Abstract:In this paper, a Kalman filter-type model is used to extract a global stochastic trend from discrete non-synchronous data on daily stock market index returns from different markets.1 The model allows for the autocorrelation in the global stochastic trend, which means that its increments are predictable. It does not necessarily mean the predictability of market returns, since the global trend is unobservable. The performance of the model for the forecast of market returns is explored for three markets: Japan, UK, USA.
Abstract:In this paper, a Kalman filter-type model is used to extract a global stochastic trend from discrete non-synchronous data on daily stock market index returns from different markets.1 The model allows for the autocorrelation in the global stochastic trend, which means that its increments are predictable. It does not necessarily mean the predictability of market returns, since the global trend is unobservable. The performance of the model for the forecast of market returns is explored for three markets: Japan, UK, USA.
A comprehensive approach to assessing risks and uncertainties using a 3D geological and hydrodynamic model of the field, as well as mapping the least risky zones in terms of the availability of hydrocarbon reserves, was applied in a field in Eastern Ustyurt. The decision to develop hydrocarbon reserves takes into account geological and technological uncertainties. Selecting intervals with increased permeability based on core data by "typing" the section is proposed. The main parameters affecting the reliability of hydrocarbon reserves were analyzed, and the ranges of their changes were determined. The reliability of the structural frame position was evaluated. Algorithms for automating the process of evaluating the best drilling direction in the presence of technical parameter uncertainties are proposed. This differentiated approach to workover planning takes into account general limitations and technological uncertainties.
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