Accurate prediction of lake-level changes is a very important problem for a wise and sustainable use. In recent years significant lake level fluctuations have occurred and can be related to the climatic change. Such a problem is crucial to the works and decisions related to the water resources...

Rainfall is one of the fundamental components of the hydrological cycle as its accurate estimation is necessary for planning, designing and operation of water resources development programmes. In the present study, monthly stochastic model was developed using rainfall data for Doimukh...

Volatility–volume regressions provide a convenient framework to study sources of volatility predictability. We apply this approach to the daily realized volatility of common stocks. We find that unexpected volume plays a more significant role in explaining realized volatility than expected...

This paper develops a new econometric tool for evolutionary autoregressive models where the AR coefficients change smoothly over time. To estimate the unknown functional form of time-varying coefficients, we propose a mdified local linear smoother. The asymptotic normality and variance of the...

Статья посвящена построению факторных регрессионных и авторегрессионных моделей, объясняющих динамику темпов инфляции в экономике Республики Казахстан в...

The forecast of agricultural prices is one of the most important factors in making decision on production farms. The appropriate forecast allows for limiting the risk connected with one’s economic activity. In this study autoregressive models have been used, which helped to determine the price...

The forecast of agricultural prices is one of the most important factors in making decision on production farms. The appropriate forecast allows for limiting the risk connected with one’s economic activity. In this study autoregressive models have been used, which helped to determine the price...

The state-space method is applied to the problem of separating an autoregressive (AR) signal from composite AR and white normal noise. In the stationary case, for which the Wiener filter exists, we show explicitly its equavalence to the steady-state Kalman filter. Existing results for...

This paper develops a systematic Markov Chain Monte Carlo (MCMC) framework based upon Efficient Importance Sampling (EIS) which can be used for the analysis of a wide range of econometric models involving integrals without an analytical solution. EIS is a simple, generic and yet accurate...

Forecasting large numbers of time series is a costly and time-consuming exercise. Before forecasting a large number of series that are logically connected in some way, the authors can first cluster them into groups of similar series. In this paper they investigate forecasting the series in each...