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Does The Federal Reserve
Affect Asset Prices?
Vefa Tarhan
Working Papers Series
Issues in Macroeconomics
Research Department
Federal Reserve Bank of Chicago
January 1992 (WP-92-3)
FEDERAL RESERVE BANK
OF CHICAGO
DOES THE FEDERAL RESERVE AFFECT ASSET PRICES?
by
Vefa Tarhan
Loyola University of Chicago
Department of Finance
June 1991
First Revision:
Second Revision:
May 1990
October 1990
I would like to thank Tim Bollerslev, Ravi Jagannathan, David
Marshall, Paul A. Spindt, and Steven Strongin.
The usual caveat
about any error in the paper applies.
Eric Klusman provided
excellent research assistance. Financial support from the Federal
Reserve Bank of Chicago is gratefully acknowledged.
ABSTRACT
The Federal Reserve is probably one of the institutions most
closely monitored by investors.
This indicates that investors
believe the actions of the Fed have implications for asset prices.
However, studies detect no empirical relation between money growth
and interest rates.
To this date, the trading activities of the
Fed in the financial markets have not been examined to see whether
the Fed has the ability to influence asset prices.
Using daily
data on Open Market Operations (OMOs) and asset prices, this study
fills this void.
One finding of the paper is that OMOs Grangercause both short and long term interest rates. Judging by the
impulse response paths, the effects of monetary policy appear to be
confined to the short run.
Furthermore,
the sign of the
relationship confirms the existence of the much hypothesized
liquidity effect.
Additionally, daily OMOs appear to have some
impact on exchange rates, but not on stock prices. This paper also
investigates the impact of monetary policy on asset return
volatility.
The evidence indicates that OMOs have a dampening
effect on volatility in some of the financial markets examined.
1
1. INTRODUCTION
This paper investigates the empirical link between Open Market
Operations
(OMOs) and asset prices.
Additionally, the connection
between OMOs and the volatility of asset returns is also examined.
While the primary emphasis of the paper is the impact of OMOs on
both short and long term interest rates, the influence of OMOs on
the stock and the foreign exchange markets are also analyzed.
Whether or not the Fed has the ability to
influence asset
prices is of prime interest to macroeconomists that investigate the
connection between monetary policy and the real economy.
The issue
is also important to investors who are concerned with the value of
their portfolios.
Recent papers by Bernanke (1990), Bernanke and Blinder (1990),
Kuttner and Friedman (1991), Stock and Watson (1989), and Strongin
(1991), demonstrate that interest rates are very informative about
future movements of real macro variables.
that
the
spreads,
Federal
and the
perform very well
funds
rate,
various
spread between the
In particular, they find
short
short
term
and
as predictors of business
interest
long term
cycles.
If
rate
rates
indeed
there is such a link between interest rates and the real sector of
the economy,
the implication of these findings is that monetary
policy can be used to influence output, provided the Fed has the
ability
to
influence
interest
rates.
However,
attempts
to
empirically document the much hypothesized negative correlation
between monetary policy and interest rates (the liquidity effect)
has met with failure.
In a survey paper, after updating some of
2
the empirical studies on this topic, Reichenstein
the
conclusion
empirical
that
support
since
for
at
the
least
April
existence
of
(1987)
1975,
the
reaches
there
liquidity
is
no
effect.
However, the failure of previous studies to document the liquidity
effect may have been due to their research design.
a
strong
case
interest
can be made
rates
is
not
that
the
the
impact
appropriate
In particular,
of money
nexus
for
growth
the
on
empirical
examination of the liquidity effect.
This paper provides strong evidence for the contention that
daily Open Market Operations influence asset prices.
the
sign
effect:
rates,
of
the
relation
Injection
and
of
is
as
reserves
hypothesized
into
reserve withdrawals
the
by
system
increase
Furthermore,
the
liquidity
lowers
interest
interest
rates.
Taken
together with the evidence linking interest rates to real macro
economic activity,
this
finding supports the view that monetary
policy influences the real sector of the economy.
The finding that the actions of the Fed influence asset prices
probably does not come as a surprise to most investors.
managers
in
convinced
houses,
the
of
this
employ
activities
of
financial
that
all
economists
the
Fed.
sector
major
as
By
"Fed
of
the
banks,
economy
as
well
watchers",
employing
these
to
In fact
must
as
be
so
brokerage
monitor
individuals
the
their
employers must be hoping to receive information about the "correct"
interpretation
of
the
Fed's
transactions.
This
in
return,
presumably, leads to potentially profitable trading strategies, or
avoidance of losses on portfolio values.
3
In
addition
prices,
this
to
paper
the
impact
empirically
of
the
examines
Fed's
actions
the
connection
daily OMOs and the volatility of asset returns.
asset
returns
considerations.
is
crucial
to
investors
for
on
asset
between
Volatility of
asset
pricing
It is also likely that volatility has a bearing on
the real sector of the economy by influencing capital budgeting and
consumption decisions.
There is a substantial body of papers that
document the time variation of asset return distributions.
the
form
of volatility
of
asset
returns
is well
While
documented by
statistical conditional variance models, the sources of volatility
has not been investigated as extensively.1 Monetary policy may be
an important factor in asset return volatility.
However, it is not
clear, on theoretical grounds, whether monetary policy would dampen
or magnify the volatility of asset returns.
2. MONETARY AUTHORITY AND ASSET PRICES
There are some theoretical models in the literature that
demonstrate that the monetary authority, by conducting open market
operations, can influence interest rates. Grossman and Weiss (1983)
and Rotemberg (1984) show that in a world where money is needed to
execute transactions both in the goods and financial markets, a one
time unanticipated sale of bonds by the central bank will raise
interest rates. In Grossman and Weiss,
the
central
intervals.
bank
go
to
As a result,
supply at any one time.
the
bank
the agents that trade with
to
withdraw
cash
at
fixed
they hold a small portion of the money
Given this,
the open market sale raises
4
interest rates, not because it changes inflationary expectations or
the real rate, but because the traders do not have the ability to
obtain more money,
i.e. they are liquidity constrained.
Lucas (1988) developed a model along the same lines. In
his model,
the
agents
that
trade
in goods
and
securities
face
separate liquidity constraints, but are members of the same family,
bound by a household utility function. The representative household
has
three members,
balance.
an
endowment
of goods,
and
an
initial
cash
The initial cash balances are allocated to the purchase
of goods and securities at the beginning of the period.
The only
shock to the system in this model is in the form of an open market
operation.
This
shock
takes
place
after
the
allocation
of
the
family's funds among the two purchasing activities has already been
made. Furthermore, this shock is observed only by the agents that
trade in the securities market. As a result, the shock in question
affects neither the distribution of cash balances between financial
market and goods market purchases,
nor the prices
in the goods
market. The only response to open market operations shocks takes
the form of changes in
bond prices.
