Introduction
The Model
Empirical Results
Conclusion
The Demographics of Innovation and Asset
Returns
Nicolae Garleanu1
1
Leonid Kogan2
UC Berkeley, NBER and CEPR
2
3
Stavros Panageas3
MIT and NBER
LBS, Chicago Booth and NBER
October 2009
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
1 / 27
Introduction
The Model
Empirical Results
Conclusion
Outline
1
Introduction
2
The Model
3
Empirical Results
4
Conclusion
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
2 / 27
Introduction
The Model
Empirical Results
Conclusion
Outline
1
Introduction
2
The Model
3
Empirical Results
4
Conclusion
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
3 / 27
Introduction
The Model
Empirical Results
Conclusion
Contribution
New description of aggregate fundamental risk
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
4 / 27
Introduction
The Model
Empirical Results
Conclusion
Contribution
New description of aggregate fundamental risk
Systematic risk factor created by innovation: displacement risk
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
4 / 27
Introduction
The Model
Empirical Results
Conclusion
Contribution
New description of aggregate fundamental risk
Systematic risk factor created by innovation: displacement risk
Empirical evidence for displacement risk
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
4 / 27
Introduction
The Model
Empirical Results
Conclusion
Contribution
New description of aggregate fundamental risk
Systematic risk factor created by innovation: displacement risk
Empirical evidence for displacement risk
Value-growth factor and the value premium, equity premium
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
4 / 27
Introduction
The Model
Empirical Results
Conclusion
Contribution
New description of aggregate fundamental risk
Systematic risk factor created by innovation: displacement risk
Empirical evidence for displacement risk
Value-growth factor and the value premium, equity premium
Long-horizon asset allocation and risk faced by retail investors
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
4 / 27
Introduction
The Model
Empirical Results
Conclusion
Motivation
Innovation generates systematic risks
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
5 / 27
Introduction
The Model
Empirical Results
Conclusion
Motivation
Innovation generates systematic risks
Existing firms may lose market share to competition
Risk to financial capital
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
5 / 27
Introduction
The Model
Empirical Results
Conclusion
Motivation
Innovation generates systematic risks
Existing firms may lose market share to competition
Risk to financial capital
Human capital of the current generation of workers is less
compatible with new technologies than human capital of new
generations
Risk to human capital
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
5 / 27
Introduction
The Model
Empirical Results
Conclusion
Motivation
Innovation generates systematic risks
Existing firms may lose market share to competition
Risk to financial capital
Human capital of the current generation of workers is less
compatible with new technologies than human capital of new
generations
Risk to human capital
Displacement Risk
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
5 / 27
Introduction
The Model
Empirical Results
Conclusion
Motivation
Benefits of future technological innovation will be partly
captured by the innovators creating new firms and new
generations of workers with superior human capital
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
6 / 27
Introduction
The Model
Empirical Results
Conclusion
Motivation
Benefits of future technological innovation will be partly
captured by the innovators creating new firms and new
generations of workers with superior human capital
Risk sharing is not perfect: no trading with future generations
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
6 / 27
Introduction
The Model
Empirical Results
Conclusion
Motivation
Benefits of future technological innovation will be partly
captured by the innovators creating new firms and new
generations of workers with superior human capital
Risk sharing is not perfect: no trading with future generations
Older cohorts of agents cannot hedge displacement risk
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
6 / 27
Introduction
The Model
Empirical Results
Conclusion
Motivation
Benefits of future technological innovation will be partly
captured by the innovators creating new firms and new
generations of workers with superior human capital
Risk sharing is not perfect: no trading with future generations
Older cohorts of agents cannot hedge displacement risk
Displacement risk is a priced risk factor
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
6 / 27
Introduction
The Model
Empirical Results
Conclusion
Key Implications
Standard Consumption-CAPM is misspecified: omits
displacement risk
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
7 / 27
Introduction
The Model
Empirical Results
Conclusion
Consumption Risk
SDF = marginal rate of substitution for the same agent
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
