Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Monetary policy and asset valuation
Rafael B. De Rezende
Jönköping International Business School, Jönköping University
Amuletum Invest AB
November 2023
Advanced Topics in Finance (JATR29 2023)
Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Content
1
Monetary policy and asset valuation
2
Listed literature
Sources: listed papers
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Monetary policy and asset valuation
In theory, contractionary monetary policy should have (mostly negative)
effects on asset returns
Effects, however, can be heterogeneous, and vary according to various
factors, including certain firms’ characteristics
Therefore, I will go through papers on that
One important aspect for measuring the effects, however, is the
identification of monetary policy shocks. Papers that use high frequency
identification using financial instruments are emphasized. In this context,
and in the presence of unconventional monetary policies, shadow rates
have become a prominent avenue for monetary policy measurement
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Monetary policy and asset valuation
Therefore, I review four papers on that
On shadow rates:
1
De Rezende and Ristiniemi (2023)
On the channels through which monetary policy affect stock prices across
firms in a heterogenous manner:
1
2
3
Thorbecke (1997)
Ehrmann and Fratzscher (2004)
Gürkaynak, Karasoy-Can and Seok Lee (2022)
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
What they do...
The paper proposes a shadow rate without a lower bound constraint that
measures the overall stance of monetary policy in any monetary policy
(ELB) environment, prior, during and after a lower-bound period
The insight of the paper is that since the GFC of 2007-2008, central
banks have continued to use unconventional monetary policies as
instruments to affect longer-term interest rates
1
2
3
In addition to the policy rate iself, central banks have used
Balance sheet policy:
Forward guidance on future policy rate and balance sheet
This has happened no matter whether the policy rate has been or hasn’t
been at the lower bound. Examples:
1
2
January 2016 to February 2020: the lift-off period in the US
Recent inflationary period: policy rates raised in several economies, while
balance sheets continued relatively large, and forward guidance has been
provided
On top of that, there is also uncertainty about where the ELB is (see De
Rezende 2017 for Swedish case)
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
What they do...
As a result, the typical shadow rates that respect ELB constraints, i.e. ,
fail to account for the various monetary policy instruments that can be
used for easing/tightening monetary conditions
And this is because of their shadow rate specification that respects the
lower-bound, by definition:
1
SRTSMs: Krippner (2013), Christensen and Rudebusch (2015), Wu and
Xia (2016), Bauer and Rudebusch (2016), Kortela (2016), Lemke and
Vladu (2016), Wu and Xia (2019), Andreasen and Meldrum (2019)
rt = max rt , st
rt = max (r , st ) st = δ0 + δ1′ Xt
st = δ0 + δ1′ Xt
2
Dyn. factor model with missing observations: Lombardi and Zhu (2018)
By definition, the specifications above imply that st = rt when the lower
bound is not binding.
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
What they do...
Because it does not impose any ELB constraint, De Rezende and
Ristiniemi (2023) shadow rate has important implications
Main implications
1
2
3
4
5
Allows for st ̸= rt when the ELB is not binding, e.g. when the central
bank exits the ELB
Handles the interest rate effects of unconventional policies in any
“unconventional” environment
Handles different cases of lower bound constraint in the data (fixed,
time-varying and no lower bound constraints)