Given that the cash raised
from the sale of family endowments is not available in the current
period,
and that the goods market is unaware of the shock,
bond
prices need to change for the markets to clear. The marginal rate
of substitution in this model is constant. Bond prices change due
to
the
liquidity
expectations
transaction.
constraint,
implications
of
and
the
not
due
to
unanticipated
inflationary
open
market
5
The Keynesian concept of liquidity is somewhat different.
In a Keynesian world, goods prices do not respond to open market
transaction shocks because prices in the goods market are "sticky".
However, unlike the case in the models discussed above, the real
rate
changes
as
a
result
of
the
unanticipated
open
market
operation. The Keynesian model typically is not cast in the context
of the individual consumer.
However, presumably individuals hold
money for purposes of executing
goods and securities transactions.
Faced with an unanticipated open market sale,
in order
for the
individual to be convinced to hold more securities (thus, consume
less today), he has to be offered a higher real rate. This means
that, in a Keynesian world, the nominal rate changes are triggered
by changes in the real rate when the monetary authority engages in
a bond sale.
Differences in what is meant by the liquidity effect not
withstanding,
above
both the Keynesian model and the models discussed
agree on the
sign of the
interest
rate
response
to open
market transactions: security purchases by the monetary authority
lower interest rates, while security sales cause the rates to be
higher. However,
empirical studies fail to confirm the existence
a negative correlation between money growth and interest rates.2
In
a
recent
study,
using
data
targeting operating procedure period,
from
the
Fed
funds
rate
Cook and Hahn
(1989)
show
that changes in the Fed funds rate target caused changes in other
interest
September
rates.
1979,
They
find
changes
in
that
the
during
Fed
September
funds
rate
1974
through
caused
large
6
movements
in
the
short
term
rates
and
movements
in
the
longer
term
rates.
small
While
but
this
significant
is
not
direct
evidence of the existence of the liquidity effect in the sense of
a
negative
correlation
between
money
and
interest
rates,
it
indicates that the Fed has the ability to influence interest rates.
Additionally,
the
findings
of
the
money
supply
announcements
literature also implies that the Fed has the ability to influence
asset prices. These studies document the reaction of interest rates
to money announcement surprises. While the interest rate response
is consistent both with the expected liquidity effect and possible
changes in inflationary expectations, recent evidence (Strongin and
Tarhan
(1990),
Hardouvelis
(1987))
support
the
contention
that
interest rates respond due to expected liquidity considerations.3
If
indeed
the
response
of
interest
rates
is
triggered
by
anticipations of the Fed's reaction to the money figures (expected
liquidity effect), the failure to document the actual liquidity
effect
may
just
be
indicative
of
a
problem
in
empirical
test
design.
The
relationship
between
OMOs
and
interest
rates
may
prove to be a better forum in which to investigate the existence of
the liquidity effect than examining the link between money and
interest rates. One difference between this study and the previous
studies is that,
in this paper, the relationship examined is the
one between open market operations and asset prices,
and not the
one between money and asset prices. Since the question investigated
in this study is the ability of the Fed to affect interest rates,
7
the causal link between asset prices and a variable over which the
Fed has direct control is the appropriate avenue of inquiry.
The Fed has the ability to control the level of reserves in
the system by its conduct of open market operations (OMOs) . Changes
in the level of reserves triggered by OMOs translate into changes
in money, via the multiplier process,
as investors and financial
institutions respond to the Fed's actions.
intentions
of the
Fed more
Thus, OMOs capture the
accurately than
the
growth
rate
of
money, which is jointly determined by the Fed, the public, and the
financial institutions.
Additionally, OMOs have the
advantage of
being events that are readily observed by market participants as
soon as they are executed.4 In contrast,
when
investors observe the growth
studies show that
it is not clear exactly
in money.
In
fact,
empirical
interest rates respond to money announcements
even though the money growth that is being announced had already
been determined ten days prior to the announcement.5
This may
indicate that investors do not observe money growth when it takes
place. OMOs are free of this problem.
The sample period in this study
31,
1984)
October
6,
(October 2, 1979 - December
covers
the
October
1979
- October
1979,
the
Federal
Reserve
1982
announced
period.
changes
in
On
its
operating procedures. Prior to this date, the short term focus of
monetary policy centered on maintaining the Fed funds rate within
a narrow target range.
operating
policy
from
The new procedures changed the focus of
targeting
Fed
funds,
to
a
policy
attempts to accomplish monetary policy objectives by
that
targeting
8
reserves.
Specifically, the desk was directed to set and maintain
a target path for nonborrowed reserves consistent with long term
money growth
Reserve
regime
again
can
targets.6
changed
best
be
In the
late
Fall
of
1982,
its operating procedures.
characterized
by
a
set
of
the
Federal
The post-1982
procedures
that
targets borrowed reserves.7
Using data from the post October 1979
period is ideal for the
empirical question examined in this paper.
was characterized by a regime that targets
If the period studied
interest rates,
the
power of empirical tests conducted would be potentially low.
To
see this, assume that in fact the Fed can affect interest rates by
its actions.
As the Fed funds rate starts to diverge
target range,
the Fed will supply reserves to or drain reserves
from the system in order to prevent rates from changing.
from its
If the
Fed indeed has the ability to control interest rates, the data will
show substantially more variation in OMOs than in interest rates.
In fact, in the extreme, if the Fed had a point target rather than
a range, and is successful in achieving its target, there will be
no variation in interest rates.
In such a scenario, the empirical
tests will detect no causality between OMOs and interest rates,
when in reality the Fed will have perfect control over interest
rates.3
3. OPEN MARKET OPERATIONS
The operating policy objective of the trading desk is to implement
the monetary policy objectives set by the Federal Open Market
9
Committee
(FOMC). The FOMC meets six to eight times a year,
decides
on
period,
the
a course
for monetary policy.
targets
for
the
conduct
During
of
the
monetary
and
1979-1982
policy
were
expressed in terms of the desired growth for monetary aggregates.
The Desk,
then, had the responsibility of converting these money
growth targets into the implied target path of nonborrowed reserves
for the intermeeting period.
The next step was
conduct
the
OMOs,
so
as to make
realized
for the Desk to
level
of nonborrowed
reserves for the intermeeting period equal the weekly average of
the
specified
target
path.
An
algorithm
describing
the
implementation of the monetary policy during this time period is
developed in Spindt and Tarhan (1987).
The
first
step
in
converting
the
FOMC's
monetary
policy
objectives involves the computation of the weekly target for money.
The next step is to determine the path of required reserves implied
by
the
projected
path
for
accounting regime that was
banks'
money.
Under
the
lagged
in effect during the
reserve
sample period,
required reserves for a given week were determined on the
basis of deposits they held two weeks previously.
path for required reserves
Given this, the
consistent with the intermeeting period
targets is obtained by multiplying the average reserve requirement
ratio with projected money figure from two weeks earlier.
the
projections
for
excess
reserves
are
added
to
the
Next,
required
reserves path to obtain the desired path for total reserves.
The
target
directives,
path
is
for nonborrowed
then
calculated
reserves
by
implied by
subtracting
the
the
FOMC
level
of
10
discount window
borrowing
assumed by
FOMC
Assumption"), from the total reserves path.