8 / 27
Introduction
The Model
Empirical Results
Conclusion
Consumption Risk
SDF = marginal rate of substitution for the same agent
14
Log Aggregate consumption
log consumption
12
Displacement
Risk
10
Time s
8
Log Consumption of agents born
before time s
6
4
2
0
0
100
200
300
400
500 600
Quarters
Garleanu, Kogan, Panageas (2009)
700
800
900
1000
Innovation and Asset Returns
October 2009
8 / 27
Introduction
The Model
Empirical Results
Conclusion
Consumption Risk
SDF = marginal rate of substitution for the same agent
14
log consumption
Future per-capita
aggregate consumption is
not the same as the future
per-capita consumption of
the current population of
agents
Log Aggregate consumption
12
Displacement
Risk
10
Time s
8
Log Consumption of agents born
before time s
6
4
2
0
0
100
200
300
400
500 600
Quarters
Garleanu, Kogan, Panageas (2009)
700
800
900
1000
Innovation and Asset Returns
October 2009
8 / 27
Introduction
The Model
Empirical Results
Conclusion
Consumption Risk
SDF = marginal rate of substitution for the same agent
14
log consumption
Future per-capita
aggregate consumption is
not the same as the future
per-capita consumption of
the current population of
agents
Log Aggregate consumption
12
Displacement
Risk
10
Time s
8
Log Consumption of agents born
before time s
6
4
2
0
0
100
200
300
400
ξt +1
=β
ξt
|
500 600
Quarters
700
800
1000
−γ −γ
1
ct +1,t +1
×
1−λ
1−λ
Y
{z
} |
{z t +1
}
Yt +1
Yt
Standard Term
Garleanu, Kogan, Panageas (2009)
900
Displacement correction
Innovation and Asset Returns
October 2009
8 / 27
Introduction
The Model
Empirical Results
Conclusion
Key Implications
Standard Consumption-CAPM is misspecified: omits
displacement risk
Value-growth factor captures exposure to displacement risk
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
9 / 27
Introduction
The Model
Empirical Results
Conclusion
Key Implications
Standard Consumption-CAPM is misspecified: omits
displacement risk
Value-growth factor captures exposure to displacement risk
Value premium due to hedging demand for growth stocks
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
9 / 27
Introduction
The Model
Empirical Results
Conclusion
Hedging Demand and the Value Premium
Some firms more innovative than others, higher valuation
ratios: growth firms
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
10 / 27
Introduction
The Model
Empirical Results
Conclusion
Hedging Demand and the Value Premium
Some firms more innovative than others, higher valuation
ratios: growth firms
Growth and value firms have unequal exposure to innovation
shocks ⇒ growth-value factor
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
10 / 27
Introduction
The Model
Empirical Results
Conclusion
Hedging Demand and the Value Premium
Some firms more innovative than others, higher valuation
ratios: growth firms
Growth and value firms have unequal exposure to innovation
shocks ⇒ growth-value factor
Growth-value factor tracks displacement shocks ⇒ priced risk
factor
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
10 / 27
Introduction
The Model
Empirical Results
Conclusion
Hedging Demand and the Value Premium
Some firms more innovative than others, higher valuation
ratios: growth firms
Growth and value firms have unequal exposure to innovation
shocks ⇒ growth-value factor
Growth-value factor tracks displacement shocks ⇒ priced risk
factor
Growth firms provide a valuable hedge against displacement
risk ⇒ positive value premium
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
10 / 27
Introduction
The Model
Empirical Results
Conclusion
Key Implications
Standard Consumption-CAPM is misspecified: omits
displacement risk
Value-growth factor captures exposure to displacement risk
Value premium due to hedging demand for growth stocks
Long-horizon investing: indexing 6= keeping up
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
11 / 27
Introduction
The Model
Empirical Results
Conclusion
Long-Horizon Investing
An average investor cannot beat the market
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
12 / 27
Introduction
The Model
Empirical Results
Conclusion
Long-Horizon Investing
An average investor cannot beat the market
Popular advice: index, stay average
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
12 / 27
Introduction
The Model
Empirical Results
Conclusion
Long-Horizon Investing
An average investor cannot beat the market
Popular advice: index, stay average
Holding the market does not protect against displacement risk
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
12 / 27
Introduction
The Model
Empirical Results
Conclusion
Long-Horizon Investing
An average investor cannot beat the market
Popular advice: index, stay average
Holding the market does not protect against displacement risk
A typical investor will fall behind the “market” on average!
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
12 / 27
Introduction
The Model
Empirical Results
Conclusion
Long-Horizon Investing
An average investor cannot beat the market
Popular advice: index, stay average
Holding the market does not protect against displacement risk
A typical investor will fall behind the “market” on average!
