__Tail Hedging

"Thus, the stock market tends to be about immediate bets (or expectations) on distant outcomes—yet all that matters to the bettors tend to be the immediate outcomes," Mark Spitznagel - TAIL HEDGING

Black Swan
Kuroi hakuchō
Kuro Hakuchō
Kuro Hahucho

Hammered
Tsuchime

Black Swan (Cygnus Atratus) – The Impossible Avian
During the period of molting that adult swans go through following the breeding season they lose their feathers and are unable to fly.
A male swan is called a cob. A female swan is called a pen. A baby swan is called a cygnet.
Black swans travel in flocks. A group of black swans in flight is called a wedge, perhaps due to the V-shaped pattern they can adopt while flying, while the same group of black swans would instead be called a bank if they were congregating on the ground.

The black swan has been a popular reference in culture throughout the years. In 1843, the philosopher John Stuart Mill used the example of black swans to point out how even large numbers of consistent observations of something can lead to an incorrect assumption – such as “all swans are white”. In 1912, the philosopher Bertrand Russell also cited this example of black swans defying generalized assumptions. Karl Popper, another philosopher, in 1934 cited how black swans were an example of how scientific assumptions, such as “all swans are white”, needed to be able to be proven false.

To be responsibly wrong

Buyers of tail risk funds have historically paid about 3.4% per year to make 25–50% in crises

Tail risk hedges are designed to only pay off when the markets suddenly plunge, so many investors don’t have the stomach to carry them.

Taleb believes investors shouldn't be in the market without a tail risk hedge because of the high degree of uncertainty about the future right now. Tail events are extreme situations that have a lower probability of happening compared to other scenarios. However, the odds of these tail events happening increases during times of uncertainty even though they remain lower than the odds of the set of standard outcomes.

For example, the CBOE Eurekahedge Tail Risk Hedge Fund Index has jumped 48.19% this year. Last year, the Eurekahedge fund lost 10% while the S&P 500 earned 34%. Universa, run by Mark Spitznagel, was up 4,000%. The Dow Jones Industrial Average is down nearly 12%, the S&P 500 is down 6.2% and the Nasdaq Composite is up by about 10%.

Taleb agrees the normal distribution strategy has its place within some data sets. Those where no chance for massive outliers exist, for instance, like pay-offs within casino games or the heights of human beings. He completely disagrees with using such a methodology for predicting future events when the data sets can have extreme outliers, meaning that one single observation can disproportionately impact the aggregate, or the total. Examples of such data sets, which he refers to as Extremistan, include wealth data or financial market data.

Foreword to Mark Spitznagel’s book Safe Haven

Nassim Nicholas Taleb

Detecting mathematical flaws in existing finance models, our edge has been linked to having been in the pit and understanding the centrality of calibration, fine-tuning, execution, orderflow and transaction costs.

Now what was the dominant idea to emerge?
There are activities with remote payoff and no feedback that are ignored by the common crowd.

With the associated corollary:
Never underestimate the effect of absence of feedback on the unconscious behavior and choices of people.
Mark kept using the example of someone playing piano for a long time with no improvement (that is, hardly capable of performing chopsticks) yet persevering; then, suddenly, one day, impeccably playing Chopin or Rachmaninoff.
No, it is not related to modern psychology. Psychologists discuss the notion of deferred payoff and the inability to delay one’s gratification as a hindrance. They hold that people who prefer a dollar now versus two in the future will eventually fare poorly in the course of life. But this is not at all what Spitz’s idea is about, since you do not know whether there might be a payoff at the end of the line, and, furthermore, psychologists are shoddy scientists, wrong almost all the time about almost all the things they discuss. The idea that delayed gratification confers some socio-economic advantage to those who defer was eventually debunked. The real world is a bit different. Under uncertainty, you must consider taking what you can now, since the person offering you two dollars in one year versus one today might be bankrupt then (or serving a jail sentence).

So what this idea is about isn’t delayed gratification, but the ability to operate without external gratification –or rather, with random gratification. Have the fortitude to live without promises.

Hence the second corollary:
Things that are good but don’t look good must have some edge.
The latter point allows she or he who is perseverant and mentally equipped to do the right thing with an endless reservoir of suckers.

For instance the theory of portfolio construction (or the associated “risk parity”) à la Markowitz requires correlations between assets to be both known and nonrandom. You remove these assumptions and you have no case for portfolio construction (not counting other, vastly more severe flaws, such as ergodicity). Yet one must have no knowledge of the existence of computer screens and no access to data to avoid noticing that correlations are, if anything, not fixed, changing randomly. People’s only excuse for using these models is that other people are using these models.

Cost-Effective Risk Mitigation
Most financial and business returns come from rare events –what happens in ordinary times is hardly relevant for the total. Financial models have done just the opposite.

The investment world is populated by analysts who, while using patently wrong mathematics, managed to look good and cosmetically sophisticated but eventually harm their clients in the long run because it is OPM (“other people’s money”) they are risking while the returns is theirs –again absence of skin in the game.

Steady returns (continuous ratification) comes along with hiding tail risks. Banks lost more money in two episodes, 1982 and 2008, than they made in the history of banking –but managers are still rich. They claimed that the standard models were showing low risk.

Imitators
At Universa, Spitz built a structure that tail-hedged portfolios, hence insulated him from the need for delayed random gratification. As introduced (and formulated) in Safe Haven, risk mitigation needs to be “cost-effective” (i.e., it should raise your wealth), and to do that it needs to mitigate the risks that matter, not the risks that don’t.

It was the birth of tail risk hedging as an investable asset class. Tail risk hedging removed the effect of the nasty Black Swan on portfolios; cost effective tail risk hedging obliterating all the other forms of risk mitigation. Accordingly, the idea grew on people and a new category was born. This led to a legion of imitators –those very same mutua muli persons who had previously been fooled by modern finance tools, finding a new thing to sell.

Universa proved the following: not only there is no substitute to tail risk hedging, but, when it comes to tail-risk hedging.

Tail risk hedging is hard.
For when you go from a principle to execution, things are much more complicated: the output is simple to the outsider, the process is hard seen from the inside. Indeed, it takes years of study and practice, not counting natural edges and understanding of the payoffs and probabilistic mechanisms.
For I said earlier that Mark’s edge came from pit trading and a natural (non contrived) understanding of the mathematics of tails. Not quite. His edge has been largely behavioral and my description of hardheaded was an understatement. Perhaps the most undervalued attribute for humans is dogged, obsessive, boring, discipline: in more than two decades, I never saw him once deviate a micro-inch from a given protocol.