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Book Review: Pitch the Perfect Investment

Pitch the Perfect Investment, by two money managers who have also taught for many years at Columbia University’s Graduate Business School, can stop small caliber bullets or deflect a vicious sword blow with its heavy-gloss 496 color pages.  Bad jokes aside, is the book worth the $30+ for its intended audience, young professionals seeking an investment career or can other readers gain investing insights?

FYI: I previously mentioned here Sept. 6th 2016, Pitch the Perfect Investment and Sept. 21, 2017 Pitch the Perfect Investment

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The authors synthesized many academic publications for the reader to understand the subtleties behind concepts like the Wisdom of Crowds, market efficiency, behavioral finance, and risk into clearer language.  This book with its colorful diagrams can help you grasp the theory of a discounted cash flow model or “DCF”; DCFs are used throughout the book because as the authors say, “all valuation is at the core a DCF, either explicitly or implicitly, whether they (analysts and portfolio managers) admit it or not.”   Of course, it is a given that the young analyst can gain his or her own company and industry expertise so as to insert reasonable assumptions into the DCF model.

Investing is simple but not easy some say. This book provides the simple concepts in a colorful, insightful way, but you have to do the hard part—scratch out a variant perception while competing with many other professionals. Sobering.

The reader is taken through the basics of valuing an asset, a business, how to evaluate competitive advantage and value growth with simple examples (The Lemonade Stand).   The authors drive home the importance of differentiating between nominal growth and profitable growth.  Growth without competitive advantage earning a return above its cost of capital is useless or worse. Certainly, all investors must grasp those concepts.  Every page is festooned with color cartoons, diagrams, tables and graphs.  This is a visual text.

The most interesting part of the book for me was the Chapter 6, The Wisdom of Crowds.  As Buffett says, “You must know two things as an investor: how to value a business, and how to think about prices.”  If I can paraphrase correctly, the Wisdom of Crowds with an adequate amount of domain-specific knowledge and diverse views acting independently from each other on disseminated information will be a force to push price towards efficiency or intrinsic value.  My respect for market efficiency and the person on the other side of the trade from me was reinforced.  If you gain anything from this book, understand that earning an investment edge or variant perception is EXTREMELY difficult and rare.   The authors may have intentionally driven home their point with their example of Cloverland Timber Company.

In their example, the analyst had the domain expertise to notice a line in the financial statement that the Cloverland was undercutting its forests, then satellite imagery was used to assess the quality of the asset and arrive at a more accurate valuation than the market’s current estimate.  The information is available but not publicly disseminated.   I wonder how many analysts/portfolio managers have the time, energy, money, or inclination to go this extra mile?  If you are this able, then you deserve alpha.   What are the implications?

If diverse individuals with independent thoughts are required to have the “Wisdom of Crowds” operate effectively, how will investment firms with their hordes of MBAs and CFAs all taught the same concepts, reading the same newspapers, magazine, research reports, and attending the same investment conferences arrive at non-consensus conclusions often–or ever?

The Wisdom of Crowds gives you an understanding of how prices are set under normal conditions when the forces of darkness and “Mr. Mayhem” (cartoon figure in the book using a magnet to pull prices away from market efficiency; he is the guy you need to spot quickly) are not strong enough to pull prices sufficiently away from intrinsic values.  In other words, behavioral finance is complementary to efficient markets.  One can then recognize when the Wisdom of Crowds becomes the Madness of Crowds.  For an understanding of how prices are set by individuals in a free market, go to pages 79-185 in Man, Economy, and State by Murray Rothbard (Google: Man, Economy, and State.pdf) which has an analysis of how individuals set prices through direct exchange.

Another valuable chapter in the book is Chapter 9, How to Assess Risk.  When investors confuse uncertainty (unknowns) with risk (losing money), then opportunity may appear.

Paul Sonkin, one of the authors, gives sobering advice to students who dream of becoming money managers.  Page 151: “I’m not trying to discourage you from pursuing your dreams, but you should do it with your eyes open.  Do it because you love analyzing companies, not to make a quick buck. And, if your goal is to outperform the market, keep in mind how difficult it has been in the past and the fact that it will only be more challenging in the future.” Those are true words.  The investing profession may end up like acting.  Only the crazy brave will pursue.