Desk
is
to
nonborrowed
conduct
reserves
OMOs,
such
during
the
that
("Initial
Borrowing
The objective of the
the
realized
intermeeting
average weekly nonborrowed reserves target.
level
period
The
of
equal
the
step
in
last
determining the magnitude of the OMOs for a given week involves
estimating the exogenous factors that will influence the level of
reserves in the system.
These projections,
then,
are netted out
from the target nonborrowed reserves path to arrive at the size of
OMOs to be conducted during that week.
Among the exogenous factors
("technical operating factors")
that the Desk needs to forecast, three are especially important.8
These
factors
difficulty,
Reserve
have
the
float.
considerable
most
crucial
Float
arises
of
due
size.
In
these
to
terms
factors
the
fact
of
forecasting
is
the
Federal
that
the
Federal
Reserve credits banks for the checks presented, on a shorter time
schedule than the time it takes to collect on these checks. Because
of unforeseen problems
in communication and transportation,
the
level of float can show substantial variability. During the sample
period float projection errors in the magnitude of 500 million
1 billion dollars per day were not uncommon.
In comparison,
to
the
average amount of reserves injection needed to sustain a 6 percent
annual growth in Ml during 1981 was
in the order of 50 million
dollars per week.9
The second source of uncertainty about the actual level
of
reserves
in
the
system
involves
the
deposits
of
the
U.S.
11
Treasury. The Treasury maintains accounts with various commercial
banks (Tax and Loan accounts). It periodically transfers funds from
these accounts to
banks.
its checking accounts at the Federal
When this happens,
the amount of reserves
declines. When the Treasury writes
Reserve
in the system
checks against its accounts at
the Federal Reserve, on the other hand, reserves are injected into
the system once the Fed credits the reserve balances of commercial
banks. At times, there can be significant errors in projecting the
reserve implications of these transactions.10
The portfolio decisions of foreign central banks constitute
the
third
significant
accommodates
these
their trades,
exogenous
reserve
factor.
institutions by becoming
a
When
the
Fed
counter party to
it in effect injects or drains reserves. Thus, the
desk needs to adjust its OMOs for
the expected level of foreign
central bank trades with the Fed.
Once
the
size
of
the
0M0
is
determined,
the
Desk
must
determine how to execute the required trades. On this issue, the
Desk has considerable flexibility.
The alternatives available to
the Desk have three broad characteristics.
the choice between OMOs that will
permanently
affect the level
transactions
whose initial reserve implications will be reversed
in the near
(repurchase
transactions), versus
of reserves
those
future
(outright
One decision involves
agreements
and
matched
sale-purchases). The
second decision that needs to be made is whether to execute trades
in the secondary market,
with dealers,
or with
foreign central
banks. The third issue involves the type of securities to be used
12
in conducting the OMOs. Here, one choice would be between short
term
Treasury
Treasuries
securities
(Treasury
bills),
longer
term
(coupon securities). Another choice would be between
Treasuries and Federal Agency securities.
the Desk,
and
The primary concern of
in comparing the various alternatives,
is to select a
course of action such that the Fed will not have undue influence in
the determination of security prices. As a result, the Fed monitors
the security portfolios of dealers,
and attempts to conduct OMOs
only
dealers
with
those
quantities.
securities
Thus,
that
have
in
sufficient
even when the Fed wants to influence security
prices, it does not want the security prices to change because of
market micro
that,
structure
considerations.
for the most part,
In practice,
this
means
Treasury bills end up as the preferred
instrument of OMOs.
An 0M0 could be in the form of an outright transaction.
In the case of an outright purchase
(sale) , the reserves in the
system increase (decrease) permanently. Repurchase agreements (RPs)
and matched sale-purchases
(MSPs), on the other hand, change the
level of reserves for a limited time period. In an RP transaction,
the level of reserves increases in the current period,
but this
increase is drained from the system when the RP matures.
transaction,
in essence,
is a reverse RP,
and thus,
A MSP
the initial
decline in the level of reserves is offset at its term.
The
sample
December 31,
period
1984.
for
this
study
is
Open market operations
October
2,
1979
to
are measured as the
13
changes
in
the
Fed's
portfolio.
The
daily
data
on
the
Fed's
portfolio was obtained from the Federal Reserve Board.
4. EMPIRICAL RESULTS: OPEN MARKET OPERATIONS AND ASSET PRICES
The impact of the Fed's actions on asset prices is first
examined by conducting bivariate Grange causality tests between
interest rates and OMOs. These tests are later repeated for stock
returns and returns on foreign exchange market variables.
i. Open Market Operations and Interest Rates
The hypothesis that open market operations (AFPt) do not
Granger cause interest rates (rt) is examined by testing the joint
hypothesis that >Si=0 in the following regression.
6
6
Art = ao + E
a . Art - i + E
i =1
P i AFI>t - \ + e t
(i)
l =1
The interest rates used cover the maturity spectrum from 1 day
(the Fed funds rate) to 30 years (the 30 year Treasury bond rate).
In addition to these two rates other interest rates examined are
the Treasury bills of 3, 6 and 12 month maturities and Treasury
bond rates of 1, 2, 3, 5, 10 and 20 year maturities.
The Granger causality test results obtained from
(1)
for changes
portfolio
in
interest rates
and the
(AFPt) are presented in Table I.11
change
estimating
in the
Fed's
The results indicate
14
that the null hypothesis that OMOs do not Granger-cause interest
rates is rejected . These results show that OMOs affect both short
and long term interest rates.
While these results strongly indicate that the actions of the
Fed
influence
interest
rates,
what
needs
to
be
determined
is
whether or not the sign of the relationship is as predicted by the
liquidity effect.
To see whether increases
in the
size of the
Fed's portfolio (transactions that inject reserves into the system)
result
in
standard
lower
interest
deviation
examined.
shock
rates,
impulse
response
in orthogonalized
OMO
paths
to
innovations
a
are
Cumulative response of interest changes as of 1, 6, and
12 days after the OMO shock are reported in Table II.
These results appear reasonable on various grounds:
predicted
by
negative,
indicating
injections.
the
liquidity
Second,
that
A
innovations
one
rates
as expected,
more than long term rates,
maturity.
effect,
the
fall
sign
in
in
First, as
all
response
cases
to
is
reserve
short term rates are affected
and the impact of OMOs decline with
standard deviation
shock
in orthogonalized OMO
generate a 7.5 basis point reduction in the Fed funds
rate in the first period.
The bill rates decline by around 1.2
basis points, and the 30 year rate declines by 0.8 basis points.12
Cook
and
Hahn
(1989)
find
that
Fed
funds
rate
changes
constant effect across the 3 months to 12 months horizon.
have
a
This is
confirmed by the results displayed in Table II. However, there are
two differences: First, in their case the magnitude of the T-bill
response is roughly one half of the change in the Funds rate while
15
here it is around 16 percent.
is
constant
across
the
Second, while the initial response
Treasury
bill
maturity
spectrum,
the
cumulative response after 6 and 12 days varies with the maturity of
Treasury
bills.
