Nonparametric Estimation of the Leverage Effect: A Trade-Off Between Robustness and Efficiency

• 成果类型: Article
• 署名作者: Kalnina, Ilze; Xiu, Dacheng
• 署名单位: Universite de Montreal; University of Chicago
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1080/01621459.2016.1141687
• 发表日期: 2017
• 页码: 384-396
• 关键词: STOCHASTIC VOLATILITY MODELS; risk premia; specification; returns; tests; jumps; spot

摘要

We consider two new approaches to nonparametric estimation of the leverage effect. The first approach uses stock prices alone. The second approach uses the data on stock prices as well as a certain volatility instrument, such as the Chicago Board Options Exchange (CBOE) volatility index (VIX) or the Black-Scholes implied volatility. The theoretical justification for the instrument-based estimator relies on a certain invariance property, which can be exploited when high-frequency data are available. The price-only estimator is more robust since it is valid under weaker assumptions. However, in the presence of a valid volatility instrument, the price-only estimator is inefficient as the instrument-based estimator has a faster rate of convergence.We consider an empirical application, in which we study the relationship between the leverage effect and the debt-to-equity ratio, credit risk, and illiquidity. Supplementary materials for this article are available online.