 We had investigated 69 daily ?nancial time series, which constituted by 3 types ?nance assets(29 stock market indica- tor time series , 21 currency futures price time series and 19 commodity futuresprice time series). Empirical analyses show that the MST network of returns is time-dependent in overall structure, while same type ?nancial assets usually keep stable inter-connections. Moreover each asset in same group show similar economic characters. In other words, each group concerned with one kind of traditional ?nancial commodity. In addition, we ?nd the time-lag between stock market indicator volatility time series and EUA (EU allowances) , WTI (West Texas Intermediate)volatility time series.
<clarity>  We had investigated 69 daily ?nancial time series, which constituted by 3 types ?nance assets(29 stock market indica- tor time series , 21 currency futures price time series and 19 commodity futuresprice time series). Empirical analyses show that the MST network of returns is time-dependent in overall structure, while same type ?nancial assets usually keep stable inter-connections. Moreover each asset in same group show similar economic characters. In other words, each group concerned with one kind of traditional ?nancial commodity. In addition, we ?nd the time-lag between stock market indicator volatility time series and EUA (EU allowances) , WTI (West Texas Intermediate)volatility time series.
 We had investigated 69 daily ?nancial time series, which constituted by 3 types ?nance assets(29 stock market indica- tor time series , 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 ?nd the time-lag between stock market indicator volatility time series and EUA (EU allowances) , WTI (West Texas Intermediate)volatility time series.