31 research outputs found
Carbon-dioxide emissions trading and hierarchical structure in worldwide finance and commodities markets
In a highly interdependent economic world, the nature of relationships
between financial entities is becoming an increasingly important area of study.
Recently, many studies have shown the usefulness of minimal spanning trees
(MST) in extracting interactions between financial entities. Here, we propose a
modified MST network whose metric distance is defined in terms of
cross-correlation coefficient absolute values, enabling the connections between
anticorrelated entities to manifest properly. We investigate 69 daily time
series, comprising three types of financial assets: 28 stock market indicators,
21 currency futures, and 20 commodity futures. We show that though the
resulting MST network evolves over time, the financial assets of similar type
tend to have connections which are stable over time. In addition, we find a
characteristic time lag between the volatility time series of the stock market
indicators and those of the EU CO2 emission allowance (EUA) and crude oil
futures (WTI). This time lag is given by the peak of the cross-correlation
function of the volatility time series EUA (or WTI) with that of the stock
market indicators, and is markedly different (>20 days) from 0, showing that
the volatility of stock market indicators today can predict the volatility of
EU emissions allowances and of crude oil in the near future.Comment: 4 figure