Objective judgement, now at this very moment,
Unselfish action, now at this very moment,
Willing acceptance, now at this very moment, of all external events.
That is all you need.
To me that captures the three disciplines (perception, action, will) very nicely. It tells you how to see the world, how to act in the world, and how to come to terms with the world. It is indeed all one needs. You could spend a lifetime trying to just live that quote.
Understanding Stoic Philosophy may help you as an investor maintain rationality, control unwanted emotional reactions, and develop clear thinking for better choices which is, after all, what investing is all about.
The essense of philosophy is that we should live so that our happiness depends on as little as possible on external causes. –Epictetus
Pitching an investment idea is the life-blood of Wall Street analysts —whether at money management firms and investment banks or with CEOs to potential investors. Those who do it well win, and win big. Sonkin and Johnson teach professional analysts, sophisticated private investors and ambitious young analysts how to uncover the perfect investment and pitch it to critical decision makers, to advance their careers and increase their wealth.
No other book like this one exists. There are plenty of books that focus on investment strategy, company analysis and critical thinking. Yet, there is no book that combines investment analysis with persuasion and sales – in Wall Street vernacular—pitching. In our increasingly competitive world, being able to pitch your idea is becoming as critical as being able to find and analyze great investment opportunities. It is imperative to get clients or superiors to take action on your ideas. The teaching of this skill is sorely lacking on Wall Street. Pitching the Perfect Investment will present a two-step process: 1) finding the perfect investment; and 2) crafting the perfect pitch. The book will show that to be successful the reader will require two very different skill sets: the first is investment analysis and decision making; and, the second is persuasion and sales.
Pitching the Perfect Investment presents world-class insights into search strategy, data collection and research, securities analysis, risk assessment and management, combined with the use of critical thinking, to uncover the perfect opportunity for professional analysts, sophisticated private investors and ambitious young analysts as well as mergers and acquisition specialists advising clients, financial consultants and corporate financial analysis teams. Pitching draws from the disciplines of psychology, argumentation and informal logic. It instructs the investor analysts of all types how to craft this perfect investment into the perfect pitch. Pitching an investment is an essential skill to securing and then excelling at your job on Wall Street.
This is an essential skill for the ambitious young investment analyst looking to begin a career on Wall Street as well as the seasoned veteran discussing an idea on CNBC, and every investor in-between.
Aspiring analysts should be aware of this book, but I am not recommending since I have not read it. Common-sense writing helps. Clearly state your thesis then provide supporting facts and risks. Done. But if you can’t state your case to a child in less than a paragraph, then go back to your desk.
For example, Navigator Holdsings (NVGS) has a dominant position in handy-size petrochemical transportation and it trades at 55% of net asset value, its balance sheet and flexible fleet allows it to be profitable despite a perfect storm in the LPG shipping market. One of the most famous value investors, Wilbur Ross bought into NVGS at an average price of $8.73 over three years ago for a 50% stake. NVGS is now 20% below that price. The current lows in freight rates due to A, B, C are unsustainable due to 1, 2, 3, therefore normalized rates will mean much higher values. Timing is, of course, uncertain, but there are considerations for building more US ethylene plants for export. NVGS has the dominant position for transporting that product which requires special handling (super low temperatures and pressure). Price is about 50% below asset value and earnings power value.
Manny introduced himself to me as “the world’s greatest stock picker.” He explained that one key to his success was that he only needed two hours of sleep a night. He pored over details in every significant financial publication and in those quiet morning hours when all others slept, he let information percolate. By the morning he had brilliant new insights into the industries and companies that were poised to outperform over the following months. Some of the world’s top fund managers subscribed to his research, he told me.
I asked if his clients knew he was housed in prison, in solitary confinement. He explained that of course they didn’t, and he asked that I kindly keep his secret. He distributed his stock research through his secretary, who kept his office open.
In the intervening days I checked out Manny’s story. Much was true – he was in fact publishing highly-regarded financial research to large AUM clients from prison.
On the surface his research analysis sounded brilliant – the creative ramblings of an out-of-the-box Wall Street-obsessed thinker. But as we talked in depth it became clear that his thought process was laced with irrational and circumstantial connections. He was often confusing wishful thinking with objective analysis. He was hypomanic, with grandiose claims and excessively optimistic projections.
