Optimal tests for parameter instability in the generalized method of moments framework

Article Abstract:

A test developed for evaluating the parameter instability in the Generalized Method of Moment (GMM) framework was based on the premise that optimality is only an asymptotic result and is conditional on the selected moment conditions. The asymptotic testing model is based on the Neyman-Peason approach where the densities between two distributions are analyzed, and is supported by the Radon-Nikodym derivative to further characterize the densities observed from the initial testing.

Brownian motion

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Monitoring structural change

Article Abstract:

Two new monitoring systems are developed to study the effects of fluctuations on the structural stability of time series studies. Both monitoring models are based on the Wald sequential probability ratio test and differs only in that one of the models, the CUSUM model, uses the Page-Hinckley test in spotting conditional detection delay. Simulation studies show that both models rely on widening of boundary functions to detect the magnitude of parameter change.

Time-series analysis, Time series analysis

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Noncausality in continuous time

Article Abstract:

Conditional independence and the decomposition of semi-martingales were used to define different concepts of noncausality for continuous-time processes. An analysis of the definitions showed that continuous-time noncausality is a function of the prediction horizon and the nature of the prediction. This shows that in a limited context, limited information or fewer parameters can be used to predict the results of a stochastic process.

Analysis, Markov processes, Stochastic processes

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