Once you have finished Section 1, The Perfect Investment, you then learn how to “Pitch” the Perfect Investment.   Assuming you are diligent enough to acquire the information, assess risk, identify an actual mispricing, and know the catalyst, then convincing another of the merits of your investment should be the easy part.  Unfortunately, too many do not provide a convincing case for the merits of their investment.   An example, of a devastatingly compelling case: The truth shall set you free (liar, liar)

The authors lay out a framework below in this example:

Value or What Can I Make:  Market price is $90 but the stock is worth $140—time horizon is less than 18 months.

Catalyst: Or Who else will figure this out:  Activist with a good track record is pushing for a sale.

Mispricing: The activist did an independent appraisal which the market is unaware of showing a substantially higher value than the company appraisal.  Also, the presence of the activist does not appear to be priced into the stock.  The market is unaware of the activist or does not think he will be successful.

Downside:  Limited. Timberland is a hard asset.

For another example of a forceful investment case with an implied catalyst: Other People’s Money Does Danny Devito provide a strong case? Does he show how much one can make, lose, what is the market missing, and the catalyst?

If you truly have a variant perception, then this is usually your reception: Michael Burry’s Variant Perception

And, only if you are right, and you make the decisions can you present this way: Michael Burry’s Investors  If you read the book, The Big Short, ironically you know that Michael Burry was not making a macro bet, but on the impossibility of individual mortgage holders to make their mortgage payment when asset prices decline and/or interest rates reset higher.

An investment edgeThere are only three ways to gain an edge

In summary, while I do not agree with the book-jacket blurb:

Mr. Nicholas Gallucio, CEO of Teton Advisors, who said, “In this era of hyper-competition on Wall Street ……even the smallest edge can make the difference between success and failure. Pitch the Perfect Investment will give the professional investor that edge.”  I do believe the book is worth $30 for a beginning and intermediate investor who wants to refine their understanding of key investment concepts and to review how to make clear and convincing investment pitches.   Even if an investor does not have a boss to pitch to, the investor should always write down a succinct investment case for each investment.

Remember, I’m biased. I’m a cheapie who went Dutch on his honeymoon, charged an entrance fee, and had a cash bar.  Sure, I made a profit, but the divorce cost a fortune.  Perhaps, I confused price with value.

PS: Graham and Dodd Oct 2017

Pitch the Perfect Investment

I have not seen the videos in the link below.  Let me know if you learn anything practical.

Pitch the perfect investment (videos)

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Listen to the interview: https://soundcloud.com/valuewalk/pitch-the-perfect-investment-with-paul-sonkin-and-paul-johnson

Other than seeing the videos and listening to the interview, I have yet to read the book.  The book may help an analyst learn how to form their ideas into a concise report.   Remember than many money managers have nano attention spans, so you must get your idea across quickly in a compelling way.

That said, one area that might not have been covered is how to KNOW THYSELF!    What approach fits your interests, skills and talents and how do you accomplish the goal of knowing your circle of competence?   Then how do you learn from mistakes?  How do you track your learning and results?   Because of randomness, learning from past investments is more difficult than it appears.  Spend as much time studying yourself as the company you are pitching!

The above is not a knock on the book; I believe self-knowledge is an underemphasized skill of the investment game.

UPDATE: 9/27/2017 http://pitchtheperfectinvestment.com/2017/09/27/92617-video-from-book-launch-event-at-fordham/     A more recent set of videos explaining the motivation for the book.

Pitch the Perfect Investment

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Pitch the Perfect Investment

The Essential Guide to Winning on Wall Street

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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.

Probably too long-winded, but you get the point.

Beware the echo chamber http://graphics.wsj.com/blue-feed-red-feed/   A serious concern for your research. Scary.

More on psychology for contrarians.

Latest NewsJune 10, 2016 – We’re pleased to announce a new website launching in the coming week.  Please let us know any questions or comments about the transition.

June 08, 2016 – Check out our latest 1-hour free webinar “Trading on Sentiment Strategies to Profit from Media Analytics in Global Equities.”

Recent PressMay 14, 2016How To Time The Stock Market Using Media Sentiment — Ky Trang Ho Forbes


The World&39;s Greatest Stock Picker

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.

Our new book, Trading on Sentiment:  The Power of Minds Over Markets (Wiley, 2016), explains in detail how media sentiment is quantified and used to time markets and select investments.


How We Know What Isn&39;t So

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.

Learn more about improving your investment returns with insights from sentiment analysis of the herd in our new book, “Trading on Sentiment:  The Power of Minds Over Markets.”

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


References

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.

more here: https://www.marketpsychinsights.com/blog/