Not sensitive to the choice of the lower bound (Bauer and Rudebusch
2016)
One can estimate shadow rates for any economy that has relied on
unconventional measures (e.g. US, EA, UK, SE)
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De Rezende and Ristiniemi (2023) specification
△st =



△rt
δ11 △Xtsr if


δ12 △Xt if
if t < t0
t ≥ t0 s.t. t ̸= t ⋆
t ≥ t0 s.t. t = t ⋆
X sr = W sr Y sr s.t. W sr = U sr W
The specification and coupled to an DATSM to estimate term premium
Term premium is removed from st on non-announcement days
1
2
3
4
carries information that is not particularly related to the stance of
monetary policy
investors’ fears and uncertainties about the future state of the economy
(Wright 2011)
degree of investors’ risk aversion, which varies due to a number of factors
including business cycles (Wachter 2006)
“flight to quality” effects at times of extreme volatility in financial markets
(Kim and Orphanides 2007)
On announcement days, both short-rate expectations and term premium
respond to unconventional policies
1
Signaling, portfolio balance, reserve induced portfolio balance and
collateral channels
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
De Rezende and Ristiniemi (2023) specification
Shadow rate in levels
st = r1 +
tX
0 −1
t=2
△rt +
T ,X
t̸=t ⋆
δ11 △ Xtsr +
T ,X
t=t ⋆
t=t0
δ12 △ Xt
t=t0
′
st is well specified, given that r1 = δ0 + δ1 X1
For comparison with other specifications, we set t0 to be equal to
the day in which the central bank first announced unconventional
policies after the financial crisis of 2007/2008
PT
t=t0 (st − rt ) may indicate how expansionary unconventional
monetary policy has been compared to conventional monetary
policy from t0 to T
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Estimation
1. Estimate event study regressions (as Kuttner 2001) using data observed
during the conventional policy period
△Xt ⋄ = α△rtu⋄ + ϵt ⋄
△Xtsr⋄ = β△rtu⋄ + εt ⋄
2. Translate movements in △Xtsr and △Xt during the unconventional policy
period into policy rate equivalent numbers using inverse prediction,
du = 1 △X sr ,
△r
t
t
b
β
du = 1 △Xt ,
△r
t
dt =
△s





α
b
1
sr
b △Xt
β
1
△Xt
α
b
if
t ≥ t0 s.t. t ̸= t ⋆
if
t ≥ t0 s.t. t = t ⋆
△rt
if
if t < t0
t ≥ t0 s.t. t ̸= t ⋆
if
t ≥ t0 s.t. t = t ⋆
dt = △r
du = △r u + 1 ϵbt ,
△s
t
t
α
b
if
t ≥ t0 s.t. t = t ⋆
dt over the whole sample
3. st is obtained by accumulating ∆s
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Shadow rate estimates
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Shadow rate estimates
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Exchange rate effects of CMP and UMP surprises
The paper also investigates the pass-through of conventional vs
unconventional monetary policies to exchange rates
To do so, they propose a decomposition of shadow rate changes into
measures of conventional and unconventional monetary policy surprises
1
u
[
\u⋆
△s
ϵbt = △rtu⋆ + △ump
t ⋆ = △rt ⋆ +
t
α
b
Which can be used to assess the effects of both policies on exchange rates
△et ⋆ = η + γ△rtu⋆,d + ϑ△umptu⋆,d + ω △ st ⋆,f + ϵt ⋆
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Exchange rate effects of CMP and UMP surprises
Federal Reserve
Riksbank
USD/SEK
USD/EUR
USD/GBP
SEK/USD
SEK/EUR
SEK/GBP
const.
0.060
0.044
0.158
−0.045
−0.033
−0.089⋆⋆
(0.100)
(0.081)
(0.125)
(0.055)
(0.051)
(0.058)
△rtu⋆,d
−0.122⋆⋆⋆
−0.092⋆⋆⋆
−0.088⋆⋆⋆
−0.103⋆⋆⋆
−0.098⋆⋆⋆
−0.100⋆⋆⋆
(0.036)
−0.043⋆⋆⋆
(0.022)
−0.027⋆⋆⋆
(0.026)
−0.019⋆⋆⋆
(0.016)
−0.038⋆⋆⋆
(0.015)
−0.034⋆⋆⋆
−0.043⋆⋆⋆
(0.007)
(0.007)
(0.005)
(0.010)
(0.009)
(0.012)
△umptu⋆,d
△st ⋆,f
R2
(0.015)
0.029
0.040
0.029
0.006
0.016
0.016
(0.021)
(0.031)
(0.019)
(0.008)
(0.024)
(0.010)
0.67
0.63
0.28
0.76
0.77
0.71
ECB
EUR/USD
EUR/SEK
Bank of England
EUR/GBP
GBP/USD
GBP/SEK
GBP/EUR
const.
