The CKLS process (introduced by Chan, Karolyi, Longstaff, and Sanders) is a typical example of a mean-reverting process. It combines random fluctuations with an elastic attraction force that tends to restore the process to a central value. As such, it is widely used to model the stochastic behaviour of various financial assets. However, the calibration of CKLS processes can be problematic, resulting in high levels of uncertainty on the parameter estimates. In this paper we show that it is still possible to draw solid conclusions about certain qualitative aspects of the time series, as the corresponding indicators are relatively insensitive to changes in the CKLS parameters.

Mean-reverting diffusion, CKLS (Chan, Karolyi, Longstaff, and Sanders), Generalized Method of Moments (GMM), Wavelets, Exogenous shock
QuantEssential, Belgium
dx.doi.org/10.3390/ijfs6030076
International Journal of Financial Studies
Intelligent and autonomous systems

Kokabisaghi, K, Pauwels, E.J.E.M, Van Meulder, K, & Dorsman, A.B. (2019). Are these shocks for real? Sensitivity analysis of the significance of the wavelet response to some CKLS processes. International Journal of Financial Studies, 6(3). doi:10.3390/ijfs6030076