主题：Weak Identification of Long Memory with Implications for Volatility Modelling
主讲人：Jun Yu 新加坡管理大学
主持人：柯书尧 BETVLCTOR伟德官网下载
时间：2023年5月12日（周五）10:00-11：30
地点：伟德BETVlCTOR1946大楼（中惠楼）102
摘要
Whereas earlier empirical evidence suggests long memory in volatility of financial assets, more recent empirical evidence indicates that volatility is rough. The present paper explores weak identification issues arising in these two popular configurations. It is shown that a model with long memory and weak autoregressive dynamics is asymptotically observationally equivalent to a model with antipersistent shocks and a near-unit autoregressive root. A data-driven semiparametric and identification-robust approach to inference is developed, revealing the effect of these model ambiguities and documenting the prevalence of weak identification in many realized volatility and trading volume series. The identification-robust empirical findings generally favor long memory dynamics in volatility and volume, a conclusion that is corroborated using social-media news flow data. Financial implications of weak identification on forecasting are also examined.
主讲人简介
Jun Yu，Singapore Management University伟德BETVlCTOR1946Lee Kong Chian讲席教授、商学院教授。研究领域包括金融计量经济学、计量经济理论、资产定价等。曾担任Journal of Econometrics、Econometric Theory等国际计量经济学知名期刊编辑。研究工作发表于Journal of Econometrics、Review of Financial Studies等国际经济学与金融学知名期刊。
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校对|王国长
责编|麦嘉杰
初审|黄振
终审发布|郑贤
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