We develop a Markov-Switching Autoregressive Conditional Intensity (MS-ACI) model with time-varying transitional probability, and show that it can be reliably estimated via the Stochastic Approximation Expectation–Maximization algorithm. Applying our to high-frequency transaction data, we detect two distinct regimes in intraday volatility process: dominant regime is observable throughout tradin...

In this paper, we introduce a discrete-time higher-order Markov-switching (HMS) model for measuring the risk of a portfolio. We suppose that the logarithmic returns from a risky portfolio is governed by a HMS model with the drift and the volatility switch over time according to the states of a discrete-time higher-order hidden Markov model (HHMM). We interpret the states of the HHMM as unobserv...

the relationship between financial development and economic growth in order to give priority to policies that will lead to financial development or addressing other economic priorities to achieve economic growth has attracted the attention of many economics. nonlinear models of causality and causal relationships between variables in the modification of variables in different regimes exist, why ...

In modeling a cold standby redundancy allocation problem (RAP) with imperfect switching mechanism, deriving a closed form version of a system reliability is too difficult. A convenient lower bound on system reliability is proposed and this approximation is widely used as a part of objective function for a system reliability maximization problem in the literature. Considering this lower bound do...

A hidden semi-Markov-switching quantile regression model is introduced as an extension of the Markov-switching one. The proposed allows for arbitrary sojourn-time distributions in states chain. Parameters estimation carried out via maximum likelihood method using Asymmetric Laplace distribution. As a by product specification, formulae and methods forecasting, state prediction, decoding checking...