After
6
days
the
cumulative
Fed
funds
rate
response is 13 basis points, and the bill rate responses are in the
range of 20 to 3 0 percent of this magnitude.
Cumulative responses
after 12 days are similar in relative magnitude to the response
after 6 days. One notable exception is that at the longest end of
the
maturity
spectrum
(20
and
30
year
rates) , the
cumulative
response is close in magnitude to the initial response.
The statistical significance of the impulse responses can be
seen in Figures 1 to 4, which display the impulse response paths of
selective
interest
rates
(in basis
points)
to
a
one
standard
deviation shock in OMOs over a 20 day horizon (the response paths
are bounded by 95% confidence intervals).
The interest rates in
question are the Fed funds rate, the 3 months bill rate,
Treasury bond rates of 2, and 20 year maturities.
and the
These graphs
show that the impact of monetary policy on interest rates is felt
very quickly.
The adjustment of interest rates to monetary shocks
is close to completion within 10 days.
Combined with the results
of Table II, these figures indicate that the adjustment of interest
rates to monetary policy is fast,
and also that monetary policy
have a lasting impact on interest rates (interest rates stabilize
at lower levels following a reserves injection).
Table II also displays the response of OMOs to own shocks.
The initial period shock is around 1.9 billion dollars. The initial
16
positive response of OMOs is reversed later on.
As a result, the
cumulative response after 12 days is in the range of 850 to 870
million dollars.
In order to test whether interest rates Granger cause OMOs,
the following equation is estimated:
6
A F P t = Yo + £
6
Yi A F P t_5 + £
i “1
6 i A r t _, + u t
(2)
i “1
The results obtained from estimating (2) are also displayed in
Table I.
that
The null hypothesis of no causality
(joint hypothesis
<Sj = 0) cannot be rejected for any of the interest rates.
first glance,
includes
Tarhan
the
this is surprising.
October
(1987)
report
1979
After all,
to October
empirical
1982
the sample period
period.
results that
At
Spindt
supports
contention that during this time period the target
the
and
Fed's
of monetary
policy was nonborrowed reserves and not interest rates.
However,
the presence of Granger causality running from interest rates to
OMOs
does
not
necessarily
imply
that
the
Fed
was
following
leaning-against-the-wind policy with respect to interest rates.
a
In
fact, upon examination of the 0M0 impulse response to innovations
in interest rates, it becomes apparent that both the sign and size
of the responses are incompatible with an interest rate targeting
procedure.
The
response
of OMOs
displayed in Table III.
to
innovations
in
interest
rates
is
Comparing the impulse responses to 0M0
17
innovations
(Table
II)
with
impulse responses
innovations, two things stand out.
to
interest rate
First, looking at the initial
period responses, the size of the reserve injection triggered by a
one standard deviation shock in interest rates is very small in
relation to the size of the shock: For example, a 63 basis increase
in the Fed funds rate results in a reserve increase in the amount
of
only
reserve
304
million
increases
dollars.
in
the
Whereas,
magnitude
of
as
1.9
discussed
billion
before,
dollars
required to move the Fed funds rate by 7.5 basis points
initial period.
increases
initially
case
of
in the
Perhaps more importantly, while an interest rate
leads
to a reserve
injection,
withdrawn from the system in the subsequent periods.
in the
is
a
Fed
funds
rate
shock,
even
reserves
are
For example,
though
reserves
increase initially by 304 million dollars, the cumulative response
after 12 days is a reserve decrease of 25.6 million dollars.
pattern holds true for interest rate shocks of all maturities.
This
In
all cases small initial increases in reserves in the initial period
are reversed in the subsequent periods such that the net response
to interest rate increases is a small withdrawal of reserves from
the system.
decline,
The important point here is not that reserves actually
but that they do not change by a meaningful
amount in
response to interest rate increases. Thus, while there is evidence
of Granger causality running from interest rates to open market
operations, the size and the sign of the cumulative 0M0 response is
not
indicative
rates.
of
a
central
bank policy
that
targets
interest
18
Figures
dollars)
to
5
and
a
standard
interest rates
6
show
the
estimated
deviation
shock
response
in
two
of
OMOs
(in
representative
(the Fed funds rate and the 5 year Treasury rate
respectively).
The
cumulative
response
of
interest
rates
to
own
shocks
indicate that the initial movement in interest rates persist.
By
the end of 12 days, initial interest rate shocks in the magnitude
of 63 to 12 basis points produce a net increase of 40 to 14 basis
in interest rates, but a small decline in the volume of reserves in
the system (26 to 135 million dollars).
Figures 7 and 8 enable us to compare the response of interest
rates and OMOs to own shocks versus shocks in the "other" variable.
Figure 7 graphs how the Fed fund rate reacts to own shocks compared
with
OMO
shocks.
Since
interest rates differ,
the
unit
of measurement
for
OMOs
and
the response paths are scaled by dividing
the response of each variable by the square root of its residual
variance.
Thus, the responses are measured in terms of fractions
of standard deviations.
Figure 8 displays the reaction of OMOs to
own shocks compared with the reaction to a shock in a selective
interest rate (6 months T-bill rate).
What emerges from figures 7
and 8 is that for both OMOs and interest rates, the reaction to own
shocks is more pronounced than their response to innovations in the
"other" variable.13
ii.Qpen Market Operations and Other Financial Asset Returns
Open Market Operations could influence the prices of other
financial
assets by
influencing
interest rates.
The change
in
19
interest rates, in return, may change asset prices if it means that
the discount rate used in valuing asset cash flow streams change
with interest rates.
Alternatively,
the actions of the Fed may
change asset prices by influencing the market risk premia.
This
also will lead investors to revise their required rates of return.
A
third
possibility
is
that
OMOs
may
have
an
impact
returns by influencing the real sector of the economy.
on
asset
In addition
to interest rates, this paper investigates the influence of OMOs on
stock returns, Eurocurrency deposit rates (Eurodollar, Euroyen, and
Eurodeutchmark deposits of one month maturity), and spot exchange
rates
(the U.S.
dollar-DM rate and the U.S.
dollar-Japanese Yen
rate).
Table
IV
summarizes
results
Granger causality tests conducted.
obtained
portfolio
(VWRET),
are employed:
and
equally
the
battery
of
The link between stock returns
and OMOs are examined in a bivariate model.
stock return measures
from
Two alternative daily
Value weighted
weighted
CRSP
CRSP market
market
return
portfolio (EWRET) . Monetary policy may affect stock prices via the
three channels discussed.
For example, OMOs indicating a policy of
monetary ease may boost stock prices by lowering interest rates and
leading investors to revise downwards the discount rates they use
in valuing expected equity cash flows.
The policy of monetary ease
may also reduce investor uncertainty and lower the risk premia,
once again increasing stock prices as a result of lower required
rates of returns on equity.
To the extent lower interest rates are
associated with higher expected output in the real sector,
stock
20
prices may go up as a result of an increase in expected corporate
profits.