As a psychiatrist I’ve worked with many people with grandiose delusions. In each case the client has fixed beliefs that are contrary to reality – beliefs that guide much of their waking actions – beliefs that are entirely untrue. Delusions aren’t limited to manic prisoners, in fact we spend most of our days navigating the world based on assumptions, many of which are entirely unfounded. Because the financial markets are imbued with uncertainty, assumptions are more dangerous in that environment. Regardless of the fragility in our collective understanding of markets, there are enormous payoffs for those who can discern reality more accurately.
In fact, academic research on trading models finds that most are delusional. “Most of the empirical research in finance, whether published in academic journals or put into production as an active trading strategy by an investment manager, is likely false.” ~ Campbell Harvey and Yan Liu, “Evaluating Trading Strategies,” 2014
This quote is particularly relevant to us at MarketPsych because we are restarting our trading business. We’re currently trading a unique media-based machine learning strategy and re-registering as an investment adviser. It has been a long road to find a strategy worth deploying capital into, and based on our prior experience, trading delusions can easily become enshrined in predictive models.
Today’s newsletter examines the nature of false beliefs among investors, how beliefs shift (with an Amazon case study), honest investment strategy development, and examines what, if anything, we can do to find the truth about what moves markets.
When Delusions Crack – Brick and Mortar Retailers
“Lose your smile and lose your customers.”
~ Sam Walton
(The following was written by our own Tate Hayes and a longer version will appear in Investopedia this weekend.)
Nordstrom’s and Macy’s have both seen a 50% drop in stock price over the last year on the back of deceasing revenues. Wal-Mart and Best Buy shares have taken just under a 10% hit over the last 12 months. In contrast, Amazon’s stock price is up almost 70% in the last year and 135% in the past two years.
Investors’ beliefs about the retail sector have changed dramatically in the past 2 years. In examining media optimism data since July 2014, a clear decline is evident. Over the last 24 months, investors became more optimistic about Amazon, but increasingly pessimistic about a number of the top brick-and-mortar retailers (Wal-Mart, Nordstrom, Macy’s, and Best Buy are charted below). The media sentiment of these individual companies are compiled in the Thomas Reuters MarketPsych Indices (TRMI). The TRMI Optimism index represents the frequency of positive, future-tense references about a company verses those that are negative in millions of articles daily from thousands of news and social media sources. The 200 day-averages of media optimism about each retailer are plotted in the chart below.
What is remarkable is both how long the delusion of bricks-and-mortar retailer safety stayed afloat, and also how quickly it is unraveling as optimism about the individual retailers plummets. First optimism about Amazon rose, and then, on cue, optimism about bricks-and-mortar retailers declined.
Throughout the twentieth century, a variety of stock market leading indicators achieved notoriety. The Super Bowl indicator was oft-cited in media. It was so-called because the U.S. stock market was said to rise in years that an NFL team won the American football Super Bowl. This indicator was 90 percent accurate in predicting the annual stock market direction from 1967 to 1997. However, the Super Bowl indicator is a random coincidence, the result of overfitting to a limited data set. Such spurious correlations are often repeated in the media and by the statistically illiterate.
As we are seeing in the U.S. election cycle, in politics there is an advantage to sincere assertions of half-truths and lies. But in scientific disciplines like healthcare and (aspirationally) finance, objective truth is the bedrock of all subsequent activity. In 2005, Dr. John Ioannidis wrote an academic article that has become the most widely read paper on PLoS One (Public Library of Science) and the first to surpass one million views. The paper contains a proof that the majority of published medical research results are false positives (i.e., untrue).(1) Dr. Ioannidis’s statistical insights have been extended to finance by Marcos Lopez Del Prado, Campbell Harvey, Yan Liu, and others.(2,3,4,5).
If a test result is considered true at a 95 percent confidence interval (two sigma), then that confidence interval must be expanded as additional tests are performed on the dataset to achieve a simile level of confidence that the result is not a random coincidence. Yet with massive data sets available, statistical overfitting is inevitable.
It is tempting to believe in strategies that do not meet solid statistical thresholds because (1) it is difficult to find novel and outperforming investment strategies, and (2) the thrill of thinking one might have found such a strategy is more compelling than the repeated frustration of intellectual honesty. The incentive to find a good result often leads to short-cuts in testing hygiene and spurious correlations.
