Forecasting and Time Series Analysis
A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Economics and Finance".
Deadline for manuscript submissions: 30 June 2025 | Viewed by 12747
Special Issue Editor
2. Department of Finance, IPAG Business School, IPAG LAB, 184 Boulevard Saint-Germain, 75006 Paris, France
Interests: econometric theory; financial econometrics; time series and panel data econometrics; applied mathematics; artificial intelligence methods; signal processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The main objective of this Special Issue of JRFM, entitled "Forecasting and Time Series Analysis", is to explore new approaches to time series forecasting that deepen our understanding of forecasting techniques. The modelling and prediction of time series are crucial prerequisites for risk management, the development of pricing formulas for investment analysis, the negotiation of short- and long-term trading positions, and the construction of hedging strategies. Indeed, several parametric, non-parametric, and/or hybrid forecasting approaches have emerged in recent years. The most suitable prediction technique is the one that reproduces the inherent characteristics of the process under investigation and achieves a better prediction performance across different horizons. As contributions to this field of research, papers submitted to this Special Issue will aim to assist decision makers in the forecasting of suitable responses to major events and processes. Contributions that focus on novel hybrid forecasting methodologies and neural network approaches are encouraged, as are those drawing on parsimonious modelling techniques.
Dr. Heni Boubaker
Guest Editor
Manuscript Submission Information
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Keywords
- time series
- modelling methods
- neural networks
- hybrid models
- forecasting approach
- prediction performance
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