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Smart beta exchange-traded funds and factor investing / Phillip A. Braun.

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SAGE Business Cases 2019 Annual Collection Available online

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Format:
Book
Author/Creator:
Braun, Phillip A. (Phillip Andrew), 1959- author.
Series:
SAGE Knowledge. Cases.
SAGE Knowledge. Cases
Language:
English
Subjects (All):
Exchange traded funds.
Stock index futures.
iShares Factor Strategies Group.
Physical Description:
1 online resource : illustrations.
Place of Publication:
London : Kellogg School of Management, 2018.
System Details:
text file
Summary:
It was early 2015 and executives in the iShares Factor Strategies Group were considering the launch of some new exchange-traded funds (ETFs). The new ETFs were in a class of ETFs called smart beta funds. Most traditional ETFs' portfolio weights were based on the market capitalization of a stock (stock price times the number of outstanding shares), but smart beta ETFs' weighting schemes were based on firms' financial characteristics or properties of their stock returns.The new smart beta multifactor ETFs being considered by iShares would provide investors with simultaneous exposure to four fundamental factors that had shown themselves historically to be significant in driving stock returns: the stock market value of a firm, the relative value of a firm's financial position, the quality of a firm's financial position, and the momentum a firm's stock price has had. While each of these factors existed in different combinations and different forms in ETFs already in the marketplace, no firm was currently offering these four as a combination in a multifactor ETF. The executives at iShares were unsure whether there would be demand in the marketplace for such multifactor ETFs, since their value added from an investor's portfolio perspective was unknown.
Notes:
Originally Published InBraun, P. (2018). Smart Beta Exchange-Traded Funds and Factor Investing. 5-417-752. Evanston, IL: Kellogg School of Management at Northwestern University.
No ILL or scholarly sharing allowed.
Description based on XML content.
ISBN:
9781526474995
OCLC:
1089141510
Access Restriction:
Restricted for use by site license.

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