{"title":"一个世纪的资产配置碰撞风险","authors":"Mikhail Samonov, Nonna Sorokina","doi":"10.1057/s41260-024-00355-2","DOIUrl":null,"url":null,"abstract":"<p>We extend proxies of several popular asset allocation approaches—U.S. and Global 60/40, Diversified Multi-Asset, Risk Parity, Endowment, Factor-Based, and Dynamic asset allocation—using long-run return data for a variety of sub-asset classes and factors to test their long-term performance. We use equity and debt assets, commodities, alternatives, and indices to reconstruct the returns on allocation portfolios from 1926 to the present, the entire period for which comprehensive asset pricing data are available. We contribute to the existing literature by developing a laboratory for testing the performance of popular asset allocation strategies in a wide range of scenarios. We also aim to test the importance of the behavioral aspect of investment decisions for portfolio outcomes. In our framework, Factor-Based portfolios exhibit the best traditionally measured risk-adjusted returns over the long run. However, Dynamic asset allocation is most likely to reduce the risk of abandonment of the strategy by an investor and selling the portfolio in panic when they experience losses over their tolerance threshold, because the dynamic strategy exhibits lower expected drawdowns, even during severe market downturns. Across all strategies, risk-tolerant investors who rely on a longer history to set their expectations, whether based upon actual or extrapolated data, experience significantly better outcomes, particularly if their investment horizon includes times of crisis. This study informs portfolio managers, investment analysts, and advisors, as well as investors themselves, of the impact of information, persistence, and properties of various portfolio allocation methods on investment returns.</p>","PeriodicalId":45953,"journal":{"name":"Journal of Asset Management","volume":null,"pages":null},"PeriodicalIF":1.5000,"publicationDate":"2024-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A century of asset allocation crash risk\",\"authors\":\"Mikhail Samonov, Nonna Sorokina\",\"doi\":\"10.1057/s41260-024-00355-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>We extend proxies of several popular asset allocation approaches—U.S. and Global 60/40, Diversified Multi-Asset, Risk Parity, Endowment, Factor-Based, and Dynamic asset allocation—using long-run return data for a variety of sub-asset classes and factors to test their long-term performance. We use equity and debt assets, commodities, alternatives, and indices to reconstruct the returns on allocation portfolios from 1926 to the present, the entire period for which comprehensive asset pricing data are available. We contribute to the existing literature by developing a laboratory for testing the performance of popular asset allocation strategies in a wide range of scenarios. We also aim to test the importance of the behavioral aspect of investment decisions for portfolio outcomes. In our framework, Factor-Based portfolios exhibit the best traditionally measured risk-adjusted returns over the long run. However, Dynamic asset allocation is most likely to reduce the risk of abandonment of the strategy by an investor and selling the portfolio in panic when they experience losses over their tolerance threshold, because the dynamic strategy exhibits lower expected drawdowns, even during severe market downturns. Across all strategies, risk-tolerant investors who rely on a longer history to set their expectations, whether based upon actual or extrapolated data, experience significantly better outcomes, particularly if their investment horizon includes times of crisis. This study informs portfolio managers, investment analysts, and advisors, as well as investors themselves, of the impact of information, persistence, and properties of various portfolio allocation methods on investment returns.</p>\",\"PeriodicalId\":45953,\"journal\":{\"name\":\"Journal of Asset Management\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.5000,\"publicationDate\":\"2024-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Asset Management\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1057/s41260-024-00355-2\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Asset Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1057/s41260-024-00355-2","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
We extend proxies of several popular asset allocation approaches—U.S. and Global 60/40, Diversified Multi-Asset, Risk Parity, Endowment, Factor-Based, and Dynamic asset allocation—using long-run return data for a variety of sub-asset classes and factors to test their long-term performance. We use equity and debt assets, commodities, alternatives, and indices to reconstruct the returns on allocation portfolios from 1926 to the present, the entire period for which comprehensive asset pricing data are available. We contribute to the existing literature by developing a laboratory for testing the performance of popular asset allocation strategies in a wide range of scenarios. We also aim to test the importance of the behavioral aspect of investment decisions for portfolio outcomes. In our framework, Factor-Based portfolios exhibit the best traditionally measured risk-adjusted returns over the long run. However, Dynamic asset allocation is most likely to reduce the risk of abandonment of the strategy by an investor and selling the portfolio in panic when they experience losses over their tolerance threshold, because the dynamic strategy exhibits lower expected drawdowns, even during severe market downturns. Across all strategies, risk-tolerant investors who rely on a longer history to set their expectations, whether based upon actual or extrapolated data, experience significantly better outcomes, particularly if their investment horizon includes times of crisis. This study informs portfolio managers, investment analysts, and advisors, as well as investors themselves, of the impact of information, persistence, and properties of various portfolio allocation methods on investment returns.
期刊介绍:
The Journal of Asset Management covers:new investment strategies, methodologies and techniquesnew products and trading developmentsimportant regulatory and legal developmentsemerging trends in asset managementUnder the guidance of its expert Editors and an eminent international Editorial Board, Journal of Asset Management has developed to provide an international forum for latest thinking, techniques and developments for the Fund Management Industry, from high-growth investment strategies to modelling and managing risk, from active management to index tracking. The Journal has established itself as a key bridge between applied academic research, commercial best practice and regulatory interests, globally.Each issue of Journal of Asset Management publishes detailed, authoritative briefings, analysis, research and reviews by leading experts in the field, to keep subscribers up to date with the latest developments and thinking in asset management.Journal of Asset Management covers:asset allocation hedge fund strategies risk definition and management index tracking performance measurement stock selection investment methodologies and techniques portfolio management and weighting product development and innovation active asset management style analysis strategies to match client profiles time horizons emerging markets alternative investments derivatives and hedging instruments pensions economics