A growth tilt in the portfolio could help mitigate displacement
risk, but it is costly
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
12 / 27
Introduction
The Model
Empirical Results
Conclusion
Outline
1
Introduction
2
The Model
3
Empirical Results
4
Conclusion
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
13 / 27
Introduction
The Model
Empirical Results
Conclusion
Agents
Arrive and die randomly each period
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
14 / 27
Introduction
The Model
Empirical Results
Conclusion
Agents
Arrive and die randomly each period
Supply labor to firms, trade in financial markets
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
14 / 27
Introduction
The Model
Empirical Results
Conclusion
Agents
Arrive and die randomly each period
Supply labor to firms, trade in financial markets
Behave rationally and competitively
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
14 / 27
Introduction
The Model
Empirical Results
Conclusion
Technology
Representative competitive firm produces the final
consumption good using labor and intermediate goods
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
15 / 27
Introduction
The Model
Empirical Results
Conclusion
Technology
Representative competitive firm produces the final
consumption good using labor and intermediate goods
Many intermediate goods produced by monopolistically
competitive firms
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
15 / 27
Introduction
The Model
Empirical Results
Conclusion
Technology
Representative competitive firm produces the final
consumption good using labor and intermediate goods
Many intermediate goods produced by monopolistically
competitive firms
Innovation = Increased variety of intermediate goods
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
15 / 27
Introduction
The Model
Empirical Results
Conclusion
Technology
Representative competitive firm produces the final
consumption good using labor and intermediate goods
Many intermediate goods produced by monopolistically
competitive firms
Innovation = Increased variety of intermediate goods
Innovation ⇒ Higher output and more competition between
intermediate-good producers
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
15 / 27
Introduction
The Model
Empirical Results
Conclusion
Innovation
Inventions, firms, and inventors
Inventions are patents for production of new intermediate
goods
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
16 / 27
Introduction
The Model
Empirical Results
Conclusion
Innovation
Inventions, firms, and inventors
Inventions are patents for production of new intermediate
goods
Intellectual property of inventions belongs to inventors (new
firms) and old firms
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
16 / 27
Introduction
The Model
Empirical Results
Conclusion
Innovation
Inventions, firms, and inventors
Inventions are patents for production of new intermediate
goods
Intellectual property of inventions belongs to inventors (new
firms) and old firms
New firms can be of “value” and “growth” type
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
16 / 27
Introduction
The Model
Empirical Results
Conclusion
Innovation
Inventions, firms, and inventors
Inventions are patents for production of new intermediate
goods
Intellectual property of inventions belongs to inventors (new
firms) and old firms
New firms can be of “value” and “growth” type
Value firms produce and do not invent, responsible for a
fraction of production of new goods
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
16 / 27
Introduction
The Model
Empirical Results
Conclusion
Innovation
Inventions, firms, and inventors
Inventions are patents for production of new intermediate
goods
Intellectual property of inventions belongs to inventors (new
firms) and old firms
New firms can be of “value” and “growth” type
Value firms produce and do not invent, responsible for a
fraction of production of new goods
Growth firms produce and invent, responsible for the rest of
production and a fraction of invention
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
16 / 27
Introduction
The Model
Empirical Results
Conclusion
Innovation
Inventions, firms, and inventors
Inventions are patents for production of new intermediate
goods
Intellectual property of inventions belongs to inventors (new
firms) and old firms
New firms can be of “value” and “growth” type
Value firms produce and do not invent, responsible for a
fraction of production of new goods
Growth firms produce and invent, responsible for the rest of
production and a fraction of invention
Old generations capture a fraction of inventions through
ownership of growth firms
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
16 / 27
Introduction
The Model
Empirical Results
Conclusion
Innovation
Workers
A fraction of new generation are workers
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
17 / 27
Introduction
The Model
Empirical Results
Conclusion
