THINKSheet is designed to help our clients anticipate, prepare for and react to market moving events before their competitors. The lowest probability, highest impact events are often referred to as “black swans” based upon the book by Nassim Taleb. Our Swans Watch Matrices provide checklists to help clients manage the process of identifying and reacting to these events faster and more accurately than their competitors. For example, the matrices help our investment clients:
- avoid overlooking potential swans
- identify the few swans to model
- identify drivers of relative value
- determine their causal effects
- determine interconnections among the investments
- update models dynamically as conditions change.
We rate the drivers unanticipated by the market in 3 categories – black swans, gray swans and catalysts – in descending order of probability and impact. Due to their intrinsic uncertainty, the categories are approximations. They are not rigidly defined but are fuzzy and relative to each other. The objective is to help everyone better communicate when comparing the unpriced in drivers by probability and impact; getting a perfect common understanding of the application of these categories is impossible.
The black swan theory or theory of black swan events is a metaphor that describes an event that comes as a surprise, has a major effect, and is often inappropriately rationalized after the fact with the benefit of hindsight.
The theory was developed by Nassim Nicholas Taleb to explain:
- The disproportionate role of high-profile, hard-to-predict, and rare events that are beyond the realm of normal expectations in history, science, finance, and technology.
- The non-computability of the probability of the consequential rare events using scientific methods (owing to the very nature of small probabilities).
- The psychological biases that blind people, both individually and collectively, to uncertainty and to a rare event’s massive role in historical affairs.
It refers only to unexpected events of large magnitude and consequence and their dominant role in history. Such events, considered extreme outliers, collectively play vastly larger roles than regular occurrences.
Interconnections can be Black Swans
The quote by Nassim Taleb below, made before the global financial crisis of 2007-10, is the foundation for the ultimate TST output – i.e., a Synthesis Swan:
Globalization creates interlocking fragility, while reducing volatility and giving the appearance of stability. In other words it creates devastating Black Swans. We have never lived before under the threat of a global collapse. Financial Institutions have been merging into a smaller number of very large banks. Almost all banks are interrelated. So the financial ecology is swelling into gigantic, incestuous, bureaucratic banks – when one fails, they all fall. The increased concentration among banks seems to have the effect of making financial crisis less likely, but when they happen they are more global in scale and hit us very hard. We have moved from a diversified ecology of small banks, with varied lending policies, to a more homogeneous framework of firms that all resemble one another. True, we now have fewer failures, but when they occur …. I shiver at the thought.
Gray Swan Definition
Investopedia defines gray swan as:
An event that can be anticipated to a certain degree, but is considered unlikely to occur and may have a sizable impact on the valuation of a security or the health of the overall market if it does occur. A grey swan event is unlike a black swan event whose total impact is difficult to predict. Despite the possibility of determining the properties and potential impact of such an event, it is difficult to create precise calculations regarding the total impact.
The term “black swan” was coined by Nassim Nicholas Taleb to describe the uncertainty and risk posed by unpredictable events. Gray swan events, which are derived from the black swan concept, may include earthquakes and even events like the Great Depression. An example of gray swans applied by the equity analyst at Evercore Partners is below. The gray swans are the judgments that rank below +++ and above – – – on the 7 gradation scale used by the analyst.
Catalysts Definition and Examples – Morgan Stanley
Morgan Stanley used the Catalyst metric to rank 21 publishing stocks. You can see the THINKSheet models and related research reports in TST Equities Systems site. Go to Morgan Stanley Section. The Morgan Stanley Catalyst definition and an example from the first report is below:
The investment world, the buy side and sell side alike, are in constant search for the burning “catalyst” for any particular stock story. Potential catalysts can be good, bad, or non-existent depending on the time-period. Our model weights the catalyst factor heavily or 17.5% of the entire weighted sum score. We score the catalyst factor employing seven different scores between 100% (the most positive) and “0”.
First Morgan Stanley Report, page 4
From the catalysts selected by the Morgan Stanley team for each stock, communicated and quantified using one of our proprietary Professional Language Similarity Functions, ThinkSHEET assigned a symbol for each catalyst and color-coded them to highlight their impact on the overall results.
You can see at a glance that the Ad turn at Times/Globe +++ catalyst for New York Times had the most positive impact, while Vocational school exposure for Washington Post the most negative impact.
Short Term Catalysts & Examples – Evercore Partners
THINKSheet is a semantics-driven model that features user-driven language with the greatest meaning in the fewest words. Replacing Catalysts with Short Term Catalysts not only communicated the metric’s meaning more clearly but also the different time frames for his ratings (12 months) and TST rankings (3-6 months). Using Short Term Catalysts saved him significant explanatory text in explaining to his readers the different time frames between his ratings & rankings.
Black Swans Example – Evercore Partners
The senior publishing analyst at Evercore Partners Black swans used as a metric by to rank his stocks. The analyst rated his stocks in 7 gradations from best to worst impact and used symbols to communicate his rating.He ranked Demand Media (Spinoff upside) and Thomson Reuters (Cost cutting exceeds(E)) best or excellent indicated by +++.
He ranked Lamar (REIT index inclusion), Live Nation (EBITDA goal- early) second best or very positive indicated by ++.
New York Times (Adv. a positive surprise) and New Corp (Amplify partnership) were third best or positive indicated by +.
Moody’s (Greater than E legal risk), Omnicom (Deal dislocation) and Monster (Restarting strategic review) were fifth best or negative indicated by -.
McGraw Hill (DOJ Case) was seventh or Worst indicated by – – – .
Critical Issues Example – Evercore Partners
Spin off upgrade”. He then combined them into a critical issues ranking.
Relative Value Example – Evercore Partners
The example below shows how the analyst combined 2 QL factors (valuation and fnancials) and 3 QL factors (short-term catalysts, risks and black swan) into a relative value ranking. The art is in synthesizing these complex issues into an easy-to-understand story of his thought process. You can see at a glance why New York Time is first: its +++ Catalyst of Digital Subscribers $8 tier) and Demand Media is last: its Sub-Optimal Financials and eHow Traffic trends – – -.
Facebook Historical Catalysts
The THINKSheet symbols (– – –, +++, and none = neutral) and colors highlight the user’s judgment about the catalyst’s impact on the Facebook stock price: IPO: very negative; WhatsApp Acquisition: neutral; and Mobile Ad Numbers 2014: very positive.