Dragon King Theory

On September 11, 2001, the world was shaken by the sudden news: The United States had been the subject of a series of attacks that would change the course of history. In 2008, the Global Financial Meltdown was also unexpected to most people, even savvy financial analysts. Both events were rare and improbable, bearing profound consequences, a perfect example of what is known as Black Swan incidents.

According to the Black Swan Theory, this kind of events can have catastrophic results for the world and the markets, especially because they are mostly unpredictable. Or are they?

Didier Sornette1, a professor of Entrepreneurial Risks at the Swiss Federal Institute of Technology Zurich, proposed the Dragon King Theory. His view is that most apparently unpredictable Black Swan events hide organizing principles that, once identified, can help us to anticipate them. In a nutshell, Dragon King Theory is a risk management tool.

The theory was the underpinning for the Financial Crisis Observatory launched by Professor Sornette in 2008, the mandate of which was to “test the hypothesis that financial bubbles can be diagnosed in real-time and that their termination can be predicted probabilistically.”

Complex systems hide instabilities

The financial markets are made up of innumerable constituent parts, including traders, brokers, trading algorithms, banks, regulators, portfolio managers, financial advisers and many more. As a whole, they are a complex system, which is – in the simplest terms – a system involving many components interacting with each other.

Each constituent part is continuously interacting with, and adapting to, the behaviour of other constituent elements. That’s what makes it a complex system.

Dragon King Theory explains that there are instabilities inside such complex systems, which can ramp up to excessive levels.

According to Calgary-based Sigma Risk Management Inc.2: “The more complex a system, the more opportunity [exists] that inherent instabilities, correlations and unknown system dynamics can create extreme consequences.”

Sigma identified two examples of such instabilities:

  1. 10% of all cyber events cause 99% of the financial loss.
  2. The largest five epidemics in the past few hundred years produced 30 times the fatalities of the other 1,363 epidemics.

The predictive power of Dragon King Theory

The Dot-Com Crash (2000), the European Foreign Debt Crisis (2009), the Fukushima Nuclear Disaster (2011), and the Crude Oil Crisis (2014), are all examples of Black Swan events.

With the help of Dragon King Theory, it is believed that economists will be able to identify and anticipate similar financial crises before they cascade out of control. For now, it is still treated as a complementary concept to the Black Swan Theory, and a growing number of economists and financial analysts believe that the applications of the former can help us anticipate the consequences of the latter.

As with most risk management tools, Dragon King Theory depends on the application of mathematical models with exceptional predictive capability. Its uses, powerful in principle, have limited utility in practice – so far.

We still have to wait to find out the real impact of its application; for the moment, this is an interesting theory to keep tabs on.


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