0.175
0.115
0.193
0.145
0.035
0.075
△rtu⋆,d
(0.140)
−0.146⋆⋆⋆
(0.086)
−0.085⋆⋆⋆
(0.118)
−0.117⋆⋆⋆
(0.093)
−0.198⋆⋆⋆
(0.118)
−0.199⋆⋆⋆
−0.116⋆⋆
(0.041)
(0.021)
(0.029)
(0.065)
(0.069)
(0.044)
△umptu⋆,d
−0.105⋆⋆⋆
−0.063⋆⋆⋆
−0.078⋆⋆⋆
−0.038⋆⋆⋆
−0.052⋆⋆⋆
−0.052⋆⋆⋆
(0.029)
(0.027)
(0.028)
(0.009)
(0.012)
(0.007)
△st ⋆,f
R2
(0.087)
0.002
0.022
0.015
−0.006
−0.005
0.048⋆⋆
(0.022)
(0.034)
(0.027)
(0.011)
(0.020)
(0.022)
0.53
0.39
0.56
0.65
0.61
0.66
Pooled event study regression: γ =
−0.097⋆⋆⋆ ,
ϑ = −0.031⋆⋆⋆
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Counterfactual exercise with DSGE models
The paper also constructs counterfactual analyses for inflation,
unemployment and output growth for the US and Sweden by replacing
the policy rates with estimated shadow rates
Two medium-scale DSGE models with their estimated impulse responses
are used: Smets and Wouters (2007) for US and Riksbank’s Ramses II
(Adolfson et al. 2013) for Sweden
US: Inflation would have been around 0.7 percentage points lower than
otherwise over 2009–2021 and output growth 5.5 percentage points lower
Similar exercise is also performed using Wu and Xia (2016) and
Krippner (2014) shadow rates
Sweden: CPIF inflation would have been around 0.33 percentage points
lower than otherwise over 2009–2021 and unemployment rate about 0.59
higher
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Results for the US
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Results for the US
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
What they do...
The paper examines whether monetary policy has real effects on the
economy, through stock market returns
To analyze this, a number of empirical techniques are employed
1
2
3
4
impulse response fundtions and variance decompositions from a VAR
GMM estimates
Event study analysis
Nonlinear Seemingly unrelated regressions (SUR) estimation of a
multifactor model
All point to the fact that monetary policy affect stock market returns
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
VAR evidence - model
Model description
The VAR structure with endogenous variables y
Can be inverted an written as VMA process
Cholesky factorization
Endogenous can be written as functions of othogonalized innovations
Based on the above, one can obtain impulse responses of variables to
innovations in each y, as well as the percentage of each variable’s forecast
error that is attributable to these innovations
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
VAR evidence - data
Monthly data over 1959:7 - 1989:12 for the following endogenous
variables is used
1
2
3
4
5
6
7
8
9
growth rate of industrial production
inflation rate
log of commodity price index
federal funds rate
log of nonborrowed reserves as part of the reserve requirements of banks
with the Fed (replace the fed funds rate above over the sample Oct 79 to
Aug 82)
log of total reserves
stock returns
a constant
six lags are used
Stock return data are for 22 industries as in Boudoukh et al. (1994) and
10 size portfolios, which are value-weighted and sorted into deciles based
on market cap. This is useful to verify whether monetary policy has real
effect through a credit (balance sheet) channel, as the decline in net
worth can reduce the ability of firms to borrow
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VAR evidence - data
Results from the 1st observation of impulse responses show that effects
are significant, and in size portfolios, are larger for smaller firms
Stock return data are for 22 industries as in Boudoukh et al. (1994) and
10 size portfolios, which are value-weighted and sorted into deciles based
on market cap. This is useful to verify whether monetary policy has real
effect through a credit (balance sheet) channel, as the decline in net
worth can reduce the ability of firms to borrow
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VAR evidence - results 1
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VAR evidence - results 2
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VAR evidence - results 3
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VAR evidence - results 4
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Narrative approach evidence
Boschen and Mills (1995) follow the narrative approach introduced by
Friedman and Schwartz (1963) to construct an index of monetary policy
shocks based on FOMC statements obtained from historical documents
over the period 1953:1 - 1991-12
They construct an index that classifies monetary policy into five
cathegories: strongly anti-inflationary (-2), anti-inflationary (-1), neutral
(0), pro-growth (1), strongly pro-growth (2)
They also add the variables of Chen, Roll and Ross (1986) to the
regression
One std. deviation increase in the index increase stock returns by an
average of 10%
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Narrative approach - results
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Event study evidence
The authors look at daily responses of the returns of Dow Jones Industrial
Average (DJIA) and Dow Jones Composite Average (DJCA) to federal
funds rate changes
The dates included are days in which references to changes in the fed
funds rate appear in newspapers. A keyword search of major newspapers
over August 11 1987 and December 31 1994 is performed
Results below indicate that effects are statistically significant
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Event study - results
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
What they do...
