Are These Shocks for Real? Sensitivity Analysis of the Significance of the Wavelet Response to Some CKLS Processes

Abstract

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.

Equações Diferenciais Estocásticas na Engenharia Química

“…(7) parece ser um processo de Ornstein-Uhlenbeck, mas não o é, porque a volatilidade é igual a − ̅ 1 . Na verdade, trata-se de um processo Chan-Karolyi-Longstaff-Sanders (CKLS), que tem volatilidade igual a − ̅ 1 ou seja, a volatilidade é , onde γ pode ser igual a 1/2 ou 1 [17]. No entanto, este processo também reverte a média.…”

Sanction or Financial Crisis? An Artificial Neural Network-Based Approach to model the impact of oil price volatility on Stock and industry indices

“…In this regard, it is expected that higher oil price leads to higher revenue, cash flow and therefore growth in the economy and financial market [3]. There are also concerns about the contagion effects of these shocks on the other financial time series such as stock market, commodities and energy indices [41]and [40] and [2] and [30] and [28], which makes the modelling and estimation of financial variables complicated [21]. hence, understanding the underlying behaviour of oil price is important to keep track of any influences.…”