1.
Is factor investing a
bubble?
René M. Stulz

2.
Agenda
•Present at the creation: A historical
perspective
•Are there 447 factors?
•Demand and supply for factor
exposures
•Risks of factor investing for investors
and the economy
•Is there a bubble?

3.
Historical perspective

4.
MIT, 1970s
• Merton develops the ICAPM.
• Key insight: Investor welfare does not depend only
on wealth.
• Example: Investors may be worse off if interest rate
is low – a bad state of the world.
• Implication: Some investors want to hedge against
bad states of the world so that assets whose return
is high in bad states of the world have higher
expected returns.

5.
Journal of Finance, 1992
• Accepted for publication Fama/French,
The cross-section of expected returns.
• 17,467 Google citations.
• Size and Value explain cross-section
well; beta does not.
• Long-short factor portfolios earn
premiums that are compensation for
risk.
• Consistent with ICAPM.

6.
Journal of Finance, 1994
• Lakonishok, Shleifer, Vishny,
Contrarian investment, extrapolation,
and risk
• Argue that factor premiums are not
compensation for risk but instead
reflect characteristics that investors
value.
• Reflect behavioral biases.

7.
Since then: All anomalies (red),
unique and published (green)
(Hou, Chen, Zhang)
0
50
100
150
200
250
300
350
400
450
500
1972
1973
1974
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016

8.
Why so many?
• Good way to get into journals for academics. That’s
how they get tenure and raises.
• Most don’t hold up if micro-caps are removed from
sample (Hou, Chen, and Zhang).
• Most don’t hold up if one accounts for publication
bias and weaken post-publication (Schwert,
McLean and Pontiff, Hou, Chen, and Zhang).
• Still, there is a large number of anomalies that
survive even then.

9.
Rational or irrational?
• Not much progress in the rational/irrational
debate.
• Most anomalies accounted for by recent
models:
• Fama-French five-factor model;
• Hou, Chen, and Zhang four-factor model.
• Explaining anomalies with anomalies?

10.
Does it matter where premiums
come from?
• Investors who care less about a risk or a
characteristic than the market as a whole can make
themselves better off by bearing more of that risk
or holding more of that characteristic than the
typical investor.
• It does not matter where the compensation comes
from.
• Future premiums are the ones that matter for
investors.

11.
Factor premium persistence
• Widespread belief that rational premiums are more
robust.
• Not clear because demand and supply affects all
factor premiums.
• Good reason to believe that over time demand for
stocks that earn higher expected returns increases
and supply decreases, so that premiums fall.

12.
Demand and supply of factor
exposures
Factor premium
Quantity
Demand from investors
Supply by firms
P2
P1

13.
Limits to demand for factor
exposures
• There are limits to the demand for factor
exposures:
• May require short-sales, but ability to short-sell is
limited.
• May require leverage.
• May require positions in high transaction cost stocks.
• Imposes loss of diversification.
• Can have extended periods of poor returns.

14.
Demand shifts
• Demand can shift to the right as limits to arbitrage
decrease and hence decrease factor premiums:
• Increases in market liquidity.
• Changes in the technology for short-selling.
• ETFs.
• Demand can shift to the right or to the left as
investors find a risk more or less costly or value a
characteristic more or less.
• If academia does its job, demand should shift to the
right. As more investors know about compensation
for risk or characteristics, demand should shift.

15.
Supply of factor exposures
• Corporations supply factor exposures, but supply can
slow moving.
• If a corporation’s exposure to a factor leads to higher
cost of capital, supply of factor exposure will fall.
• Example of size. If being small involves a higher cost of
capital, it pays for firms to merge. We would see fewer
small firms.
• Example of low book-to-market firms. These firms have
low cost of equity, so they issue more equity.
• These changes affect the supply of factor exposures.

16.
Fewer listings than in 1975
0
1000
2000
3000
4000
5000
6000
7000
8000
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
No.oflistings
number of listings

17.
Average market cap increased sharply in
constant dollars
-
1,000,000.00
2,000,000.00
3,000,000.00
4,000,000.00
5,000,000.00
6,000,000.00
7,000,000.00
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Average firm market
capitalization

18.
Fraction of firms with low market cap (<$100
million in 2015 dollars)
0.000
0.100
0.200
0.300
0.400
0.500
0.600
0.700
1975
1976
1977
1978
1979
1980
1981
1982
1983
1984
1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
Fraction of firms with low
market capitalization

19.
Size effect
1963-2014: 0.58% (t=2.83)
1963=1983: 1.16% (t=3.28)
1983-2014: 0.21% (t=-0.84)
Source: Hou and van Dijk, Resurrecting the size
effect, July 2017

20.
The future
• As demand for factor exposures increases,
factor premia must fall.
• Supply response from corporations: they will
supply fewer exposures that increase their cost
of equity.
• These mechanisms suggest lower factor
premiums in the future.
• But: There are limitations to taking advantage
of factor premiums: limits to short-sales, limited
liquidity, taxes, and so on.
• Realized factor premiums are volatile, so that
forecasting factor premiums is hard.

21.
Risks of factor investing
• Fall in factor premium.
– Stocks long the exposure increase in value
– Short-run dislocation if investors run away from the stocks
– Stocks short the exposure decrease in value.
– Short-run dislocation if investors close positions quickly.
• Increase in factor premium.
– Stocks long the exposure decrease in value.
– Stocks short the exposure increase in value.
– Whipsaw!
• There is a diversification cost.

22.
Is it a bubble?
• Only in the identification of factors by academics.
• In practice, it is a sound approach supported both by theory
and empirics.
• Unfortunately, in the investing world, expected alpha is
inversely related to the number of smart asset managers
trying to produce alpha.
• If there is too much enthusiasm for factors, there must be
some good stock picking opportunities.
22