The paper examines the effects of US monetary policy on stock prices,
through cash-flows
Their argument is that there is that the response of equity prices of
companies is heterogeneous, due to two factors:
1
2
the credit channel of monetary policy transmission: (i) tighter monetary
policy may have stronger impacts on firms that are highly bank-dependent
borrower, as credit shrinks; (ii) worsening credit market conditions affect
firms also by weakening their balance sheets as the present value of
collateral falls with rising interest rates, which also shrinks their access to
credit
the interest rate channel of monetary policy transmission: firms that
produce goods for which demand is highly cyclical or interest-sensitive
experience a higher contraction of CFs. Responses differ due to
firm-specific characteristics, but also due to the industry the firm pertain
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
What they do...
In summary, they find that
1
2
3
reactions of individual firms in the SP500 to monetary policy shocks is
highly heterogeneous
there are industry-specific effects. Cyclical sectors, such as technology,
communications, and cyclical consumer goods, react two to three times
stronger to monetary policy than less cyclical sectors
stronger effect on the equity returns of firms that are financially
constrained and/or have good investment opportunities. Firms with low
cash flows, poor credit ratings, low debt to capital ratios, high
price-earnings ratios, or a high Tobin’s q are affected significantly more
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Data
Monetary policy shocks are identified using high-frequency identification:
the unexpected component of changes in the fed-funds rate
1
2
3
Monetary policy expectations are measured using the Reuters poll among
market participants, conducted on Fridays before each FOMC meeting
As alternative measure they use the surprise component of changes in fed
funds future (1st contract, or ff1)
The sample covers 79 FOMC meetings from Feb 1994 to Jan 2003
Stock market returns are measured using daily log-returns of closing
prices for the S&P500 index, and the 500 individual stocks there in
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Econometric model
The paper uses the following regression models
1
rt = α + βst + εt
2
ri,t = α + β1 st + β2 st xi,t + τ xi,t + εi,t
where 2 is estimated using OLS using panel-corrected standard errors,
which corrects for dependence across observations
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Results - industry effects
Tables 1 and 2 in the next slides report results for a breakdown of nine sectors
and 60 industry groups
The second panels of Tables 1 and 2 report the corresponding results for β2 ,
which control for market movements, and aim to estimate how sensitive stock
returns of a given industry are to monetary policy relative to the market return
Stock returns of firms in the technology, communication and cyclical consumer
goods industries are more responsive than the average stock, whereas
non-cyclical consumer goods, energy, and utilities respond below average
Industries whose reaction to monetary policy shocks is around the average are
the basic materials, industrial, and financial sectors
Overall, this supports the hypothesis that cyclical and capital-intensive industries
are affected most. From Table 2, we see that highly non-cyclical sectors like
food, agriculture, or beverages respond less, whereas firms in semiconductors,
internet, telecommunications, computers, and software, react more strongly
than the average
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Results - industry effects
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Results - industry effects
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Results - firm-specific effects
The authors also analyze the role of the credit channel
The idea is that firms that are financially constrained are likely to be affected
more strongly by changes in interest rates than firms that are less constrained
In Table 5 below they first use the size of firms (number of employees and
market value) as a proxy for the degree of credit constraint
The authors also use several more direct measures of financial constraints: the
cash flow to income ratio and the ratio of debt to total capital. In theory, firms
with large cash flows should be more immune to changes in interest rates as
they can rely more on internal financing for investment. One may also expect
that firms with a lower ratio of debt to capital are affected more by monetary
policy because they are more bank-dependent
They also include the price-earnings ratio and employ Moody’s investment
rating and Moody’s bank loan rating as two measures of financial constraints.
One would expect that firms with a better rating should find it easier to obtain
financing of their investments and therefore should be less affected by changes
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in monetary policy
Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Results - firm-specific effects
Looking at vanous measures of financial constraints, the paper finds that
firms that are financially constrained respond significantly more to
monetary policy than less constrained ones
A somewhat unexpected finding is that the largest effect of monetary
policy is expenenced by firms with a low level of debt, whereas firms with
high levels of debt react similar to the average firm. Authors intelpret this
result as indicating that firms that have a high level of debt are not more
constrained financially than others, but instead that firms hold low levels
of debt because they are currently financially constrained and thus may
not be able to borrow more
Firms with a high Tobin’s q are affected more, as these firms may
experience higher financial constraints to finance investments
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Results - firm-specific effects
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Results - firm-specific effects
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
What they do...
