoid many pitfalls.

Friday, July 13, 2018

Hall, A Carnival of Losses

I’m getting to the age that I read things about getting old. Not the advice that AARP sends out but essays by writers who are comfortably ahead of me on the march to 100. Donald Hall, the former poet laureate, delivered two such volumes of late, Essays After Eighty and A Carnival of Losses (Houghton Mifflin Harcourt, 2018), the latter written as he was nearing 90. (Hall died last month, on June 23.)

Essays After Eighty addressed old age more expansively, and humorously, than A Carnival of Losses. The new book has qualities of leftover stew: warmed-up reminiscences and bits and pieces that were probably in the literary root cellar, such as his recollections of poets. It’s still a delightful read, but if I were to recommend only a single title, it would be Essays After Eighty.

Wednesday, July 11, 2018

Govindarajan & Ramamurti, Reverse Innovation in Health Care

I got an advance reader’s copy of Reverse Innovation in Health Care: How to Make Value-Based Delivery Work (Harvard Business Review Press, 2018) by Vijay Govindarajan and Ravi Ramamurti. I put it aside, thinking that it was not within the scope of this blog. But then came the tornadoes that struck Connecticut, one of which touched down far too close for comfort, on May 15. My property (fortunately not the house) was devastated, with large uprooted trees all around the house and the edges of the property and the top of one mighty oak pinning, and miraculously only denting, the car sitting in the driveway. Naturally, I had no power for days, and no Internet access for days more. And so, with my usual routine upended as well, I turned to this book.

The book’s premise is that U.S. healthcare providers can learn from models that have been successful in India. The authors are not, of course, touting Indian healthcare as a whole, which is sorely wanting. But one hospital system in particular, Narayana Health, could serve as an exemplar.

Founded by Dr. Devi Shetty in 2001 with a vision to treat all patients regardless of their ability to pay, Narayana Health is now a profitable company that offers, most notably, open-heart surgery (which would normally cost between $100,000 and $150,000 in the U.S.) to paying patients for $2,100 and to subsidized patients for $1,307. The hospital’s cost for each surgery is $1,100 to $1,200. Narayana is now doing about 14,700 cardiac surgeries a year. On average, in 2016-17 Narayana’s cardiac surgeons performed two to three times as many open-heart surgeries as their U.S. counterparts. And their outcome metrics rival those of the best hospitals in the world.

Shetty is a ruthless cost-cutter, as long as cutting costs doesn’t negatively impact quality of care. To construct Narayana’s no-frills hospitals, for example, costs about half that of its competitors. And when Shetty wanted to buy disposable surgery gowns and drapes from multinational suppliers who refused to budge on price, he had them stitched locally. Within four years, this firm became the largest manufacturer of disposable surgical gowns in India. The multinationals, unable to compete on price, left the market.

Narayana has innovated through task-shifting, allowing surgeons to do three operations in the time it takes other hospitals to do one. “[E]very motion in the operating cycle is choreographed to reduce turnaround time and optimize pay grades.” Senior surgeons do little or nothing that can be done by lower-paid, less-skilled staff.

In perhaps the most striking instance of task-shifting, in Narayana’s multispecialty hospital in Mysore, family members provide much of the post-ICU care. Since, in India, the entire family comes to the hospital with the patient and typically spends three days there, Narayana upgraded them from “underfoot” to caregivers. They get instruction from a four-hour video curriculum. “The practice of training families for in-hospital postoperative care not only frees up the nursing staff for other work but also eases the transition to reliable, high-quality home care, reducing readmissions by 30 percent.”

Narayana uses a hub-and-spoke model and, through farming cooperatives in Shetty’s home state, instituted an insurance plan to reach out to underserved villages. By 2017 the insurer had four million members who, for 22 cents a month, could get free treatment at 800 network hospitals across the state for any procedure whose cost did not exceed $2,200.

Shetty is also starting to pursue opportunities in telemedicine.

The authors highlight four new models in or near the United States that use some of the Indian tactics: Health City Cayman Islands (founded by Narayana Health), University of Mississippi Medical Center, Ascension, and Iora Health. All of these are making strides in trying to change the American healthcare system from the bottom up.

Reverse Innovation in Health Care offers ways for U.S. healthcare to save billions without compromising (indeed, perhaps with improving) quality. And it’s not simply on the back of low wages. The authors address a series of questions that skeptics raise to show that aspects of the model would be viable in the United States. As such, it’s an essential read for anyone who is prepared to tackle the change-resistant healthcare establishment.

Wednesday, June 27, 2018

McNally, The Promise of Failure

Why write? Especially when, in most cases, the writer faces rejection of one sort or another. This is the question John McNally raises in The Promise of Failure: One Writer’s Perspective on Not Succeeding (University of Iowa Press, 2018). Although McNally is addressing writers and would-be writers (of whom I am decidedly not one), his thoughts on failure can sometimes be generalized.

So, again, why write? “If no one out there cares if you put down your pen right now and never pick it up again, why keep doing this thing that you’re doing?” One reason is that “it’s the only thing [you’re] even remotely good at.”

So you keep writing and “putting [your] work out there,” even though you “ultimately have no control over whether something gets published or doesn’t…. It’s like letting go of a helium-filled balloon and hoping it touches an airplane. Once you let go of the string, it’s no longer in your control.” What a wonderful image for the disjunction between process and outcome. Once you hit the buy or sell button…. No, I don’t want to mash McNally’s language by forcing an analogy.

When, in the face of failure, should you just pack it in and quit doing what you’re doing? McNally says that he has “always been of the belief that as long as you’re not hurting anyone, it’s foolish not to pursue the thing you want to pursue, even if you pursue it badly.” Here it’s more difficult to analogize to trading. The writer piles up rejection slips; the trader piles up losses. Losses may not be psychologically more difficult to handle than rejection slips, but they do have a way of eroding any semblance of well-being. The losing trader either has to find some way to be profitable (and many highly successful traders have clawed their way back from nothingness) or should find something else to pursue.

But if you’re going to pursue trading, here’s McNally’s advice (and in this case it’s easy to analogize): “I measure my goals not by a typed page, not by a paragraph, not by a sentence. But by a word. One word. Because I know well enough now that one word will lead me to the next word and that this is how you get to where you’re going.”