Case Study: Fama-French Five-Factor Model and iShares Smart Beta ETFs

This assignment delves into the Fama-French five-factor model and the iShares Smart Beta concept. It begins by outlining the Fama-French model's findings, including the size, value, profitability, and investment factors, and contrasts these with the Capital Asset Pricing Model (CAPM). The analysis then explores the iShares Smart Beta concept, explaining its construction, which combines size, value, quality, and momentum factors using MSCI's bottom-up approach, and its application in both active and passive investment strategies. The assignment highlights the differences between iShares Smart Beta and traditional multifactor ETFs. The document also includes a comprehensive reference list. The assignment addresses key aspects of investment management and portfolio construction, providing a detailed understanding of factor-based investing and its practical applications in the financial market.

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INVESTMENT MANAGEMENT
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Q.1 Fama French’s Findings
Introduction
Asset pricing models keep evolving with new discoveries and advancement in
knowledge. Smart beta, alternative beta or strategic beta is a popular finance concept. Several
risk factors have been used over the years to explain excess returns. The Pricing Model was
developed in the sixties was the first to define risk and its returns by looking at its market
beta exposure. The beta is the metric used to gauge the risk relative to the overall market.
The Fama French model came with value additions like relating momentum to mutual fund
returns. The model still contains irregularities although it gives a good account of average
returns. Furthermore, it does not expound on the small stocks’ low returns despite their
massive investment, a similarity shared with the previous factor models. The exclusion of the
HML value factor records average returns and it captures the five factor model rendering it
redundant. The first Fama French findings were on the association between the portfolio
betas and the average returns (Allen & McAleer, 2018 p.18). Theoretically, there was no
strong upward-sloping association between the portfolio betas and the returns as would have
been expected (Fama & French, 2015 p.10). This led to the conclusion that the CAPM theory
(Barucci & Fontana, 2017 p.458) could not explain average returns well. The second factor
was on size factor, which is the firm’s size measured by market capitalization (Fama &
French, 2015 p.12). Through controlling other factors, Fama-French showed that size is
relative to the firm's profitability (LEONG, 2015 p.33). Since the size is correlated to
information uncertainty that is, smaller firms are not often followed by investments banks
while simultaneously have more volatile fundamentals.
Value factor was also from the Fama-French findings, which was the B-M ratio which
is the ratio of firms’ book value to its present capitalization (Fama & French, 2015 p.13). The
portfolios which had a B-M ratio that was better had returns that were better than average.

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The Fama-French argued that the positive association of average returns and B-M ratio was
due to better B-M stocks are less profitable and relatively distressed hence firms with this
stocks were riskier and had to have better than average returns.
Profitability factor; the ratio of firms operating profits to book value was also in the
Fama-French findings. They argued that productive firms should have better returns
compared to unproductive firms. Furthermore the better the profitability proved to have better
quality in the firms (Hammond et al., 2015 p.225).
The finding on the investment factor by Fama-French was through ranking and
sorting the firms in quartiles portfolios (Asness et al., 2015 p.37). The conservative levels of
investments had better returns than aggressive firms. A rise in firms’ investments implied that
Lower investment levels were seen to yield better expected earnings when the firms' revenue
was held constant (Gustafsson & Gustavsson, 2019 p.11).
The SMB portfolio catered for size, the HML which handled the B-M factor, the
RMW which handled the factor on profitability and the CMA this handles the investment
spending factor (Anderson, 2016 p.19).
Q.2 ishares Smart Beta Concept
Ishares multifactor EFTs was a combination of size, value, quality, and momentum
factors together encompassing both domestic and international stocks. The multifactor EFTs
that Ishares were considering was capturing three to four factors simultaneously to the new
market. The iShare EFTs were better than the typical multifactor EFTs. The iShare smart beta
constructed was in a different way than the usual smart beta. The iShare smart beta
constructed with the allowance of all factors the size, value, quality and momentum factors
which were developed by the MSCI incorporation which was known for indexes,
performance reporting, and risk management tools (Blitz et al., 2019 p.129). In the creating

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of the diversified multifactor indexes; MSCI assigned a weight to each stock that was an
average of stocks individuals Z-scores for size, value, quality, and the momentum indexes.
The MSCI multifactor Beta indexes were constructed differently from the normal multifactor
EFTs that were already in the market (Braun,2018 p 64).. Normal multifactor EFTs were
through averaging single factor indexes through the top-down approach, but the MSCI used
the bottom-up approach, weighting each stock multifactor index by the set of its fundamental
valuation characteristics; the Z-scores. The bottom-up model would optimize the exposure to
these factors to a better degree than the top-down approach.
The iShare smart Beta fitted correctly in active and passive investing (Clift, 2016
p.34). The iShare smart Beta EFTs actively fitted through weights from the resultant included
Z-scores primarily deviating from the standard market capitalization weights. The iShare
smart Beta captured the size, value, quality, and momentum factors that would greatly help
standard diversification of investments (Carson, Shores & Nefouse, 2017 p.71). iShare smart
also passively mimicked the termed factor indexes, and hence for the Ishares case, no input
could be required. In conclusion although they provide value and a reliable description of
projected returns, asset pricing models are not always correct. The Fama French five factor
models are adopted internationally in evaluation of portfolio performance. Unlike previous
models the Fama French five factor models have yet to show significant improvement from
previous models as most investors still stick to the three factor model.

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References List
Allen, D.E. and McAleer, M., 2018. 'Choosing Factors' by Fama and French (2018):
A Comment. Available at SSRN 3272608.
Anderson, N., 2016. The Performance of Relative-Value Equity Strategies. Available
at SSRN 2782945.
Asness, C., Frazzini, A., Israel, R. and Moskowitz, T., 2015. Fact, fiction, and value
investing. The Journal of Portfolio Management, 42(1), pp.34-52.
Barucci, E. and Fontana, C., 2017. Financial Markets Microstructure. In Financial
Markets Theory (pp. 583-659). Springer, London.
Blitz, D., Huisman, R., Swinkels, L. and van Vliet, P., 2019. Media Attention and the
Volatility Effect. Available at SSRN 3403466.
Braun, Phillip A. Smart beta exchange-traded funds and factor investing. Kellogg
School of Management, 2018.
Carson, B., Shores, S. and Nefouse, N., 2017. Life-Cycle Investing and Smart Beta
Strategies. The Journal of Retirement, 5(2), pp.66-82.
Clift, T., 2016. Modern Investing Trends Reframe Active vs. Passive Debate. Journal
of Financial Planning, 29(8), p.34.
Fama, E.F. and French, K.R., 2015. A five-factor asset pricing model. Journal of
financial economics, 116(1), pp.1-22.
Gustafsson, F. and Gustavsson, R., 2019. Testing the Performance of the Capital
Asset Pricing Model and the Fama-French Three-Factor Model-A study on the
Swedish Stock Market between 2014-2019.
Hammond, P.B., Leibowitz, M.L., Siegel, L.B., Ibbotson, R.G., Asness, C.S.,
Dimson, E., Marsh, P., Staunton, M., Grinold, R.C., Kroner, K.F. and Arnott, R.D.,
2015. Rethinking the equity risk premium.

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LEONG, T. (2015). The effectiveness of the capital asset pricing model (CAPM) and
Fama French 3-factor model evidence from Bursa Malaysia.