北京大气细粒子PM2.5的化学组成

为了解北京大气细粒子(PM2.5)的污染水平和污染特征,在车公庄和清华园进行了连续1年、每周1次同步采样和全样品分析。2个采样点PM2.5的化学组成相似。含碳组分和水溶性离子是主要的组分,其质量浓度之和超过PM2.5的50%。有机碳、元素碳和细粒子PM2.5的季节变化一致,即冬季质量浓度最高,夏季最低。夏季NO-3的质量浓度最低且在采样过程中从特氟隆滤膜上有近50%的挥发。SO2-4不同于PM2.5的季节变化主要取决于SO2的转化率。地壳元素的质量浓度从冬季到春季大幅度上升,春季沙尘天气频是一个重要原因。     

Market risk management of banks: implications from the accuracy of Value‐at‐Risk forecasts

This paper adopts the backtesting criteria of the Basle Committee to compare the performance of a number of simple Value‐at‐Risk (VaR) models. These criteria provide a new standard on forecasting accuracy. Currently central banks in major money centres, under the auspices of the Basle Committee of the Bank of International settlement, adopt the VaR system to evaluate the market risk of their supervised banks. Banks are required to report VaRs to bank regulators with their internal models. These models must comply with Basle's backtesting criteria. If a bank fails the VaR backtesting, higher capital requirements will be imposed. VaR is a function of volatility forecasts. Past studies mostly conclude that ARCH and GARCH models provide better volatility forecasts. However, this paper finds that ARCH‐ and GARCH‐based VaR models consistently fail to meet Basle's backtesting criteria. These findings suggest that the use of ARCH‐ and GARCH‐based models to forecast their VaRs is not a reliable way to manage a bank's market risk. Copyright © 2002 John Wiley & Sons, Ltd.