تقرير
Risk Sharing with Deep Neural Networks
| العنوان: | Risk Sharing with Deep Neural Networks |
|---|---|
| المؤلفون: | Burzoni, Matteo, Doldi, Alessandro, Compagnoni, Enea Monzio |
| سنة النشر: | 2022 |
| المجموعة: | Mathematics Quantitative Finance |
| مصطلحات موضوعية: | Quantitative Finance - Risk Management, Mathematics - Probability |
| الوصف: | We consider the problem of optimally sharing a financial position among agents with potentially different reference risk measures. The problem is equivalent to computing the infimal convolution of the risk metrics and finding the so-called optimal allocations. We propose a neural network-based framework to solve the problem and we prove the convergence of the approximated inf-convolution, as well as the approximated optimal allocations, to the corresponding theoretical values. We support our findings with several numerical experiments. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2212.11752 |
| رقم الأكسشن: | edsarx.2212.11752 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |