Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/258123 
Year of Publication: 
2021
Citation: 
[Journal:] Risks [ISSN:] 2227-9091 [Volume:] 9 [Issue:] 2 [Article No.:] 34 [Publisher:] MDPI [Place:] Basel [Year:] 2021 [Pages:] 1-25
Publisher: 
MDPI, Basel
Abstract: 
Smart beta strategies across economic regimes seek to address inefficiencies created by market-based indices, thereby enhancing portfolio returns above traditional benchmarks. Our goal is to develop a strategy for re-hedging smart beta portfolios that shows the connection between multi-factor strategies and macroeconomic variables. This is done, first, by analyzing finite correlations between the portfolio weights and macroeconomic variables and, more remarkably, by defining an investment tilting variable. The latter is analyzed with a discriminant analysis approach with a twofold application. The first is the selection of the crucial re-hedging thresholds which generate a strong connection between factors and macroeconomic variables. The second is forecasting portfolio dynamics (gain and loss). The capability of forecasting is even more evident in the COVID-19 period. Analysis is carried out on the iShares US exchange traded fund (ETF) market using monthly data in the period December 2013-May 2020, thereby highlighting the impact of COVID-19.
Subjects: 
factor-based model
financial risk management
fintech risk management
market timing activity
smart beta
Persistent Identifier of the first edition: 
Creative Commons License: 
cc-by Logo
Document Type: 
Article
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