More recently, the term has been attributed to certain stock market events. In 2007, a mathematician and former trader named Nassim Nicholas Taleb used the term as the title of his book to describe rare and profoundly impactful events that happened in society. He explained that not only were the events unpredictable and rare, but that people had simplistic explanations about the events after the fact â as if the events were predictable.
What Is A Black Swan Event?
Why was the black swan theory developed?
The black swan theory was developed by economist Nassim Nicholas Taleb in 2007 to describe the impact of randomness on daily life and human disciplines like economics. Learning about these events can help us understand why these events reoccur, the scope of their impact and possible ways to prevent or recover from them.
Some economists have suggested that diversifying investments can help protect investors from a black swan event, since some investments may recover or see less loss than others. Since economists have suggested that these events occur because of economic tension from artificial fluctuation restrictions, one way to prevent them may be to allow more fluctuation in the economy regularly so that less tension builds up. Others have suggested that allowing the consequences of black swan events to freely impact the economy can build up resilience to prevent later black swan events.
What are black swan events?
Black swan events are global events that are so rare that normal economic models cannot predict them. They have a huge impact, and they prompt historians and economists to create explanations for how they could have been predicted or how they follow from other events. They are called “black swan events” because the discovery of black swans in Australia was unexpected and had an enormous impact on the field of zoology.
The black swan theory divides all fields of study into two types: linear domains and complex domains. In linear domains like math and physics, factors interact predictably and models can forecast outcomes accurately. In complex domains like economics and politics, outcomes depend on human behavior and rationality, so models are less accurate. Black swan events are the events in complex domains that are so unpredictable that models didnt account for their existence at all until they happened. The desire to see logic in complex domains encourages people to invent explanations for black swan events afterward, which is called “hindsight bias.”
Economic black swan events happen when a system is suppressing risks with regulations or other methods. Because the system does not have to recover from minor losses that those risks would cause, it becomes fragile and vulnerable. The system appears to remain strong and reliable, but builds up tension, and the collapse of that tension is a black swan event.
How to identify a black swan event
You can identify a black swan event by checking if an economic event meets the three black swan event requirements with this method:
1. Analyze the impact
The first characteristic of a black swan event is its tremendous impact, far beyond normal economic consequences. If an economic event had a relatively minor impact, like a temporary fluctuation of stock values or currency inflation, it is likely not a black swan event. If economists estimate a value loss of trillions of dollars, the event is likely a black swan event.
2. Analyze whether normal prediction methods could have been used to forecast it
The second characteristic of a black swan event is that even the use of forecasting tools like modeling cannot foresee a black swan event. Economists cant calculate the probability of a black swan event happening because they happen too rarely for there to be enough data to fully understand why they occur. After a black swan event, economists might build new models that can attempt to predict black swan events. Because there is so little data, however, these prediction models are based on statistical probabilities rather than factual knowledge of what events caused the black swan event.
So if the models to forecast that event are based on known relationships where one event causes another, that event is not a black swan event. If the models are based on the statistical likelihood of certain events, the event likely is a black swan event.
3. Analyze public response
The third characteristic of a black swan event is a reaction from historians and economists afterward to rationalize the event as if it could have been predicted. This phenomenon is called “hindsight bias.” One way to understand whether hindsight bias influenced public response is to look at when the prediction models for that event were created. If the prediction models were created before the event, it was a predictable event and not a black swan event. If models for that event started showing up only after the event, it may be a black swan event.
Examples of black swan events
Whether an event is a black swan event is subjective, since there is no dollar amount for how much loss an event has to cause to be a black swan event, and the public response and predictability of an event can also be subjective. Here are some global events that many economists consider black swan events:
Financial crisis in Asian countries in 1997
In 1997, several Asian countries including Thailand, South Korea, Malaysia and Indonesia experienced rapid growth, massive foreign investment and significant growth in their property markets which encouraged public debt. When organizations could not repay their debt, it triggered a decline that included currency devaluations up to 38% and a 60% drop in the value of some stocks.
Dot-com bubble in 2000
In 2000, the value of tech companies fell as investors realized that not all internet companies would become successful. This event is known as the “dot-com bubble,” and it wiped out nearly a trillion dollars of stock with the NASDAQ stock market losing 78% of its value.
Stock value loss after 9/11 attacks in 2001
After the 9/11 attacks in 2001, the U.S. saw a $1.4 trillion stock value loss in a week as many investors rushed to sell off stocks in airline companies and other businesses.
Hyperinflation event in Zimbabwe in 2008
In 2008, years of political conflict and inflation in Zimbabwe peaked as the Zimbabwean dollar experienced a period of hyperinflation reaching 79.6 billion percent. In 2009, the Zimbabwean dollar was removed as the countrys official currency.
Housing market crash in the U.S. in 2008
In September 2008, the U.S. housing market crashed because of sub-prime mortgages that people could not pay back. Many banks and corporations who had invested in these assets experienced significant losses. The U.S. government bailed out many major financial institutions and purchased Fannie Mae and Freddy Mac, the two main insurers of U.S. mortgages. Economists estimate that $10 trillion was lost in global markets.
European sovereign debt crisis in 2009
In 2009, the banking systems in several European countries including Portugal, Ireland, Italy, Spain and Greece collapsed. These banks were not able to pay off their public debt, and the European Central Bank had to bail each of them out at least once.
Crude oil crisis in 2014
In 2014, a commodity boom triggered the U.S. and Canada to start producing more crude oil and the Libyan oil supply became controlled by Western powers. This increased the amount of crude oil on the market and drove the price per barrel down by more than 50%.
Brexit announcement in 2016
In 2016, the United Kingdom voted to leave the European Union. This vote caused both the UK and EU currencies, the pound and the euro, to lose value rapidly and caused a loss of up to $2 trillion in global markets.
What are examples of black swan events?
What is the meaning of black swan events?
What was the longest black swan event?