Innovation
Workers
A fraction of new generation are workers
Workers are born with endowment of hours
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
17 / 27
Introduction
The Model
Empirical Results
Conclusion
Innovation
Workers
A fraction of new generation are workers
Workers are born with endowment of hours
Assumption: older workers do not keep up with innovative
technologies as well as the younger workers
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
17 / 27
Introduction
The Model
Empirical Results
Conclusion
Asset Markets
Complete set of state-contingent claims
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
18 / 27
Introduction
The Model
Empirical Results
Conclusion
Asset Markets
Complete set of state-contingent claims
Assets are priced by the standard DCF formula
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
18 / 27
Introduction
The Model
Empirical Results
Conclusion
Equilibrium
Consumers (workers and inventors) chose their consumption
optimally subject to their budget constraints
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
19 / 27
Introduction
The Model
Empirical Results
Conclusion
Equilibrium
Consumers (workers and inventors) chose their consumption
optimally subject to their budget constraints
Firms maximize their profits
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
19 / 27
Introduction
The Model
Empirical Results
Conclusion
Equilibrium
Consumers (workers and inventors) chose their consumption
optimally subject to their budget constraints
Firms maximize their profits
Markets for labor and goods clear
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
19 / 27
Introduction
The Model
Empirical Results
Conclusion
Summary
Innovation = Increased variety of intermediate goods
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
20 / 27
Introduction
The Model
Empirical Results
Conclusion
Summary
Innovation = Increased variety of intermediate goods
Agents
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
20 / 27
Introduction
The Model
Empirical Results
Conclusion
Summary
Innovation = Increased variety of intermediate goods
Agents
Inventors (own patents/firms)
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
20 / 27
Introduction
The Model
Empirical Results
Conclusion
Summary
Innovation = Increased variety of intermediate goods
Agents
Inventors (own patents/firms)
Workers (sell labor)
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
20 / 27
Introduction
The Model
Empirical Results
Conclusion
Summary
Innovation = Increased variety of intermediate goods
Agents
Inventors (own patents/firms)
Workers (sell labor)
Firms
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
20 / 27
Introduction
The Model
Empirical Results
Conclusion
Summary
Innovation = Increased variety of intermediate goods
Agents
Inventors (own patents/firms)
Workers (sell labor)
Firms
Value (production, no innovation)
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
20 / 27
Introduction
The Model
Empirical Results
Conclusion
Summary
Innovation = Increased variety of intermediate goods
Agents
Inventors (own patents/firms)
Workers (sell labor)
Firms
Value (production, no innovation)
Growth (some innovation)
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
20 / 27
Introduction
The Model
Empirical Results
Conclusion
Outline
1
Introduction
2
The Model
3
Empirical Results
4
Conclusion
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
21 / 27
Introduction
The Model
Empirical Results
Conclusion
The Displacement Factor
Theory: can estimate the displacement factor as a change in
relative consumption of a group of households:
log
Garleanu, Kogan, Panageas (2009)
cti +1,s
Ct +1
− log
Innovation and Asset Returns
cti ,s
Ct
October 2009
22 / 27
Introduction
The Model
Empirical Results
Conclusion
The Displacement Factor
Theory: can estimate the displacement factor as a change in
relative consumption of a group of households:
log
cti +1,s
Ct +1
− log
cti ,s
Ct
Use household-level consumption data (CEX, 1984-2003)
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
22 / 27
Introduction
The Model
Empirical Results
Conclusion
The Displacement Factor
Theory: can estimate the displacement factor as a change in
relative consumption of a group of households:
log
cti +1,s
Ct +1
− log
cti ,s
Ct
Use household-level consumption data (CEX, 1984-2003)
Group all cohorts of households that entered the economy
before date s
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
22 / 27
Introduction
The Model
Empirical Results
Conclusion
The Displacement Factor
Cohorts pre−1980
Cohorts pre−1965
−.1
(log) Displacement factor
−.05
0
.05
Cohorts pre−1975
Cohorts pre−1970
1985
Garleanu, Kogan, Panageas (2009)
1990
1995
Year
Innovation and Asset Returns
2000
2005
October 2009
23 / 27
Introduction
The Model
Empirical Results
Conclusion
HML return (right axis)
Correlation: .27
Correlation: −.01
.4
.2
.03
.4
0
.02
−.2
.01
1985
1990
1995
Year
Garleanu, Kogan, Panageas (2009)
2000
2005