Essential to identifying useful predictive relationships in data is to adopt techniques to achieve statistical confidence in positive findings. Also important is to understand the probable rationale – the underlying assumptions – for the findings. Amidst so much hype, how can we know what is real?
Our Own Trading
“With four parameters I can fit an elephant, and with five I can make him wiggle his trunk.”
~ John von Neumann, a brilliant mathematician who among many other accomplishments founded the field of game theory (8)
While trading MarketPsych’s hedge fund, we adopted numerous datamining hygiene techniques, including: rigorous data exploration of the training set only; using multiple out of sample sets and k-fold cross-validation; utilizing universal concepts and language in our ontologies; visual inspection of output; and using a human filter to exclude strategies that are not empirically supported or based on “common sense.” We are confident in the validity of our statistical hygiene and testing techniques because of these efforts to debias.
However, without real-time performance and common-sense explanations, it is difficult to establish the robustness of quantitative investing strategies. To address these concerns, we have (1) an independently audited track record from our hedge fund, (2) live forward tested strategies launched online in 2013, and (3) empirical support for the validity of our strategies from psychological research. Each of those factors increases confidence, but nonetheless, modeling is very difficult to get right. Our equity curve is below.
As markets recovered from the financial crisis, our fear-based trading strategy was no longer suited to the positive momentum of prices. Yet we did not successfully pivot on the strategy, and we shut down the fund.
We have a new strategy being traded currently, and it is adaptive – as media delusions shift, it compensates. This strategy appears less vulnerable to regime changes, but it’s not open for outside investors yet.
Among traders the most common techniques for establishing the statistical validity of a finding include data division into training/test/out-of-sample sets and k-fold cross-validation. When data is divided into sets, typically 60% of the data is used for feature selection (identifying the best indicators), while 20% is used for testing to verify that the findings in the training set hold true in data that was “blinded”. Then once the model has been tweaked and risk management set on the training and testing sets, the model is run on the out-of-sample set to verify that it still holds true.
K-fold cross-validation is another technique for verifying the predictive value of a trading system. After studying the performance of indicators on an external training set (maybe 30% of the study data), and selecting the best, then the testing set (60%) and training set (90% of alll data) are utilized for cross-validation. If k = 10%, then the data set is divided into deciles. The overall model is learned on 90% of the data and tested on 10%. The 90% and 10% data sets are randomized each pass and dozens of passes are performed. The range of performance on each 10% set gives an approximation of the model’s stability. If the model is declared useful, then a final 10% study is performed on the final out-of-sample set to verify the model’s value.
In all cases of developing trading models, it also helps to watch real-time trading on paper first and then to forward-test with a small amount of real money before going live.
Housekeeping and Closing
I met Manny well before the financial crisis while I was working part-time in a prison (to fund the launch of MarketPsych). His optimistic research tone reflected the mood of the times. Many of the popular Wall Street delusions are simply beliefs that fit the current social mood.
Eventually I asked Manny, “Do your clients know you’re manic?” He replied “Of course not!” He was trying to milk his manic energy for all he could by producing as much research as possible to pay for his legal bills. I haven’t kept track of Manny, so I don’t know if he saw the financial crisis coming or how his life turned out. Nonetheless I wish him well.
We love to chat with our readers about their experience with psychology in the markets. Please send us feedback on what you’d like to hear more about in this area.
If you represent an institution, please contact us if you’d like to see into the mind of the market using our Thomson Reuters MarketPsych Indices to monitor real-time market psychology and macroeconomic trends for 30 currencies, 50 commodities, 130 countries, 50 equity sectors and indexes, and 8,000 global equities extracted in real-time from millions of social and news media articles daily.
Keep It Real,
The MarketPsych Team
1. J. P. Ioannidis, “Why Most Published Research Findings Are False,” PLoS Medicine 2, e124 (2005), pp. 694–701.
2. M. López de Prado, “What to Look for in a Backtest,” Working paper, Lawrence Berkeley National Laboratory, 2013, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2308682.
3. Harvey and Liu, “Evaluating Trading Strategies.”
4. C. R. Harvey and Y. Liu, “Backtesting,”Working paper, Duke University, 2014a. Available at http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2345489.
