A new model for predicting the future expected cash flows from a loan is developed. It is based on a detailed analysis of the events of fulfilling, delinquency and default of each individual payment on the loan. The proposed model has significantly less uncertainty compared with the Markov chain...

This paper proposes a flexible way of modeling dynamic heterogeneous covariance breakdowns in multivariate GARCH (MGARCH) models. During periods of normal market activity, volatility dynamics are governed by an MGARCH specification. A covariance breakdown is any significant temporary deviation...

Statistical process control is an important and convenient tool to stabilize the quality of manufactured goods and service operations. The traditional Shewhart control chart has been used extensively for process control, which is valid under the independence assumption of consecutive...

In this paper, we establish a turning point chronology for the Chinese provincial deviation cycles during the period 1989–2009. The existing work has exclusively focused on the national business cycle.

This paper contributes to the understanding of the persistently high poverty rates in rural Madagascar. It tests the existence of poverty traps thanks to a Markovian poverty transition model where past poverty is allowed to have either a slope or an intercept effect on the current poverty risk....

The investment decisions and profitability of airlines encompasses elements such as air traffic forecasting, the cycles of orders and deliveries, profit cycles, airline growth and survivability in Asia. Regression analysis showed that air traffic growth rates are positively associated with GDP...

It is known that the robit regression model for binary data is a robust alternative to the more popular probit and logistic models. The robit model is obtained by replacing the normal distribution in the probit regression model with the Student’s t distribution. Unlike the probit and logistic...

Spectral properties of 1D systems with long-range correlated disorder and their response to an applied field are examined. An algorithm based on the additive multi-step Markov chains is used to analyze and synthesize layered systems consisting of two randomly alternated elements. Using an...

We consider a Markov chain model for population growth subject to rare catastrophic events. In this model, the moves of the process are getting algebraically rare (as from x−λ) when the process visits large heights x, and given a move occurs and the height is large, the chain grows by one...

We present a site-percolation model based on a modified FCC lattice, as well as an efficient algorithm of inspecting percolation which takes advantage of the Markov stochastic theory, in order to study the percolation threshold of carbon nanotube (CNT) fibers. Our Markov-chain based algorithm...