Large scale mean-variance strategies in the U.S. stock market

Luca Pezzo; Lei Wang; Duygu Zirek

doi:10.1016/j.ribaf.2023.102062

Large scale mean-variance strategies in the U.S. stock market

Luca Pezzo, Lei Wang, Duygu Zirek

Accounting and Finance

Montclair State University

Research output: Contribution to journal › Review article › peer-review

Abstract

We provide an extensive analysis of the profitability of large-scale Mean-Variance (MV) strategies in the US stock market. Implementing MV strategies has never been so rewarding as recently. MV strategies work best in periods where their parameters are more accurately estimated, making strategies more stable and able to adapt to changes in the investment opportunity set. Minimizing over costs is better than going for the classical approach, especially for strategies that target higher returns. This is because cost optimization puts a stabilizing economic bound on the weights, lowering downside risk and enabling better scaling, while driving execution costs toward zero.

Original language	English
Article number	102062
Journal	Research in International Business and Finance
Volume	66
DOIs	https://doi.org/10.1016/j.ribaf.2023.102062
State	Published - Oct 2023

ASJC Scopus subject areas

Business, Management and Accounting (miscellaneous)
Finance

Keywords

Estimation error
Market-timing
Mean-Variance
Profitability
Transaction costs

Access to Document

10.1016/j.ribaf.2023.102062

Cite this

@article{50d52939b2ac4fb0a036a376a48a1b5b,

title = "Large scale mean-variance strategies in the U.S. stock market",

abstract = "We provide an extensive analysis of the profitability of large-scale Mean-Variance (MV) strategies in the US stock market. Implementing MV strategies has never been so rewarding as recently. MV strategies work best in periods where their parameters are more accurately estimated, making strategies more stable and able to adapt to changes in the investment opportunity set. Minimizing over costs is better than going for the classical approach, especially for strategies that target higher returns. This is because cost optimization puts a stabilizing economic bound on the weights, lowering downside risk and enabling better scaling, while driving execution costs toward zero.",

keywords = "Estimation error, Market-timing, Mean-Variance, Profitability, Transaction costs",

author = "Luca Pezzo and Lei Wang and Duygu Zirek",

note = "Publisher Copyright: {\textcopyright} 2023 Elsevier B.V.",

year = "2023",

month = oct,

doi = "10.1016/j.ribaf.2023.102062",

language = "English",

volume = "66",

journal = "Research in International Business and Finance",

issn = "0275-5319",

publisher = "Elsevier BV",

}

TY - JOUR

T1 - Large scale mean-variance strategies in the U.S. stock market

AU - Pezzo, Luca

AU - Wang, Lei

AU - Zirek, Duygu

PY - 2023/10

Y1 - 2023/10

N2 - We provide an extensive analysis of the profitability of large-scale Mean-Variance (MV) strategies in the US stock market. Implementing MV strategies has never been so rewarding as recently. MV strategies work best in periods where their parameters are more accurately estimated, making strategies more stable and able to adapt to changes in the investment opportunity set. Minimizing over costs is better than going for the classical approach, especially for strategies that target higher returns. This is because cost optimization puts a stabilizing economic bound on the weights, lowering downside risk and enabling better scaling, while driving execution costs toward zero.

AB - We provide an extensive analysis of the profitability of large-scale Mean-Variance (MV) strategies in the US stock market. Implementing MV strategies has never been so rewarding as recently. MV strategies work best in periods where their parameters are more accurately estimated, making strategies more stable and able to adapt to changes in the investment opportunity set. Minimizing over costs is better than going for the classical approach, especially for strategies that target higher returns. This is because cost optimization puts a stabilizing economic bound on the weights, lowering downside risk and enabling better scaling, while driving execution costs toward zero.

KW - Estimation error

KW - Market-timing

KW - Mean-Variance

KW - Profitability

KW - Transaction costs

UR - http://www.scopus.com/inward/record.url?scp=85169339547&partnerID=8YFLogxK

U2 - 10.1016/j.ribaf.2023.102062

DO - 10.1016/j.ribaf.2023.102062

M3 - Review article

SN - 0275-5319

VL - 66

JO - Research in International Business and Finance

JF - Research in International Business and Finance

M1 - 102062

ER -

Large scale mean-variance strategies in the U.S. stock market

Abstract

ASJC Scopus subject areas

Keywords

Access to Document

Other files and links

Fingerprint

Cite this