5. David H. Bailey, Jonathan M. Borwein, and Marcos Lopez de Prado, and Qiji Jim Zhu, “The Probability of Backtest Overfitting” Journal of Computational Finance (Risk Journals), (February 27, 2015). Available at SSRN: http://ssrn.com/abstract=2326253
6. Attributed to von Neumann by Enrico Fermi, as quoted by Freeman Dyson in “A meeting with Enrico Fermi” in Nature 427 (22 January 2004), p. 297.
YSSA’s Value Investing Thought Leadership Group presents
NYSSA Author Series™:
Monday August 22, 2016 6:00 PM through 8:00 PM NYSSA Conference Center
Available as: Live Session Categories: Market Integrity, NYSSA Author Series™, Programs for Members, Seminar, Value Investing
Deep Value: Why Activist Investors and Other Contrarians Battle for Control of Losing Corporations” is a must-read exploration of the deep value investment strategy, describing the evolution of the theories of valuation and shareholder activism from Graham to Icahn and beyond. The book combines engaging anecdotes with industry research to illustrate the principles and methods of this complex strategy and explains the reasoning behind seemingly incomprehensible activist maneuvers. Written by an active value investor, Deep Value provides an insider’s perspective on shareholder activist strategies in a format accessible to both professional investors and laypeople.
The Deep Value investment philosophy described by Graham is rarely available in the modern market, forcing activists to adapt. Current activists exploit a much wider range of tools to achieve their goals. Deep Value enumerates and expands upon the strategies available to value investors today and describes how the economic climate is allowing value investing to re-emerge.
This event will cover:
Strategies and tactics of effective activism
Unseating management and fomenting change
Determining advantageous strategies
Eyeing conditions for the next M&A boom
Who should attend?
Portfolio Managers and Analysts
Tobias Carlisle is the founder and managing director of Carbon Beach Asset Management LLC. He is best known as the author of the well regarded website Greenbackd, the book Deep Value: Why Activists Investors and Other Contrarians Battle for Control of Losing Corporations (2014, Wiley Finance), and Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors (2012, Wiley Finance). He has extensive experience in investment management, business valuation, public company corporate governance, and corporate law. Prior to founding Eyquem in 2010, Tobias was an analyst at an activist hedge fund, general counsel of a company listed on the Australian Stock Exchange, and a corporate advisory lawyer. As a lawyer specializing in mergers and acquisitions he has advised on transactions across a variety of industries in the United States, the United Kingdom, China, Australia, Singapore, Bermuda, Papua New Guinea, New Zealand, and Guam. He is a graduate of the University of Queensland in Australia with degrees in Law (2001) and Business (Management) (1999).
NYSSA expects all attendees to comply with NYSSA’s Code of Conduct while attending NYSSA events or meetings. NYSSA expressly reserves the right, in its sole discretion, to grant or deny access to any individual, or to expel any individual from any NYSSA event or meeting.
New York University’s School of Professional Studies is offering an online class focused on the time-honored techniques of value investing, as practiced by the world’s most legendary investor, Warren Buffett. We thought you might be interested in knowing more about this class, and perhaps in sharing this information with your readers.
By examining case studies of Buffett’s acquisitions, students will explore the real-world principles that Buffett uses to pick companies. The class starts April 2nd and is open to the public for registration.
For more information, please see the attached press release.
John Chew (Editor, csinvesting.org) I am not endorsing this class per se because I don’t know the professor or the details of the course material, but for those of you who seek a more structured learning experience then perhaps this class is for you. Let me know if you take the class, so I can share your experience with others. Also, remember that if you use the search box at csinvesting.org, you can find dozens of Buffett case studies for FREE.
Just remember that trying to copy Buffett will NOT work, but applying the Buffett principles of investing to YOUR OWN methodology will help you. Be the BEST YOU can be not a second-rate copy of another.
he following quote from C. Edward Griffin tells the little known story how dollars are created.
