STATISTICAL PROPERTIES OF DAILY RETURNS: EVIDENCE FROM EUROPEAN STOCK MARKETS
研究多个欧洲股票交易所日收益率的分布特征，发现随机游走模型无法捕捉的非线性依赖，并采用GARCH(1,1)过程配合条件t分布来拟合数据。
This paper attempts to model the distributional properties of daily stock returns on several European Stock Exchanges. The empirical findings reveal the presence of non‐linear dependencies that cannot be captured by the random walk model. A model of return‐generating process that fit the data empirically is the Generalized Autoregressive Conditional Heteroskedastic GARCH (1,1) process with a conditional student‐ t distribution.