Controlling and monitoring financial risk has been receiving more and more attention from business practitioners, decision makers and academic researchers. When monitoring financial risk, the probability of a large adverse market movement is always of great practical concern (e.g., Bollerslev 2001). Large market movements can occur due to inherent market uncertainty, dramatic policy changes, surprising shocks, speculative attacks, financial contagion, and etc.
When they occur, extreme market movements imply changehands of a huge amount of capital among market participants, unavoidably leading to bankruptcies. They can even cause collapse of financial systems and social instability. Market participants have been always aware of painful experience when extreme adverse market movements occur, and their aversion to in solvency type extreme risk is usually high.
Large market movements have become commonplace nowadays. For example, on the Black Monday, October 19, 1987, U.S. stocks collapsed by 23%, wiping out US$ 1 trillion in capital. Around 1990, Japanese stock prices fell, with the Nikkei 225 index sliding from 39,000 at the end of 1989 to 17,000 three years later, resulting in a total of US$ 2.7 trillions in capital loss. In the bond debacle of 1994, the Federal Reserve Broad, after having kept interest rates low for three years, started a series of six consecutive interest rate hikes that erased US$ 1.5 trillion in global capital.
The Orange County Investment Pool, a portfolio of US$ 7.5 billion belonging to municipal investors, including the county, cities, and schools, lost US$ 1.64 billion in December, 1994. This is the largest municipal failure in history. During the 1997-1998 Asian financial crisis, several Asian currencies devaluated dramatically within a very short period (e.g., Woo et al. 2000). Other examples of large market movements include recent large price adverse movements in the U.S. stock market after the September 11 Terror Incident, as well as the bankruptcies of the Long Term Capital Management, Enron, and Worldcom.
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Detecting Extreme Risk Spillover Between Financial Markets