Monetary policy could have a significant impact on share
prices since it can lower equity capitalization rates and increase
in expected equity cash flows simultaneously.
Investors mention
all of these channels in arguing the importance of the actions of
the Fed for stock market returns.
However, in spite of these
arguments, as an empirical matter, at least for the sample period
used in this study, there is no evidence that the Fed influences
share
prices.
obtained
from
Table
two
IV also
vector
exchange market variables.
The variables
in the
displays
the
autoregressions
significant
of
OMOs
and
results
foreign
There are four variables in each VAR.
first model
are OMOs,
Eurodollar and Euro DM deposit rates
one month maturity
(differences), and the spot
Dollar-DM exchange rate (DMs per dollar in log differences).
The second VAR includes the same variables, but the Japanese yen.
is substituted in place of the DM.
One
result
causality between
is
that
OMOs
there
is
evidence
and one month
for
bidirectional
Eurodollar deposit
rates.
Given, the relationship between OMOs and domestic interest rates,
this result is not surprising.
Another significant result is that the two spot exchange rates
and OMOs are related.
Japanese yen
The relationship is bidirectional for the
(JY) , but in the case of the DM,
OMOs but is not caused by OMOs.
JY
exchange
rates
Granger
it Granger causes
The fact that both the DM and the
cause
OMOs
may
indicate
that
stabilization of the value of the dollar is one of the goals of
21
monetary
policy.
stabilization
However,
attempts
are
it
is
also
confined
to
possible
the
that
foreign
the
exchange
intervention activities of the Fed, and it may be that OMOs appear
to be related to the exchange rates due to the sterilization
of the intervention operations.
phase
In fact impulse responses
(not
reported here) indicate that a shock in the form of an increase in
the value of the dollar vis-a-vis both the DM and the JY trigger an
Open Market Sale.
policy
of
This will be consistent with an intervention
purchasing
dollars
when
the
value
of
the
dollar
increases, and offsetting the increase in the money supply caused
by the intervention by means of open market sales.14
Table
IV
also
between exchange
indicates the presence
of Granger causality
rates and Euro deposit rates.
This result is
consistent with the Interest Rate Parity relationship. 5
5. EMPIRICAL RESULTS: OMOs AND THE VOLATILITY OF ASSET PRICES
Time
conditional
established
volatility
empirical
phenomena.
Bollerslev
(1989),and
Connolly
volatility
of
rates.
analyzed
in
Stambaugh
exchange
Baillie
of
and
(1987), Schwert
For
and
returns
example,
Taylor
Volatility
DeGennaro
(1989)
asset
(1990),
a
Baillie
(1990)
in
is
stock
French
well
and
examine
returns
Schwert
and Poterba and Summers
the
is
and
(1987).
Econometric models that document time conditional volatility of
financial assets (ARCH, GARCH), do not typically investigate what
economic variables could account for observed volatility.
policy may
be
an
important
factor
in
asset
return
Monetary
volatility.
22
First, stabilization of interest rates may be one of the targets of
monetary policy.
financial
If so, the Fed may respond to volatility in the
markets.,
volatility.
Second,
OMOs
may
On theoretical grounds,
affect
interest
rate
it is not clear whether the
activities of the Fed would increase or dampen the volatility in
financial markets.
There
information
(for
flows
is evidence
example,
in
in the stock market that
the
form
of
earnings
announcements) tend to increase volatility of asset returns.
It is
conceivable that the actions of the Fed may produce similar results
as investors try to extract the policy content of OMOs.
other hand,
if stabilization
is a goal
On the
of monetary policy,
the
Fed's actions may signal to the market that it intends to reduce
volatility.
This, in return may reduce volatility if the Fed has
credibility.
The general point
is that the connection between
monetary policy and volatility of asset prices needs to be examined
empirically.
The effect of OMOs on the conditional mean and variance
of financial assets is examined by:
Art
=
b0
+
b^MO^
o*
=
a0
+
a1et.12
+
+
Where DT is Open Market Operations.
et
a2(abs ( O M O ^ ) )
(3)
(4)
The conditional mean (3) and
the conditional variance (4) equations are jointly estimated using
the Berndt, Hall, Hall and Hausman maximum likelihood procedure.
23
The
sign of the
estimate
for the a2 coefficient would
whether OMOs magnify or dampen volatility.
of OMOs variable
simple
ARCH
is deleted from
specification.
When the absolute value
(4) , the model
When
the
indicate
simple
collapses to a
ARCH
model
was
estimated for the assets under consideration the estimates for a1
proved to be very highly significant,
ARCH effects.
indicating the presence of
If the results obtained from (3) and (4) show that
a1 becomes insignificant, this would indicate that ARCH effects on
asset returns can be explained by OMOs.
It is also possible that
ARCH effects are not related to policy.
Table V and VI display the results obtained from estimation of
the
conditional
consideration.
mean
and
variance
equations
for
assets
under
The estimate for b, is negative and significant for
all the interest rates considered, confirming again, the presence
of the liquidity effect
Fed's
portfolio
Estimates
of
assets considered,
since it indicates that increases in the
(reserve
injections)
lower
a1 continue to be highly
interest
significant
rates.
for all
indicating that ARCH effects cannot completely
be explained by OMOs.
The estimate for a2 is negative and highly
significant in the Fed funds equation.
Apparently, the Fed has the
ability to reduce volatility in this market.
The estimate for this
coefficient is also significant in the 1 month Eurodollar, and the
30
year
Treasury
rates.
The
same
coefficient
is
marginally
significant in the 6 month T-bill rate, and the 5 year and 20 year
Treasury
rates.
In
all
these
cases
the
sign
continues
to be
24
negative,
indicating the actions of the Fed have
a stabilizing
effect in these markets.
An interesting result that emerges from Table VI is that while
OMOs do not appear to have any impact on the level of stock prices,
they significantly reduce the volatility of stock returns since a2
is negative and significant for both stock return measures. In sum,
it appears that when OMOs turn out to be a significant explanatory
variable in the conditional volatility of asset returns, in all but
one case
(spot yen/dollar exchange rate), the effect
is
in the
direction of reduced volatility.
7. CONCLUSIONS
Even
though
the
Federal
Reserve
is
one
of
the
most
closely monitored institutions by investors, the impact of OMOs on
asset prices has not been investigated empirically.
Using data
from a period during which the Fed did not peg interest rates, this
study
examines
this
issue
in
the
context
of
Granger-causality
tests. The major findings of the study are the following:
1) OMOs
Granger-cause interest rates across the maturity spectrum.
sign
of
the
relationship
confirms
hypothesized liquidity effect.
the
existence
of
2) The
the
much
3) As expected, the magnitude of
the response of the interest rates decay with the term to maturity.
4)
Interest rate response to monetary policy appears to be very
fast.
5) While there is Granger causality running from interest
rates to OMOs, this does not appear to be indicative of interest
rate targeting.
6) Monetary policy appears to effect some asset
25
returns in the foreign exchange market but not the stock market.
