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Domain Stabilization for Model-Free Option Implied Moment Estimation

Authors
Lee, GeulRyu, DoojinYang, Li
Issue Date
22-Feb-2025
Publisher
OXFORD UNIV PRESS
Keywords
deep-out-of-the-money options; domain stabilization; forecasting; option-implied moments; S&P 500 options
Citation
JOURNAL OF FINANCIAL ECONOMETRICS, v.23, no.2
Indexed
SSCI
SCOPUS
Journal Title
JOURNAL OF FINANCIAL ECONOMETRICS
Volume
23
Number
2
URI
https://scholarx.skku.edu/handle/2021.sw.skku/121060
DOI
10.1093/jjfinec/nbae037
ISSN
1479-8409
1479-8417
Abstract
We propose a new method, domain stabilization (DStab), to enhance the return predictive and forecasting ability of model-free option-implied moment estimators. Analyzing S&P 500 options data from January 2015 to December 2021, we show that DStab improves moment estimation consistency by stabilizing the integration domain, leading to better predictive and forecasting performance. When the options data characteristics are appropriately considered, DStab enhances both in-sample predictive and out-of-sample forecasting abilities of implied moments. DStab's out-of-sample forecasting ability surpasses other treatment methods.
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