Correlation of financial markets in times of crisis

Using the eigenvalues and eigenvectors of correlations matrices of some of the main financial market indices in the world, we show that high volatility of markets is directly linked with strong correlations between them. This means that markets tend to behave as one during great crashes. In order to do so, we investigate several financial market crises that occurred in the years 1987 (Black Monday), 1989 (Russian crisis), 2001 (Burst of the dot-com bubble and September 11), and 2008 (Subprime Mortgage Crisis), which mark some of the largest downturns of financial markets in the last three decades.Comment: 33 pages, 46 figure

Correlation of financial markets in times of crisis

Using the eigenvalues and eigenvectors of correlations matrices of some of the main financial market indices in the world, we show that high volatility of markets is directly linked with strong correlations between them. This means that markets tend to behave as one during great crashes. In order to do so, we investigate several financial market crises that occurred in the years 1987 (Black Monday), 1989 (Russian crisis), 2001 (Burst of the dot-com bubble and September 11), and 2008 (Subprime Mortgage Crisis), which mark some of the largest downturns of financial markets in the last three decades.

Shocks in financial markets, price expectation, and damped harmonic oscillators

Using a modified damped harmonic oscillator model equivalent to a model of market dynamics with price expectations, we analyze the reaction of financial markets to shocks. In order to do this, we gather data from indices of a variety of financial markets for the 1987 Black Monday, the Russian crisis of 1998, the crash after September 11th (2001), and the recent downturn of markets due to the subprime mortgage crisis in the USA (2008). Analyzing those data we were able to establish the amount by which each market felt the shocks, a dampening factor which expresses the capacity of a market of absorving a shock, and also a frequency related with volatility after the shock. The results gauge the efficiency of different markets in recovering from such shocks, and measure some level of dependence between them. We also show, using the correlation matrices between the indices used, that financial markets are now much more connected than they were two decades ago.