A0238
Title: On pricing kernels for digital assets
Authors: Ratmir Miftachov - Humboldt University of Berlin (Germany) [presenting]
Maria Grith - Erasmus University Rotterdam (Netherlands)
Zijin Wang - Southwestern University of Finance and Economics (China)
Abstract: Time-varying preferences and the risk aversion of digital market investors are investigated by estimating pricing kernels (EPK) on Bitcoin (BTC) options data. We compare the classical method based on risk-neutral and physical density to the so-called conditional density integration (CDI) method that incorporates forward-looking information and B-spline functions. The CDI estimator takes into account the information available to investors but misses a proper construction of confidence bands that allow comparing EPKs estimated by both methods. Further, we use a functional principal component approach on the latter B-spline coefficients to cluster the estimated pricing kernels. The clusters are interpreted as different regimes and set in relation to other financial market measures. Our empirical results show that short- and long-term investors differ significantly regarding their EPKs.
