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Modern financial management is largely about risk management, which is increasingly data-driven. The problem is how to extract information from the data overload. It is here that advanced statistical and machine learning techniques can help. Accordingly, finance, statistics, and data analytics...
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rolling-windows based DYCI. Finally, we show that the TVP-VAR based index performs better in forecasting systemic events in …
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behaviors in any given situation. This work presents several scalable frameworks for modeling and forecasting agent behavior …, particularly in the realm of international security dynamics. A probabilistic logic formalism for modeling and forecasting behavior … of this problem, forecasting methods are also introduced that operate directly on time series data, rather than an …
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of multi-channel customer contact, organizational decision-makers often rely on robust but simplistic forecasting methods …. Although forecasting literature indicates that incorporating additional information into time series predictions adds value by … for call center arrivals' forecasting that is able to capture the dynamics of a time series and to include contextual …
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We perform a comprehensive examination of the recursive, comparative predictive performance of a number of linear and non-linear models for UK stock and bond returns. We estimate Markov switching, threshold autoregressive (TAR), and smooth transition autoregressive (STR) regime switching models,...
Persistent link: https://www.econbiz.de/10008990694
series has been use for the forecasting the shock occurring in the economic data series. Objective and Subjective technique …
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