They recognize that due to the heterogeneity of firms (in various dimensions),
the interaction of monetary policy and stock prices is not well understood yet
They study the effects of monetary policy on stock prices due to liability
difference caused by fixed versus floating rate obligations of otherwise similar
firms. In that sense, the maturity structure of debt matters for the cashflow
exposure of firms when monetary policy contracts, with firms with more and
longer maturing debt being more exposed.
They find that firms that have more cash flow exposure due to more and longer
maturity floating rate debt see a larger stock price reaction to monetary policy
(forward guidance) surprises, which affect the path of monetary policy and,
therefore, longer-maturity debt. These results are independent of the lower
bound environment
They argue that these effects happen because the marginal stock market
investor is quite sophisticated and understands the debt structure of firms and
the implications of monetary policy
These results go against the Modigliani-Miller theorem, which states that a
company’s capital structure is not a factor in its value
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Data
Monetary policy data:
1
2
3
High frequency identification of monetary policy shocks
Target surprises measured from changes in Fed funds futures rates (ff1
contract) with a 30-minute window around monetary policy
announcements
Path surprises measured from changes in Eurodollar futures rates (ED1,
ED2, ED3, ED4) with a 30-minute window around monetary policy
announcements
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Data
Firm level data:
1
2
3
4
5
Sample comprises firms that were part of the S&P500 at any point
between 1957 (creation of the index) and 2018 (end of our sample) whose
balance sheet data are also available in the Capital IQ (CIQ) database.
This gives 975 firms.
Stock returns are measured using daily percentage changes
They measure debt exposure as
where i indexes firms, j debt items, FRDA and FRDM denote the amount
and maturity of floating rate debt, and TA denotes total assets
Balance sheet items are size, profitability, book leverage, market-to-book
ratio, asset maturity etc. Other variables are financial slack, retained
earnings, dividends per share, short-term debt
They also use another explanatory variable: “hedge interest rate”
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Data
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Method
The model they estimate using OLS is the following
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Cashflow channel of monetary policy - preZLB
When the exposure measure is used and allow for both target and path
surprises as well as leverage and exposure, the relevant variable turns out
to be exposure’s interaction with path
Hedging against interest rate risk reduces the impact of the cash flow
exposure on firm’ stock prices
The R2 more than doubles as we move from target and leverage to path
and exposure, which highlights the importance of the additional
information on maturity embedded in the exposure measure for
understanding stock price reactions to monetary policy.
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Cashflow channel of monetary policy - preZLB
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Cashflow channel of monetary policy - preZLB
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Cashflow channel of monetary policy - ZLB
The floating rate channel remained intact during the ZLB
They test for a change in the relationship at the ZLB by including a
binary variable for this period (January 2009 to December 2015) and
interacting it with the cash flow channel variables
None of the interactions are statistically significant, showing that the
binding constraint on immediate policy actions (target) did not materially
affect the cash flow channel, which depends on the interaction of path
and cash flow exposure
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Cashflow channel of monetary policy - ZLB
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Cashflow channel of monetary policy - ZLB
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Stock market sophistication
Three tests of stock market participant’s sophistication
1 If a firm is an IPO, investors should not form rules of thumb about
effects of monetary policy certain firms and not on the structure of
the balance sheet. Results confirm that.
2 Dummy large changes should also be irrelevant if investors follow
(attentive investors) the balance sheet structure
3 If investors form rules of thumb, then past performance should be
irrelevant
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Stock market sophistication
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Stock market sophistication
Panel regression results
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Balance sheet regressions
Balance sheet regression model to analyze how firms adjust their balance
sheets following a contractionary monetary shock. They find strong
evidence of adjustments in several variables (capital investments, net
worth, total assets, total liabilities, inventory investment, cash holdings)
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Balance sheet regressions
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Balance sheet regressions
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
Balance sheet regressions
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Content MP & asset val. De Rezende and Ristiniemi (2023) Thorbecke (1997) Ehrmann and Fratzscher (2004) Gürkaynak, Kara
END OF TODAY’S LECTURE. THANK YOU!
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