7) When monetary policy influences the conditional volatility of
asset
returns,
it
is
the
in the
actions
direction
of
the
of
Fed
reducing
have
a
volatility,
indicating
that
stabilizing
influence.
8) Finally, combined with the evidence that show that
there is a link between interest rates and the real sector of the
economy, this paper's finding that the OMOs affect interest rates
indicate that monetary policy influences the real sector.
ENDNOTES
1. One paper that examines the influence of policy on volatility
is Connolly and Taylor (1990).
They investigate the connection
between spot Japanese Yen exchange rate volatility and central bank
intervention.
Another paper, Lastrapes (1989), looks at the
volatility of exchange rates under different monetary regimes.
Other papers examined the connection between trading volume and
volatility.
2.
The earlier tests on this topic were conducted by Gibson
(1970), Cagan (1972) and Cagan and Gandolfi (1969). These studies
provide results supporting the liquidity effect.
However, later
tests on this topic reached a different conclusion.
For example,
Mishkin (1981) and (1982) finds no empirical support for the
liquidity effect that has the correct sign in the case of both the
short and long term rates. More recent studies also do not detect
the existence of a negative correlation between money growth and
interest rates. See for example, Melvin (1983), Makin (1983), and
Wilcox (1983). In this survey paper,-Reichenstein (1987) concludes
that since at least April 1987 there is no empirical support for
the much hypothesized liquidity effect.
3.
Strongin and Tarhan (1990) examine the reaction of interest
rates to money announcements.
Their model discriminates between
the two hypotheses by directly taking into account investor
expectations regarding the Federal Reserve's monetary stance.
Their results strongly support the expected liquidity hypothesis.
Hardouvelis (1987), on the other hand, investigates the reaction of
interest rates to reserves announcements.
His results show that
during the May 1980 - October 1982 period real interest rates
reacted to unanticipated nonborrowed reserves announcements.
To
the extent reserves announcements provide information about future
money supply changes, the interest rate reaction indicates the
presence of the liquidity effect.
4. Actually they
the Fed is about
from the primary
which of the bids
are observed even before they are executed. When
to execute an OMO, it asks for bids and offers
government securities dealers.
Then it decides
and offers to accept.*
5
5.
The figures regarding the level of the monetary base are
released ten days prior to the announcement. Thus, the information
being revealed by the money supply announcement is information
regarding the value of the multiplier.
The observed reaction of
interest rates to the announced money figure in reality captures
the response of interest rates to the fact that the multiplier
implied by the money figure was different than expected.
6.
Spindt and Tarhan (1987) examine the October 1979 - October
1982 period, to determine whether or not the Fed indeed changed its
operating procedures.
Some critics of the Fed claim that the new
policy still amounted to a procedure that pegged interest rates.
If during this period the Fed was targeting nonborrowed reserves,
it should be the case that innovations in money Granger cause
innovations in borrowed reserves.
An empirical finding that
indicates a causal link between money and nonborrowed reserves, on
the other hand, would be indicative of a policy that targets the
Fed funds rate.
Their results show the existence of causality
running from money to borrowed reserves. Thus, it appears that the
focus of monetary policy during this time period was what the Fed
claimed it to be.
7. Tests conducted in this paper were repeated for two sub sample
periods:
October 1979 - October 1982 and October 1982 - December
1984.
However, the results for the sub sample periods were not
materially different from the full sample period results.
Thus,
only the full sample period results are reported here.
8.
For a detailed description of the daily activities of the
Federal Reserve trading desk during the sample period, see Meek
(1981), and Melton (1985).
9.
See Meek (1981), Chapter 7.
10.
Even though the Treasury accounts normally are exogenous to
the activities of the Desk, at times, these balances can become a
tool of reserve management to the Fed. For example, when the Desk
wants to drain reserves from the system, if it feels it is not
receiving 'good' bids from the dealers for security sales, it may
request that the Treasury transfer funds from its Tax and Loans
accounts to its accounts at the Fed.
This will have the same
reserve drainage implication as the sale of securities from its
portfolio.
11.
Consistent estimates of the covariance matrix of estimated
coefficients was obtained by using Robusterrors procedure of RATS
version 3.0.
12. The decline in the size of the coefficients is not monotonic
with maturity. In fact, the decline in the 1 year Treasury rate is
actually larger than the decline in the 1 year T-bill rate.
Strongin and Tarhan (1990) find a similar response to money
announcement shocks. Their explanation of this is that the l year
Treasury bond, because it is a coupon paying security, has a
shorter effective maturity than a 1 year discount security like the
Treasury bill.3
1
13.
Figures 7 and 8 are representative of the relative impulse
responses for all interest rates examined.
The finding that own
innovations ara a bigger source of variation in both the OMOs and
interest rates is confirmed by variance decompositions. Except for
the Fed funds rate, own innovations in interest rates account for
over 90 percent of the forecast errors in interest rates (20 day
horizon). Similarly, over 90 percent of the OMO variation is OMO
specific.
In the case of the Fed funds rate, OMO innovations
account for 24 percent of the variation and the Fed fund
innovations account for the remaining 76 percent.
These results
are not sensitive to the order of othogonalization.
14.
To understand the Granger causality running from OMOs to the
Japanese exchange rate,
impulse response to a one standard
deviation shock in OMOs was examined.
Impulse responses indicate
that an increase in the U.S. money supply lowers the value of the
dollar. While this could also be intervention related, it is also
possible that the decline in the value of the dollar is due to
lower domestic interest rates (via the interest rate parity) or due
to higher expected U.S. inflation rate (via purchasing power
parity).
REFERENCES
1.
Baillie, Richard T. and Tim Bollerslev. "The Message in Daily
Exchange Rates: A Conditional Variance Tale," Journal of
Business and Economic Statistics. 7 (1989), 297-305.
2.
Baillie, Richard T. and Ramon P. DeGennaro.
"Stock Returns
and Volatility," Journal of Financial and Quantitative
Analysis. 25 (1990), 203-214.
3.
Bernanke, Ben and Alan Blinder.
"The Federal Funds Rate and
the Channels of Monetary Transmission," NBER Working Paper
no. 3487, October 1990.
4.
Bernanke, Ben. "On the Predictive Power of Interest Rates and
Interest Rate Spreads," New England Economic R e view. Federal
Reserve Bank of Boston, November/December 1990, 51-68.
5.
Cagan, P.D. "The Channels of Monetary Effects," National
Bureau of Economic Research, New York, 1972.
6.
Cagan, P.D. and A. Gandolfi.
"The Lag in Monetary Policy as
Implied by the Time Pattern of Monetary Effects on Interest
Rates," American Economic Review. (May 1969), 277-84.
7.
Connolly, Robert A. and William M. Taylor.
"The Impact of
Intervention on Exchange Rate Volatility," Unpublished
Manuscript, Graduate School of Management, University of
California, Irvine (1990).
8.
Cook, Timothy and Thomas Hahn.
