The Black Swan

A black swan is an unpredictable event that is beyond what is normally expected of a situation and has potentially severe consequences. Black swan events are characterized by their extreme rarity, their severe impact, and the widespread insistence they were obvious in hindsight. 

• A black swan is an extremely rare event with severe consequences. It cannot be predicted beforehand, though many will later claim it should be predictable after the fact.
• Black swan events can cause catastrophic damage to an economy, and because they cannot be predicted, they can only be prepared for by building robust systems.
• Reliance on standard forecasting tools can both fail to predict and potentially increase vulnerability to black swans by propagating risk and offering false security.

Recent Examples of Past Black Swan Events

The financial crash of the U.S. housing market during the 2008 crisis is one of the most recent and well-known black swan events. The effect of the crash was catastrophic and global, and only a few outliers were able to predict it happening.

Also, in 2008, Zimbabwe had the worst case of hyperinflation in the 21^st century with a peak inflation rate of more than 79.6 billion percent. An inflation level of that amount is nearly impossible to predict and can easily ruin a country financially.

The dot-com bubble of 2001 is another black swan event that has similarities to the 2008 financial crisis. America was enjoying rapid economic growth and increases in private wealth before the economy catastrophically collapsed. Since the Internet was at its infancy in terms of commercial use, various investment funds were investing in technology companies with inflated valuations and no market traction. When these companies folded, the funds were hit hard, and the downside risk was passed on over to the investors. The digital frontier was new and nearly impossible to predict the collapse.

As another example, the previously successful hedge fund, Long-Term Capital Management (LTCM), was driven into the ground in 1998 as a result of the ripple effect caused by the Russian government’s debt default, something the company’s computer models could not have predicted.

Source: Investopedia 

Las Vegas, NV·Posted Mar 29, 2020