Practical Applications of The Capacity of Factor Strategies

David Blitz, Thom Marchesini
{"title":"Practical Applications of The Capacity of Factor Strategies","authors":"David Blitz, Thom Marchesini","doi":"10.3905/pa.8.2.391","DOIUrl":null,"url":null,"abstract":"Practical Applications Summary In The Capacity of Factor Strategies, from the September 2019 issue of The Journal of Portfolio Management, David Blitz and Thom Marchesini, both of Robeco Asset Management, examine factor-investing strategies and the capacities needed to process these increasingly popular approaches. Focusing their research on the low-volatility factor, the authors conduct a simulation alongside current minimum-volatility indexes, with the simulation’s trades occurring more frequently and over a longer period than is currently standard with factor indexes. The simulation shows no performance loss and considerable capacity expansion over standard minimum-volatility indexes. The authors also conduct simulations with quality and value factor indexes, with similar results. The authors surmise that index-based factor strategies are currently subject to pronounced capacity constraints because most trades occur on just a few active days of rebalancing each year. This leads to liquidity squeezes and ultimately compromised returns. To add capacity and ameliorate these conditions, the authors advise implementation of more sophisticated factor-investing strategies, including more frequent rebalancing. They suggest spreading out trades over a larger number of days during the year to continuously leverage latent market liquidity. Active, frequent trading in smaller amounts, the authors advise, promotes greater capacity than more passive factor-index replication strategies that make infrequent but much larger trades. TOPICS: Factor-based models, style investing, analysis of individual factors/risk premia","PeriodicalId":179835,"journal":{"name":"Practical Application","volume":"59 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Practical Application","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3905/pa.8.2.391","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Practical Applications Summary In The Capacity of Factor Strategies, from the September 2019 issue of The Journal of Portfolio Management, David Blitz and Thom Marchesini, both of Robeco Asset Management, examine factor-investing strategies and the capacities needed to process these increasingly popular approaches. Focusing their research on the low-volatility factor, the authors conduct a simulation alongside current minimum-volatility indexes, with the simulation’s trades occurring more frequently and over a longer period than is currently standard with factor indexes. The simulation shows no performance loss and considerable capacity expansion over standard minimum-volatility indexes. The authors also conduct simulations with quality and value factor indexes, with similar results. The authors surmise that index-based factor strategies are currently subject to pronounced capacity constraints because most trades occur on just a few active days of rebalancing each year. This leads to liquidity squeezes and ultimately compromised returns. To add capacity and ameliorate these conditions, the authors advise implementation of more sophisticated factor-investing strategies, including more frequent rebalancing. They suggest spreading out trades over a larger number of days during the year to continuously leverage latent market liquidity. Active, frequent trading in smaller amounts, the authors advise, promotes greater capacity than more passive factor-index replication strategies that make infrequent but much larger trades. TOPICS: Factor-based models, style investing, analysis of individual factors/risk premia
要素策略容量的实际应用
在2019年9月出版的《投资组合管理杂志》上的《因子策略能力》一文中,来自Robeco资产管理公司的David Blitz和Thom Marchesini研究了因子投资策略以及处理这些日益流行的方法所需的能力。作者将研究重点放在低波动系数上,与当前的最低波动指数一起进行了模拟,与目前标准的因素指数相比,模拟的交易发生的频率更高,持续的时间更长。仿真结果表明,与标准的最小波动率指数相比,该方法没有性能损失,并且有相当大的容量扩展。作者还用质量和价值因子指标进行了模拟,得到了相似的结果。作者推测,基于指数的要素策略目前受到明显的产能限制,因为大多数交易发生在每年重新平衡的几个活跃日子里。这导致流动性紧缩,最终损害回报。为了增加产能和改善这些状况,作者建议实施更复杂的要素投资策略,包括更频繁地进行再平衡。他们建议将交易分散到一年中更多的天数,以持续利用潜在的市场流动性。作者建议,与被动的因子指数复制策略相比,积极、频繁的小额交易促进了更大的交易能力,后者的交易不频繁,但规模要大得多。主题:基于因素的模型,风格投资,个体因素/风险溢价分析
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信