| dc.description.abstract | In the financial markets, asset returns exhibit collective dynamics masking individual impacts on the rest
of the market. Hence, it is still an open problem to identify how shocks originating from one particular
asset would create spillover effects across other assets. The problem is more acute when there is a large
number of simultaneously traded assets, making the identification of which asset affects which other assets
even more difficult. In this paper, we construct a network of the conditional volatility series estimated
from asset returns and propose a many-dimensional VAR model with unique identification criteria based
on the network topology. Because of the interlinkages across stocks, volatility shock to a particular asset
propagates through the network creating a ripple effect. Our method allows us to find the exact path
the ripple effect follows on the whole network of assets. | en_US |
