In this study we construct volatility spillover indexes for some of the major stock market indexes in the world. We use a DCC-GARCH framework for modelling the multivariate relationships of volatility among markets. Extending the framework of Diebold and Yilmaz [2012] we compute spillover indexes directly from the series of returns considering the time-variant structure of their covariance matrices. Our spillover indexes use daily stock market data of Australia, Canada, China, Germany, Japan, the United Kingdom, and the United States, for the period January 2001 to August 2016. We obtain several relevant results. First, total spillovers exhibit substantial time-series variation, being higher in moments of market turbulence. Second, the net position of each country (transmitter or receiver) does not change during the sample period. However, their intensities exhibit important time-variation. Finally, transmission originates in the most developed markets, as expected. Of special relevance, even though the Chinese stock market has grown importantly over time, it is still a net receiver of volatility spillovers.
We extend the framework of Diebold and Yilmaz [2009] and Diebold and Yilmaz [2012] and construct volatility spillover indexes using a DCC-GARCH framework to model the multivariate relationships of volatility among assets. We compute spillover indexes directly from the series of asset returns and recognize the time-variant nature of the covariance matrix. Our approach allows for a better understanding of the movements of financial returns within a framework of volatility spillovers. We apply our method to stock market indexes of the United States and four Latin American countries. Our results show that Brazil is a net volatility transmitter for most of the sample period, while Chile, Colombia and Mexico are net receivers. The total spillover index is substantially higher between 2008Q3 and 2012Q2, and shock transmission from the United States to Latin America substantially increased around the Lehman Brothers' episode.
In this paper, we examine the financial and real effects of macroprudential policies with a new identifying strategy that exploits borrower-specific provisioning levels for each bank. Locally, we compare similar firms just below and above regulatory thresholds established in Colombia during 2008--2018 for the corporate credit portfolio. Our results indicate that the scheme induces banks to increase the provisioning cost of downgraded loans. This implies that, for loans with similar risk but with a discontinuously lower rating, banks offer a lower amount of credit, demand higher quality guarantees, and impose a higher level of provision coverage through the loan-loss given default. To illustrate, a 1 percentage point (pp) increase in the provision-to-credit ratio leads to a reduction in credit growth of up to 15pp and lowers the probability of receiving new credit by up to 11pp. When mapping our results to the real sector, we find that downgraded firms are constrained in their investment decisions and experience a contraction in liabilities, equity, and total assets.
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