{"title":"Systematic Asset Management","authors":"Tung-Lam Dao","doi":"10.2139/ssrn.3208574","DOIUrl":null,"url":null,"abstract":"Since the last decade, financial technology (Fintech) has made a lot progresses in many angles of the finance industry from the novel concepts of the transaction to the systematic/intelligent management of financial products. Back to the 80s, the first attempts to combine applied mathematics, numerical algorithms with high-performance computers in trading and portfolio construction gave birth to a new trend of asset management \"systematic asset management\". Employing computers to perform complex calculations, to estimate the optimal trading quantities have improved the gain probability and the risk management. Systematic asset management must be considered as one of the first revolutions in financial technology. However, it quickly became the industrial secret of many successful hedge funds such as Renaissance, D.E.Shaw, Two Sigmas, CFM, e.t.c. The 2008 crisis has changed the investment point of view of investors and the regulators. They required more and more efforts from the hedge fund industry and asset management in the transparency of their portfolios and their risk management. Some management styles such as \"Smart beta\" or \"Risk Parity\" were revealed to the large public with very detailed explanation both on the concept and the implementation. Recently, a new class of investment strategies named \"alternative beta\" or \"alternative risk premium\" was also opened to the public. It consists of combining well-known trading strategies with systematic risk management in order to offer high performance and decorrelated return to the market benchmark. These last evolutions allowed more and more opportunities for Fintech to improve the systematic asset management. Machine learning and AI can be employed to explore novel trading strategies, to detect anomal risks, to reduce the operational risks or to simulate stress-scenarios whereas blockchain is a great candidate for future improvement of the current transaction system. The objective of this note is to explain the main principles of the systematic asset management through some simple examples. We expect that our approach may be useful to identify the potential applications of Fintech in this domain.","PeriodicalId":369276,"journal":{"name":"ERPN: Social Innovation (Sub-Topic)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ERPN: Social Innovation (Sub-Topic)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3208574","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
Since the last decade, financial technology (Fintech) has made a lot progresses in many angles of the finance industry from the novel concepts of the transaction to the systematic/intelligent management of financial products. Back to the 80s, the first attempts to combine applied mathematics, numerical algorithms with high-performance computers in trading and portfolio construction gave birth to a new trend of asset management "systematic asset management". Employing computers to perform complex calculations, to estimate the optimal trading quantities have improved the gain probability and the risk management. Systematic asset management must be considered as one of the first revolutions in financial technology. However, it quickly became the industrial secret of many successful hedge funds such as Renaissance, D.E.Shaw, Two Sigmas, CFM, e.t.c. The 2008 crisis has changed the investment point of view of investors and the regulators. They required more and more efforts from the hedge fund industry and asset management in the transparency of their portfolios and their risk management. Some management styles such as "Smart beta" or "Risk Parity" were revealed to the large public with very detailed explanation both on the concept and the implementation. Recently, a new class of investment strategies named "alternative beta" or "alternative risk premium" was also opened to the public. It consists of combining well-known trading strategies with systematic risk management in order to offer high performance and decorrelated return to the market benchmark. These last evolutions allowed more and more opportunities for Fintech to improve the systematic asset management. Machine learning and AI can be employed to explore novel trading strategies, to detect anomal risks, to reduce the operational risks or to simulate stress-scenarios whereas blockchain is a great candidate for future improvement of the current transaction system. The objective of this note is to explain the main principles of the systematic asset management through some simple examples. We expect that our approach may be useful to identify the potential applications of Fintech in this domain.
近十年来,金融科技(Fintech)从新颖的交易概念到金融产品的系统化/智能化管理,在金融行业的多个角度都取得了很大的进步。早在上世纪80年代,将应用数学、数值算法与高性能计算机结合在交易和投资组合构建中的首次尝试,催生了资产管理的新趋势“系统化资产管理”。利用计算机进行复杂的计算,估计最优交易量,提高了获利概率和风险管理。系统化资产管理必须被视为金融技术的第一次革命之一。然而,它迅速成为许多成功的对冲基金的行业秘密,如文艺复兴,D.E.Shaw, Two Sigmas, CFM等。2008年的危机改变了投资者和监管机构的投资观点。它们要求对冲基金行业和资产管理公司在投资组合和风险管理的透明度方面做出越来越大的努力。一些管理风格,如“智能beta”或“风险平价”,向公众展示了非常详细的概念和实施解释。最近,一种名为“另类贝塔”或“另类风险溢价”的新投资策略也向公众开放。它将众所周知的交易策略与系统风险管理相结合,以提供高绩效和与市场基准无关的回报。这些最新的演变为金融科技提供了越来越多的机会来改善系统的资产管理。机器学习和人工智能可以用来探索新的交易策略,检测异常风险,降低操作风险或模拟压力场景,而区块链是未来改进当前交易系统的一个很好的候选者。本笔记的目的是通过一些简单的例子来解释系统资产管理的主要原则。我们期望我们的方法可能有助于确定金融科技在这一领域的潜在应用。