"The Effect of Changes in the
Federal Funds Rate Target on Market Interest Rates in the
1970's," Journal of Monetary Economics. 24 (1989), 331-51.
9.
French, Kennneth R . , G. William Schwert and Robert F.
Stambaugh.
"Expected Stock Returns and Volatility,"
Journal of Financial Economics. (19), 1987, 3-30.
10.
Friedman, Benjamin M. and Kenneth N. Kuttner.
"Why is the
Paper-Bill Spread Such a Good Predictor of Real Economic
Activity?", NBER Conference on New Research on Business
Cycles, Indicators and Forecasting, Forthcoming.
11.
Hardouvelis, Gikas A. "Reserve Announcements and Interest
Rates: Does Monetary Policy Matter?" Journal of Finance.
June 1987, 407-422.
12.
Gibson, William E.
"The Lag in the Effect of Monetary Policy
on Income and Interest Rates," Quarterly Journal of
Economics (1970), 288-300.
13.
Grossman, Stanford and Laurence Weiss. "A Transactions-Based
Model of the Monetary Transmission Mechanism," American
Economic Review. 73 (1983), 871-880.
14.
Lastrapes, William D.
"Weekly Exchange Rate Volatility and
U.S. Monetary Policy Regimes: An Application of the ARCH
Model," Journal of Money Credit and Banking. 21, (1989),
66-77.
15.
Lucas, Robert E.
"Liquidity and Interest Rates," University
of Chicago working paper, September 1988.
16.
Makin, J. H.
"Real Interest, Money Surprises, Anticipated
Inflation and Fiscal Deficits," The Review of Economics and
Statistics. August 1983, 374-384.
17.
Meek, Paul.
U.S. Monetary Policy and Financial Markets,
Federal Reserve Bank of New York, 1982.
18.
Melvin, Michael.
"The Vanishing Liquidity Effect of Money
on Interest: Analysis and Implications for Policy,"
Economic Inquiry. (1983), 188-202.
19.
Melton, William C.
Inside the-Fed: Making Monetary Policy.
Homewood, Illinois.
Dow Jones-Irwin, 1985.
20.
Mishkin, Frederick S. "Monetary Policy and Long-Term Interest
Rates: An Efficient Markets Approach," Journal of Monetary
Economics. (1981), 29-55.
21.
__________ "Monetary Policy and Short-term Interest Rates: An
Efficient Markets-Rational Expectations Approach," Journal
of Monetary Economics. (1982), 63-72.
22.
Poterba, James and Lawrence Summers.
"The Persistence of
Volatility and Stock Market Fluctuations," American
Economic Review. 76, (1986), 1142-1151.
23.
Reichenstein, W. "The Impact of Money on Short-Term Interest
Rates,"
Economic Inquiry. (1987), 67-82.
24.
Rotemberg, Julio J.
"A Monetary Equilibrium Model with
Transactactions Costs," Journal of Political Economy.
(1984), 40-58.
25.
Schwert, G. William. "Why Does Stock Market Volatility Change
Over Time," Journal of Finance. 44, (1989), 1115-1153.*
6
2
26.
Spindt, Paul A. and Vefa Tarhan.
"The Federal Reserve's New
Operating Procedures: A Post Mortem." Journal of Monetary
Economics. (1987), 107-123.
27.
Stock, James and Mark Watson.
"New Indexes of Coincident and
Leading Economic Indicators," NBER Macroeconomics Annual.
Oliver J. Blanchard and Stanley Fisher, eds. Cambridge, MIT
Press, (1989), 351-394.
28.
Strongin, Steven and Vefa Tarhan. "Money Supply Announcements
and the Market's Perception of Federal Reserve Policy,"
Journal of Money, Credit and Banking. May 1990, 135-153.
29.
Strongin, Steven.
"Macroeconomic Models and the Term
Structure of Interest Rates,"
Federal Reserve Bank of
Chicago, working paper, 1990.0
3
30.
Wilcox, J.A. "Why Real Rates Were So Low in the 1970's,"
American Economic Review. March 1983, 44-53.
TABLE I
Granger Causality Tests of Open Market Operations (OMOt) and
Interest Rates (rt)
0M0t Does Not Grangercause rt
Chi-Square
Statistic
(Marginal
Significance
level)
Interest Rate
Fed Funds
3 mos. T-bill
6 mos. T-bill
12 mos. T-bill
1 yr Treasury
2 yr Treasury
3 yr Treasury
5 yr Treasury
10 yr Treasury
20 yr Treasury
30 yr Treasury
29.45
10.56
14.44
16.83
19.16
22.13
22.60
15.35
17.55
21.27
15.06
(0.000)
(0.103)
(0.025)
(0.010)
(0.004)
(0.017)
(0.001)
(0.017)
(0.007)
(0.002)
(0.020)
rt Does not Grangercause 0M0t
Chi-square
Statistic
(Marginal
S igni f icance
level)
31.10
31.16
44.42
40.99
40.16
34.50
34.43
29.15
24.69
25.69
23.09
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
(0.000)
Notes:
Each equation contains a constant term, 6 lags of the
forecasted variable, and 6 lags of the variable that is suspected
to be Granger-causing the forecasted variable. The first marginal
significance levels are for omitting 6 lags of the open market
operations variable from the unrestricted OLS prediction equation
for the
interest rate
in question.
The
second marginal
significance level is for omitting 6 lags of the interest rate
variable from the unrestricted OLS prediction equation for open
market operations.
Interest rates are in first differences.
Open Market Operations
(0M0t) are measured as the first difference of the Fed's total
portfolio of securities.
The data is daily.
December 31, 1984.
The
sample
period
is
October
2,
1979
to
TABLE II
Impulse Responses to a One Standard Deviation Shock in 0M0
Innovations
Interest Rate
Fed funds
3 Mos T-bill
6 Mos T-bill
12 Mos T-bill
1 yr Treasury
2 yr Treasury
3 yr Treasury
5 yr Treasury
10 yr Treasury
20 yr Treasury
30 yr Treasury
Interest
Rate
Response
in the
Period after
the Shock
(Basis Points)
-7.49
-1.12
-1.21
-1.20
-1.61
-1.29
-1.23
-1.00
-0.92
-0.94
-0.78
Cumulative
Interest
Rate Response
(Basis Points)
After
6 davs
12 davs
-13.00
-4.21
-3.38
-2.76
-3.72
-2.94
-2.01
-1.84
-1.60
-1.24
-1.18
-11.29
-3.63
-2.79
-2.15
-2.94
-2.29
-1.51
-1.35
-1.13
-0.76
-0.78
Cumulative
OMO Response
to own shock
12 days
After
(Million
Dollars)
878.9
873.1
857.1
858.8
956.1
858.2
852.3
858.8
858.5
854.7
855.5
NOTE:
The magnitude of the initial OMO shock is in the range
$1910 million.
The response coefficients are ;
s ignificant for
interest rates. Confidence intervals for the response paths
selected interest rates are shown in Figures 1-4.