The Mandrake Mechanism
The American dollar has no intrinsic value. It is a classic example of fiat money with no limit to the quantity that can be produced. Its primary value lies in the willingness of people to accept it and, to that end, legal tender laws require them to do so. It is true that our money is created out of nothing, but it is more accurate to say that it is based upon debt. In one sense, therefore, our money is created out of less than nothing. The entire money supply would vanish into bank vaults and computer chips if all debts are repaid. Under the present System, therefore, our leaders cannot allow a serious reduction in either the national or consumer debt. Charging interest on pretended loans is usury, and that has become institutionalized under the Federal Reserve System. The Mandrake Mechanism by which the Fed converts debt into money may seem complicated at first, but it is simple if one remembers that the process is not intended to be logical but to confuse and deceive. The end product of the Mechanism is artificial expansion of the money supply, which is the root cause of the hidden tax called inflation. The expansion then leads to contraction and, together, they produce the destructive boom-bust cycle that has plagued mankind throughout history wherever fiat money has existed.
The Santangel’s Investor Forum invites eligible students to apply to receive a free ticket to attend the 2015 Forum, to be held in New York City on October 22, 2015.
A benefactor who wishes to remain anonymous has endowed a table at the upcoming conference to enable a select number of talented students to attend the annual invitation-only event.
All enrolled undergraduate and graduate students are eligible. Interested candidates should apply by emailing their resume and a current investment idea write-up to Steven Friedman (email@example.com). The idea can be for any type of security or asset class, but the write-up must be limited to 300 words. Preference will be given to unique and original ideas. Please submit ideas by September 15, 2015.
Please feel free to pass this along to anyone who may have an interest.
We skip Chapter Six (for now) and focus on Chapter 7 in DEEP VALUE: Catch a Falling Knife: The Anatomy of a Contrarian Value Strategy
In Search of Un-Excellence
The authors identified 36 publicly traded “excellent companies” on the basis of out-performance in six criteria, measured from 1961 to 1980.
Return on total capital
Return on equity
Return on sales
Market to book value
Then an investment analysts, Michelle Clayman, identified 39 publicly traded “un-excellent companies” which ranked in the bottom third of all Peters and Waterman’s criteria from 1976 to 1980. These “in search of disaster” companies outperformed 24.4% pa over five years vs. 12.7% for the “excellent” companies.
The good companies under-perform because the market overestimates their future growth and future return on equity and, as a result, accords the stocks overvalued price-to-book ratios; the converse is true of the poor companies.
Over time, company results have a tendency to regress to the mean as underlying economic forces attract new entrants to attractive markets and encourage participants to leave low-return businesses. Because of this tendency, companies that have been good performers in the past may prove to be inferior investments, while poor companies frequently provide superior investment returns in the future.”
Note pages 128 to 136 in DEEP VALUE: Tables 7.1 to 7.9
Stocks in the Contrarian Value portfolios were cheaper than the comparable Glamour portfolios on every metric but on a Price-to-Earnings basis, possibly because the earnings in those portfolios were so weak.
First, valuation is more important than growth in constructing portfolios.
Cheap, low growth portfolios systematically outperform expensive, high-growth portfolios, and by wide margins. It seems that the uglier the stock, the better the return, even when the valuations are comparable. Oppenheimer found in a study on Ben Graham Net/Nets that loss making and non-dividend paying net/nets outperform profitable, dividend-paying net/nets. Ben Graham Net Current Asset Values A Performance Update
In almost any study, the cheap, hated, ugly, least-admired, and poorly performing stock outperforms the high-growth, glamour stocks.
What these studies demonstrate is that mean reversion is a pervasive phenomenon, and one that we don’t intuitively recognize. Our untrained instinct is to pursue the glamorous stock, the high-growth stock, the story stock, the excellent stock, the admired stock, the A+ stock, or even the profitable net net, but study after study shows that this instinct leads us to under-perform. Buying well-run companies with good businesses at bargain prices seems to make even more sense. The research shows , however, that the better investment–rather than the better company–the value stock, the scorned, the unexcellent, the Ds, the loss-making net nets. And the better value stock, according to Lakonishok, Shleifer, and Vishny’s research is the low-no-growth value stock, what they describe as “contrarian value,”
What is clear is that value investing in general, and deep value (buying the ugliest of ugly) in particular, is exceedingly behaviorally difficult. It is counter-intuitive and against instinct, which is why many investors shy away from it.
Lecture by Toby Carlisle on Deep Value Investing
We will finish up this chapter by covering The Broken-Leg Problem. Please give this chapter a close study–the conclusions are extremely COUNTER-INTUITIVE and the opposite of what most investors look for. We are at the heart of deep value investing.