Over the last decades more and more attention has been paid to the problem how to fit a parametric model of time series with time-varying parameters. A typical example is given by autoregressive models with time-varying parameters (tvAR processes). We propose a procedure to fit such time-varying models to general nonstationary processes. The estimator is a maximum Whittle likelihood estimator o...

This paper applies time-varying autoregressive (TVAR) models with stochastically evolving parameters to the problem of speech modelling and enhancement. The stochastic evolution models for the TVAR parameters are Markovian di usion processes. The main aim of the paper is to perform on-line estimation of the clean speech and the model parameters, and to determine the adequacy of the chosen stati...

The RER which is theoretically influenced by the real interest rate differential (RRE) and currency excess return (CER), is statistically examined during 1990-2016. Accordingly, the stationarity of RER as null hypothesis is not approved in the Iranian economy. Therefore, the TVAR method is examined to analyze the nonstationary RER sample to two sub-periods stationary process which are both stat...

Empirical evidence suggests that financial risk has a heavy-tailed profile. Motivated by recent advances in the generalized quantile measure, we propose tail value-at-risk (TVaR)-based expectile, which can capture compared with classic expectile. In addition to showing measure is well-defined, properties of TVaR-based expectiles as measures were also studied. particular, give equivalent charact...

Empirical studies of the global liquidity spillover on Indonesia’s economy are still relatively limited. Most contagion literature focuses only effects real shock (on output) due to financial shock. We assert that effect output Indonesia macroeconomic conditions is a fairly relevant issue be studied. This research aims investigate interdependent relationships between world GDP, commodity prices...

A new method for the stabilization of time-varying autoregressive models is proposed. The method is based on the interpretation of the underdetermined time-varying least squares prediction problem as an ill-posed inverse problem. The problem is regularized with the Tikhonov approach and is then augmented with nonlinear hyperstability constraints. The problem is solved iteratively with an exteri...