Introduction Data Evidence Interpretation DSGE Model Conclusion Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 1 Thiago Ferreira * * Federal Reserve Board Ninth BIS CCA Research Conference Rio de Janeiro June 2018 1 Previously presented as “Cross-Section Skewness, Business Cycle Fluctuations and the Financial Accelerator Channel”. The views expressed in this paper are solely my responsibility and should not be interpreted as reflecting the views of the Board of Governors of the Federal Reserve System or of any other person associated with the Federal Reserve System.” Thiago Ferreira * * Federal Reserve Board Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 1
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Stock Market Cross-Sectional Skewness · 2)Financial skewness seem to signal future economic performance of nancial rms’ borrowers 3)Financial skewness shocks are important cyclical
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Introduction Data Evidence Interpretation DSGE Model Conclusion
Stock Market Cross-Sectional Skewnessand Business Cycle Fluctuations1
Thiago Ferreira∗∗Federal Reserve Board
Ninth BIS CCA Research Conference
Rio de Janeiro
June 2018
1 Previously presented as “Cross-Section Skewness, Business Cycle Fluctuations and the Financial AcceleratorChannel”. The views expressed in this paper are solely my responsibility and should not be interpreted as reflectingthe views of the Board of Governors of the Federal Reserve System or of any other person associated with theFederal Reserve System.”
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 1
Introduction Data Evidence Interpretation DSGE Model Conclusion
Business Cycles: Prediction and Explanation
Fluctuations in economic uncertainty and business cycles
I focus on 2nd moments and aggregate (negative) tail risks
I want to shift the discussion to skewness. Too nerdy?
I captures the comparison of tail risks: upside X downside
I often used in FOMC and ECB comunications
More specifically, can cross-section skewness of asset prices help uspredict and understand business cycle fluctuations?
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 2
Introduction Data Evidence Interpretation DSGE Model Conclusion
Cross-Sectional Distribution of Stock Returns of Financial Firms
Log returns (percent)-60 -40 -20 0 20 40 60
0
2
4
6
8
10
2006:Q22008:Q4
Downside Risks Upside Risks( ) ( )
(a) Probability Density Function
2006:Q2 2008Q4Median 0% 0%Skewness 0% -27%
(b) Cross-Sectional Moments
financial skewnesst =(ln r95th
t − ln r50tht
)︸ ︷︷ ︸upside tail risks
−(ln r50th
t − ln r5tht
).︸ ︷︷ ︸
downside tail risks
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 3
Introduction Data Evidence Interpretation DSGE Model Conclusion
Financial Skewness Tracks Business Cycles
-23
-14
-5
4
13
Q1-1927
Q2-1933
Q4-1939
Q1-1946
Q2-1952
Q3-1958
Q4-1964
Q2-1971
Q3-1977
Q4-1983
Q1-1990
Q3-1996
Q4-2002
Q1-2009
Q2-2015-4
0
4
9
13Percent Percent
GDP Growth(Right)
FinancialSkewness(Left)
Financial vs Nonfinancial
Correlations
Logit
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 4
Introduction Data Evidence Interpretation DSGE Model Conclusion
3 main results:
1) Financial skewness is a powerful predictor of economic activityI better than many well-known indicators
2) Financial skewness seem to signal future economicperformance of financial firms’ borrowers
3) Financial skewness shocks are important cyclical drivers, withtransmission channel consistent with financial frictions models
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 5
Introduction Data Evidence Interpretation DSGE Model Conclusion
Literature Review X Results
Business cycles drivers: cross-sectional skewness is important.I Idiosyncratic firms’ behavior is important driver of BC. Focus on 2nd moments:
Bloom et al (2012), Arellano et al (2012), Christiano et al (2014), Chugh (2016), Schaal (2015), Panousi
and Papanikolaou (2012), Gabaix (2011); Acemoglu et al (2011).
