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含观测误差时间序列的间接推断AI 解读

Summary We propose the indirect inference estimator as a consistent method to estimate the parameters of a structural model when the observed series are contaminated by measurement error by considering the noise as a structural feature. We show that the indirect inference estimates are asymptotically biased if the error is neglected. When the condition for identification is satisfied, the structural and measurement error parameters can be consistently estimated. The issues…

追踪波动率：含波动率跳跃的乘法误差模型AI 解读

Persistence and unpredictable large increments characterize the volatility of financial returns. We propose the Multiplicative Error Model with volatility jumps (MEM-J) to describe and predict the probability and the size of these extreme events. Under the MEM-J, the conditional density of the realized measure is a countably infinite mixture of Gamma and Kappa distributions, with closed form conditional moments. We derive stationarity conditions and the asymptotic theory for…

欧元公司债券的风险因子AI 解读

SUMMARY This paper investigates the determinants of credit spread changes in euro‐denominated bonds. We adopt a factor model framework, inspired by the credit risk structural approach, as credit spread changes can be easily viewed as an excess return on corporate bonds over Treasury bonds. We try to assess the relative importance of market and idiosyncratic factors as an explanation of movements in credit spreads. We adopt a heterogeneous panel with a multifactor error model…

GARCH均值模型中的人工回归检验AI 解读

The issue of finite-sample inference in Generalised Autoregressive Conditional Heteroskedasticity (GARCH)-like models has seldom been explored in the theoretical literature, although its potential relevance for practitioners is obvious. In some cases, asymptotic theory may provide a very poor approximation to the actual distribution of the estimators in finite samples. The aim of this paper is to propose the application of the so-called double length regressions (DLR) to…