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dominate the traditional metrics during forecasting financial performance, especially in the presence of the use of machine … hybrid statistical and machine learning approaches, can improve forecasting accuracy. Integrating cutting-edge analytical …
Persistent link: https://www.econbiz.de/10015408386
While previous academic research highlights the potential of machine learning and big data for predicting corporate bond recovery rates, the operations management challenge is to identify the relevant predictive variables and the appropriate model. In this paper, we use meta-learning to combine...
Persistent link: https://www.econbiz.de/10013363030
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understanding mortality risk and longevity risk. Studies of mortality forecasting are of interest among actuaries and demographers … because mortality forecasting can quantify mortality and longevity risks. There is an abundance of literature on the topic of … modelling and forecasting mortality, which often leads to confusion in determining a particular model to be adopted as a …
Persistent link: https://www.econbiz.de/10013556651
Accurate forecasting of insurance claims is of the utmost importance for insurance activity as the evolution of claims … capital required (by the regulators) to absorb the assumed risks. The conventional claim forecasting methods attempt to fit … claims. This study offers a fresh approach in insurance claims forecasting. First, we introduce two novel sets of variables …
Persistent link: https://www.econbiz.de/10014375275
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Persistent link: https://www.econbiz.de/10015144111
Much of the debate around a potential British exit (Brexit) from the European Union has centred on the potential macroeconomic impact. In this paper, we instead focus on understanding market expectations for price action around the Brexit referendum date. Extracting implied distributions from...
Persistent link: https://www.econbiz.de/10011688238
We introduce a multistep-ahead forecasting methodology that combines empirical mode decomposition (EMD) and support … vector regression (SVR). This methodology is based on the idea that the forecasting task is simplified by using as input for …
Persistent link: https://www.econbiz.de/10011811500
We are interested in obtaining forecasts for multiple time series, by taking into account the potential nonlinear relationships between their observations. For this purpose, we use a specific type of regression model on an augmented dataset of lagged time series. Our model is inspired by dynamic...
Persistent link: https://www.econbiz.de/10011811615