−.4
−.4
−.1
0
−.2
−.05
0
0
.2
.04
Diff. aggr. log(consum.) (left axis)
HML return (right axis)
.05
(log) Displacement factor (left axis)
1985
Innovation and Asset Returns
1990
1995
Year
2000
2005
October 2009
24 / 27
Introduction
The Model
Empirical Results
Conclusion
Consumption Cohort Effects
Time-series dimension of CEX is limited
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
24 / 27
Introduction
The Model
Empirical Results
Conclusion
Consumption Cohort Effects
Time-series dimension of CEX is limited
Use theory to exploit the cross-section of consumption
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
24 / 27
Introduction
The Model
Empirical Results
Conclusion
Consumption Cohort Effects
Time-series dimension of CEX is limited
Use theory to exploit the cross-section of consumption
Our model implies existence of consumption cohort effects
log ct ,s = as + bt
t - calendar time
s - cohort
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
24 / 27
Introduction
The Model
Empirical Results
Conclusion
Consumption Cohort Effects
Time-series dimension of CEX is limited
Use theory to exploit the cross-section of consumption
Our model implies existence of consumption cohort effects
log ct ,s = as + bt
t - calendar time
s - cohort
Displacement shocks are the permanent component of
consumption cohort effects as
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
24 / 27
Introduction
The Model
Empirical Results
Conclusion
Consumption Cohorts
−.5
−.05
−1
−.1
−.15
−.1
−.05
0
0
0
.05
.05
.5
.1
Detrended cohorts (left axis)
Detrended cumulative HML return (right axis)
1920
1940
1960
1980
2000
1920
Year
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
25 / 27
Introduction
The Model
Empirical Results
Conclusion
Value Premium
Long-short B/M portfolios: Decile i − Decile 10: 1927-2007
0.01
0.005
Average (log) Return
0
−0.005
−0.01
−0.015
−0.02
−0.025
−0.03
−0.035
1
2
3
4
5
6
7
8
9
Decile
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
26 / 27
Introduction
The Model
Empirical Results
Conclusion
Innovation Betas and Book-to-Market
Long-short B/M portfolios: Decile i − Decile 10: 1927-1995
7.5
7
Consumption Cohort β
6.5
6
5.5
5
4.5
4
3.5
3
2.5
1
2
3
4
5
6
7
8
9
Decile
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
27 / 27
Introduction
The Model
Empirical Results
Conclusion
Alternative Measures of Innovation
We extract innovation shocks from consumption cohort effects
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
28 / 27
Introduction
The Model
Empirical Results
Conclusion
Alternative Measures of Innovation
We extract innovation shocks from consumption cohort effects
Can one identify other, more direct proxies for innovation?
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
28 / 27
Introduction
The Model
Empirical Results
Conclusion
Alternative Measures of Innovation
We extract innovation shocks from consumption cohort effects
Can one identify other, more direct proxies for innovation?
Motivated by the model: changes in the stock of trademarks
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
28 / 27
Introduction
The Model
Empirical Results
Conclusion
Alternative Measures of Innovation
We extract innovation shocks from consumption cohort effects
Can one identify other, more direct proxies for innovation?
Motivated by the model: changes in the stock of trademarks
Relate average returns on the book-to-market decile portfolios
to innovation betas
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
28 / 27
Introduction
The Model
Empirical Results
Conclusion
Innovation Betas and Book-to-Market
8
2
6
1
4
0
Trademark β
Consumption Cohort β
Long-short B/M portfolios: Decile i − Decile 10: 1927-2000
2
1
2
3
4
5
6
7
8
−1
9
Decile
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
29 / 27
Introduction
The Model
Empirical Results
Conclusion
Outline
1
Introduction
2
The Model
3
Empirical Results
4
Conclusion
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
30 / 27
Introduction
The Model
Empirical Results
Conclusion
Conclusion
Displacement risk is a fundamental risk factor
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
31 / 27
Introduction
The Model
Empirical Results
Conclusion
Conclusion
Displacement risk is a fundamental risk factor
Empirical evidence for displacement risk
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
31 / 27
Introduction
The Model
Empirical Results
Conclusion
Conclusion
Displacement risk is a fundamental risk factor
Empirical evidence for displacement risk
Calibration (not shown) is quantitatively realistic
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
31 / 27
Introduction
The Model
Empirical Results
Conclusion
Conclusion
Displacement risk is a fundamental risk factor
Empirical evidence for displacement risk
Calibration (not shown) is quantitatively realistic
Better understanding of the value-growth factor, value
premium, equity premium
Garleanu, Kogan, Panageas (2009)
Innovation and Asset Returns
October 2009
31 / 27