{"title":"Asset allocation models for big tech stocks: The importance of lower partial moments and short length windows","authors":"","doi":"10.1016/j.bir.2024.05.006","DOIUrl":null,"url":null,"abstract":"<div><p>The group of companies formed by Meta, Apple, Microsoft, Amazon and Alphabet have become a successful investment alternative in the U.S. stock market. In this context, the aim of this research is to provide investment strategies based on these companies to the challenge of how individual investors should allocate their funds in a portfolio and outperform benchmarks such as the SPY ETF or a naïve portfolio. To this end, we developed a total of 20 asset allocation models and constructed portfolios with different rebalancing periods between April 2014 and June 2022. Our overall results reveal that a combination of a short window length for estimating the parameters of the asset allocation models and a procedure that takes downside risk into account, more precisely the Lower Partial Moment approach, significantly outperforms the alternative of investing in the SPY ETF and also the naïve portfolio.</p></div>","PeriodicalId":46690,"journal":{"name":"Borsa Istanbul Review","volume":null,"pages":null},"PeriodicalIF":6.3000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2214845024000851/pdfft?md5=19a86e1536faf1b55ab8768c91ee8e9e&pid=1-s2.0-S2214845024000851-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Borsa Istanbul Review","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2214845024000851","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0
Abstract
The group of companies formed by Meta, Apple, Microsoft, Amazon and Alphabet have become a successful investment alternative in the U.S. stock market. In this context, the aim of this research is to provide investment strategies based on these companies to the challenge of how individual investors should allocate their funds in a portfolio and outperform benchmarks such as the SPY ETF or a naïve portfolio. To this end, we developed a total of 20 asset allocation models and constructed portfolios with different rebalancing periods between April 2014 and June 2022. Our overall results reveal that a combination of a short window length for estimating the parameters of the asset allocation models and a procedure that takes downside risk into account, more precisely the Lower Partial Moment approach, significantly outperforms the alternative of investing in the SPY ETF and also the naïve portfolio.
期刊介绍:
Peer Review under the responsibility of Borsa İstanbul Anonim Sirketi. Borsa İstanbul Review provides a scholarly platform for empirical financial studies including but not limited to financial markets and institutions, financial economics, investor behavior, financial centers and market structures, corporate finance, recent economic and financial trends. Micro and macro data applications and comparative studies are welcome. Country coverage includes advanced, emerging and developing economies. In particular, we would like to publish empirical papers with significant policy implications and encourage submissions in the following areas: Research Topics: • Investments and Portfolio Management • Behavioral Finance • Financial Markets and Institutions • Market Microstructure • Islamic Finance • Financial Risk Management • Valuation • Capital Markets Governance • Financial Regulations