Stochastic model genetic programming: Deriving pricing equations for rainfall weather derivatives
- Submitting institution
-
The University of Kent
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 14749
- Type
- D - Journal article
- DOI
-
10.1016/j.swevo.2019.01.008
- Title of journal
- Swarm and Evolutionary Computation
- Article number
- -
- First page
- 184
- Volume
- 46
- Issue
- -
- ISSN
- 2210-6502
- Open access status
- Compliant
- Month of publication
- February
- Year of publication
- 2019
- URL
-
https://kar.kent.ac.uk/72082/
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- Yes
- Number of additional authors
-
3
- Research group(s)
-
-
- Citation count
- 3
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This work presents a novel Genetic Programming algorithm for pricing weather derivatives contracts, a real-world problem (rainfall prediction) affecting a large proportion of businesses. This paper is significant because, prior to this work there was no generally recognised pricing framework in the field. We provide a generalised framework applicable to all rainfall derivatives. The proposed algorithm outperformed six well-known machine learning algorithms and two well-known statistical methods.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
