径流组合的深度复制
Deep Replication of a Runoff Portfolio
摘要：
据我们所知，深度学习在量化风险管理领域的应用仍然是一个相对较新的现象。本文提出了深度资产负债管理（Deep~ALM）的核心概念，即在整个期限结构上进行资产和负债管理的技术变革。该方法对广泛的应用产生了深远的影响，例如财务人员的最佳决策，商品的最佳采购或水力发电厂的优化。作为一个副产品，基于目标的投资或资产负债管理（ALM）的有趣方面，在抽象的条款有关我们的社会的紧迫挑战预计一起。我们说明了在一个程式化的情况下的方法的潜力。
英文摘要：
To the best of our knowledge, the application of deep learning in the field of quantitative risk management is still a relatively recent phenomenon. This article presents the key notions of Deep Asset Liability Management (Deep~ALM) for a technological transformation in the management of assets and liabilities along a whole term structure. The approach has a profound impact on a wide range of applications such as optimal decision making for treasurers, optimal procurement of commodities or the optimisation of hydroelectric power plants. As a by-product, intriguing aspects of goal-based investing or Asset Liability Management (ALM) in abstract terms concerning urgent challenges of our society are expected alongside. We illustrate the potential of the approach in a stylised case.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