I Tail risks are important for BC. Most focus on aggregate downside risks:Barro (2006), Gabaix (2012), and Gorio (2012).
Asset prices predict business cycles: financial skewness does particularly well.I Despite importance in BC theory, CS risk is not important in forecasting:
Lit reviews: Stock and Watson (2003) and Ng and Wright (2013).
I Bond markets may signal better than stocks about economic fundamentals:Philippon (2009), Gilchrist and Zakrajsek (2012), and Lopez-Salido et al. (2017).
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 6
Introduction Data Evidence Interpretation DSGE Model Conclusion
Data Evidence
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 7
Introduction Data Evidence Interpretation DSGE Model Conclusion
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 18
Introduction Data Evidence Interpretation DSGE Model Conclusion
What explain financial skewness? Part II
-25
-20
-15
-10
-5
0
5
10
Q1-1989
Q1-1992
Q4-1994
Q4-1997
Q4-2000
Q3-2003
Q3-2006
Q3-2009
Q2-2012
Q2-2015
Financial Skewness
Fitted Values
Percent
(h) Fitted Values from Return on Assets and Lending Standards
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 19
Introduction Data Evidence Interpretation DSGE Model Conclusion
Structural Analysis:
DSGE Model and BVARs
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 20
Introduction Data Evidence Interpretation DSGE Model Conclusion
3nd: Structural Analysis - BVAR and DSGE Models
14 variables: macro, financial and stock market cross-sectional moments.
In both BVAR and DSGE model, financial skewness shocks:
• have a transmission channel consistent with financial frictions models
• are important business cycle drivers and have sizable economic effects
• account for most of the fluctuations in financial skewness
• drive out other shocks, including dispersion ones
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 21
Introduction Data Evidence Interpretation DSGE Model Conclusion
NK-DSGE with financial accelerator channelSimilar to Christiano et al (2014) in its bells and whistles
Why this model?
cross-section shocks generates business cyclesendogenous cross-section distributioncompare widely used DSGE model against BVAR
Re-interpretation of the model:
Households Loan Contracts
Bank +
Entrepreneur
Bank+Entrepreneur
Cross-section risk⇒{
nonfin CS risk after some diversification (e.g, dotcom)
fin CS risk (e.g, Lehman)
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 22
Introduction Data Evidence Interpretation DSGE Model Conclusion
Distribution of Returns and the Financial Accelerator
Define gross realized equity return of entrepreneur i at period t:
X it =
ωit Rc
t Qt−1Kit−Z i
t B it
N it
, if ωit Rc
t Qt−1Kit ≥ Z i
t B it
0, otherwise=
{ [ωi
t − ωt]
Rct Lt , if ωi
t ≥ ωt
0, otherwise.
I endogenous distribution of X it : ωt , Rc
t and Lt are endogenous variables
I ωit follows a mixture of two log-normal distributions
I E(ωit) = 1, Std(ωi
t) = sdt and m1t proxies skewness
For instance, cross-section skewness of the model is: (x̃95t − x̃50
t )− (x̃50t − x̃5
t ),
where x̃vt = log(ω̃v
t − ωt) and ω̃vt is the v th percentile of cdf Ft(·|ωt > ωt).
