RT Journal Article
SR Electronic
T1 Bias Correction for Bond Option Greeks via Jackknife
JF The Journal of Derivatives
FD Institutional Investor Journals
SP 45
OP 63
DO 10.3905/jod.2021.1.129
VO 28
IS 4
A1 Zhang, Jinyu
A1 Gao, Kang
A1 Li, Yong
YR 2021
UL http://jod.pm-research.com/content/28/4/45.abstract
AB The underlying models for bond options are often based on some linear drift functions such that the option Greeks depend crucially on the mean reversion parameters. Substantial estimation bias may arise when these parameters are estimated using standard methods such as maximum likelihood estimation, leading to a bias in estimating the Greeks. To address this issue, following Phillips and Yu (2005), a jackknife method is adopted in this article. In particular, we apply the method directly to the estimation of option Greeks, rather than the estimation of parameters. This approach is general and computationally inexpensive; hence, it is convenient in practice. The finite-sample performance is investigated in several Monte Carlo studies. At last, in dynamic Delta hedging, we show that the bias reduction in the estimation of option Greeks using the proposed method can achieve some economic value.TOPICS: Derivatives, options, fixed income and structured finance, quantitative methods, simulationsKey Findings▪ Like option pricing, the bias problem is still serious in estimating the Greeks of the options.▪ The jackknife method is a good method to reduce the estimation bias in estimating the Greeks.▪ The bias reduction in the estimation of option Greeks using the proposed method can achieve some economic values in option markets around the world.