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 23
Introduction Data Evidence Interpretation DSGE Model Conclusion
NK-DSGE with financial accelerator channel: 1964-20151st Step: 1964-2006, Taylor Rule;2nd Step: 2002-2015, Taylor Rule with news; re-estimate shocks autocorr and std;
Observable variables Shocks
GDP permanent TFP-growth
Consumption inter-temporal discount
Investment capital adjustment cost (IS-shock)
Hours worked transitory TFP
Real wage price-markup
Fed Funds rate monetary policy
OIS 1Y-ahead (2002-2015) news on monetary policy
PCE core inflation inflation trend/target
Relative price of Investment investment price
Real credit government/NX residual
Equity (Meannfint ) equity and meas-error
Baa - US 10y
Dispnfint and Skewfin
t sdt and m1t
news about them up to 4Q in advance
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 24
Introduction Data Evidence Interpretation DSGE Model Conclusion
Primacy of Skewness Shocks: Hist + Var Decomp’sP
erce
ntag
e
-8
-6
-4
-2
0
2
4
6
Q1-1964
Q4-1969
Q3-1975
Q1-1981
Q4-1986
Q3-1992
Q2-1998
Q1-2004
Q3-2009
Q2-2015
DataAnticipated and Unanticipated Skewness Shocks
(i) GDP (7 | 41 %)
Per
cent
age
-25
-20
-15
-10
-5
0
5
10
15
Q1-1964
Q4-1969
Q3-1975
Q1-1981
Q4-1986
Q3-1992
Q2-1998
Q1-2004
Q3-2009
Q2-2015
DataAnticipated and Unanticipated Skewness Shocks
(j) Investment (9 | 51%)
Per
cent
age
-10
-8
-6
-4
-2
0
2
4
6
8
Q1-1964
Q4-1969
Q3-1975
Q1-1981
Q4-1986
Q3-1992
Q2-1998
Q1-2004
Q3-2009
Q2-2015
DataAnticipated and Unanticipated Skewness Shocks
(k) Credit (6 | 35%)
Per
cent
age
-2
-1
0
1
2
3
4
Q1-1964
Q4-1969
Q3-1975
Q1-1981
Q4-1986
Q3-1992
Q2-1998
Q1-2004
Q3-2009
Q2-2015
DataAnticipated and Unanticipated Skewness Shocks
(l) Baa spread (16 | 50%)
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 25
Introduction Data Evidence Interpretation DSGE Model Conclusion
Skewness shocks:• FEVD: GDP = 5-20%
• IRF: GDP falls 0.3-0.75%
• FEVD: majority of FinSkew
Fin-friction transmission:• IRFs: general picture
• ↑ Baa-10y ⇒ Larger IRFs
• DSGE IRFs ≈ BVAR IRFs
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 26
Introduction Data Evidence Interpretation DSGE Model Conclusion
Dispersion shocks:• FEVD of GDP = 0-3%
• IRF ≈ 0
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 27
Introduction Data Evidence Interpretation DSGE Model Conclusion
Conclusion:
I Financial skewness is a powerful predictor of economic activity
I Financial skewness seem to signal future economicperformance of financial firms’ borrowers
I Financial skewness shocks are important cyclical drivers
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 28
Introduction Data Evidence Interpretation DSGE Model Conclusion
Cross-Section Skewness: Financial X Nonfinancial Back
Per
cent
age
-23
-14
-5
4
13
Q1-1927
Q4-1931
Q2-1936
Q1-1941
Q3-1945
Q2-1950
Q1-1955
Q3-1959
Q2-1964
Q4-1968
Q3-1973
Q2-1978
Q4-1982
Q3-1987
Q1-1992
Q4-1996
Q2-2001
Q1-2006
Q4-2010
Q2-2015
Per
cent
age
-4
0
4
9
13Skewfin
t 4Q-ave (left axis)
GDP 4Q-growth (right axis)
Per
cent
age
-22
-11
-0
10
21
Q1-1927
Q4-1931
Q2-1936
Q1-1941
Q3-1945
Q2-1950
Q1-1955
Q3-1959
Q2-1964
Q4-1968
Q3-1973
Q2-1978
Q4-1982
Q3-1987
Q1-1992
Q4-1996
Q2-2001
Q1-2006
Q4-2010
Q2-2015
Per
cent
age
-4
0
4
9
13
Skewnfint 4Q-ave(left axis)
GDP 4Q-growth (right axis)
Thiago Ferreira∗ ∗Federal Reserve Board
Stock Market Cross-Sectional Skewness and Business Cycle Fluctuations 29
Introduction Data Evidence Interpretation DSGE Model Conclusion