TABLE III
Impulse Responses to One Standard Deviation Shock in
Interest Rate Innovations
Interest
Rate
Shock (Basis
Points)
Fed-Funds (63BP)
3 Mos. T-bill (22.3)
6 Mos. T-bill (19.9)
12 Mos. T-bill (16.9)
1 yr. Treasury(20.5)
2 yr. Treasury(17.3)
3 yr. Treasury(16.1)
5 yr. Treasury(14.8)
10 yr. Treasury(13.3)
20 yr. Treasury(12.6)
30 yr. Treasury(12.2)
OMO
Response
in the
Period
after the
Shock
(Million
Dollars)
304.8
153.5
222.8
217.0
218.8
212.4
212.1
205.7
175.6
163.9
157.1
Cumulative
Response
12 days
after
(Million
Dollars)
-25.9
-112.6
-98.8
-102.1
-99.0
-109.6
-129.0
-103.0
-125.6
-132.7
-135.3
Cumulative
Interest
Rate Response
to own Shocks
after 12 days
(Basis Points)
40.3
28.8
24.6
21.1
25.6
22.6
20.3
18.6
16.3
14.5
14.1
Notes:
The numbers in parentheses in the first column are the
first period interest rate responses to own shocks.
0M0 responses are significant at the 5 percent level in the case of
all interest rates.
The interest rate response to own shocks is
also significant at the same level of significance.
Confidence intervals of the response of OMOs to selective interest
rates are shown in Figures 5-6.
TABLE IV
Granger Causality Tests of Open Market Operations and Stock
Market and Foreign Exchange Market variables
The First Variable does The Second Variable does
not Granger-Cause
not Granger-Cause
the Second Variable
the First Variable
Chi-Scruare Statistic
Relationship examined Chi-Souare Statistic
OMOs,
Stock
OMOs,
Stock
Equally Weighted
Returns
Value Weighted
Returns
OMOs, Spot
Deutche Mark (DM)
OMOs, 1 m o s .
Eurodollar Int. Rate
OMOs, 1 m o s .
Euro DM Int. Rate
1 mos. Eurodollar,
1 mos Euro DM Int. Rate
Spot DM, 1 mos.
Euro DM Int. Rate
Spot DM, 1 mos. Euro
Dollars Int. Rate
2.66 (0.850)
2.26
(0.894)
(0.961)
2.67
(0.849)
8.35 (0.214)
36.38
(0.000)
18.84 (0.004)
43.97
(0.000)
12.39 (0.054)
7.77
(0.256)
9.18 (0.163)
10.57
(0.102)
27.61 (0.000)
10.87
(0.092)
8.74
(0.189)
1.47
48.62
(0.000)
OMOs, Spot
Japanese Yen (JY)
13.21 (0.039)
OMOs, 1 m o s .
17.81 (0.007)
Euro Dollar Int. Rate
OMOs, 1 mos. Euro Yen
1.63 (0.950)
1 mos Euro Dollar
1 mos Euro Yen Int. Rate 6.39 (0.381)
Spot JY, 1 mos
Euro Yen Int. Rate
9.19 (0.163)
Spot JY, 1 mos
36.20 (0.000)
Euro Dollar Int. Rate
17.90 (0.006)
42.47 (0.000)
10.81 (0.094)
10.63
(0.100)
5.19
(0.519)
6.19
(0.402)
Notes:
The numbers in parentheses are marginal significance
levels. The daily stock returns are the equally and value weighted
CRSP portfolio returns.
The Granger Causality tests reported in rows 3 to 8 are obtained
from vector autoregressions with 6 daily lags of OMOs, spot DM
exchange rate (DMs per dollar) , the interest rate on one month
Eurodollar deposits, and the interest rate on one month Euro DM
deposits. The Granger Causality tests reported in rows 9 to 14 are
obtained from vector autoregressions with 6 daily lags of OMOs,
spot Japanese Yen exchange rate (JYs per dollar) , the interest rate
on one month Euro JY deposits.
The exchange rates are in log differences, interest rates are in
first differences.
See Table I for additional notes.
TABLE V
Open Market Operations and ARCH Effects on Interest Rate Variances
Art
CTe2
=
=
b»0
a o
Interest rate
fe o
Fed Funds
-0.02
(0.02)
3 mos T-bill
0.29
(0.60)
6 mos T-bill
0.20
(10.37)
12 mos T-bill
0.22
(10.47)
1 yr T-bond
0.23
(0.41)
2 yr T-bond
0.40
(0.82)
3 yr T-bond
0.48
(1.05)
5 yr T-bond
0.40
(0.98)
0.52
10 yr T-bond
(1.40)
20 yr T-bond
0.40
(1.1)
0.30
30 yr T-bond
(0.87)
Notes:
+
+
b iOMOt-l
aiet-i2
fei
-0.003
(14.27)
-0.0004
(13.07)
-0.0005
(2.19)
-0.0007
(3.04)
-0.0008
(2.99)
-0.0007
(2.92)
-0.0007
(3.6)
-0.0006
(3.37)
-0.005
(3.41)
-0.0005
(3.33)
-0.0004
(2.90)
+
+ <
a2 (abs (OMOt.1))
2502
(27.46)
328.9
(22.19)
364.3
(24.05)
253.6
(23.71)
371.04
(23.89)
268.-7
(26.47)
215.9
(24.7)
191.48
(24.79)
147.7
(20.03)
147.8
(20.5)
145.3
(22.03)
Locr L
ai
—2
0.66
-0.25
-5970.39
(13.2)
(5.76)
0.55
-0.0009 -4680.25
(12.50) (0.77)
0.16
-0.011
-4566.85
(5.30)
(1.60)
0.14
0.054
-4358.6
(4.47)
(0.75)
0.12
0.084
-4604.4
(4.18)
(1.08)
0.14
0.0003
-4382.6
(5.41)
(0.06)
0.205 -0.0003
-4269.1
(7.45)
(0.07)
0.19
-0.005
-4158.2
(5.83)
(1.52)
0.23
-0.004
-4013.1
(6.54)
(1.27)
0.13
-0.004
-3959.5
(4.60)
(1.65)
0.08
-0.006
-3909.6
(2.28)
(3.31)
Interest rates (rt) are in first differences.
The line in
parentheses under the coefficient values gives t-statistics
see tables I and III for additional notes.
TABLE VI
Open Market Operations and ARCH effects on Exchange Rate, Euro
Interest Rates and Stock Return variances.
Art
=
= a0
Variable Examined
1 mos Euro$
1 mos EuroDM
1 mos EuroJY
Spot DM
Spot JY
Equally Wtd.
Stock Ret.
Value Wtd.
Stock Ret.
+
bo
b°
-0.008
(0.97)
-0.005
(2.62)
-0.002
(0.54)
1.69
(1.23)
3.61
(3.22)
0.45
(1.85)
0.09
(5.06)
+
b 1OMOt.
-1
alet-l2
fei0.000009
(2.80)
0.000007
(8.41)
0.000002
(0.82)
-0.0004
(0.60)
-0.0002
(0.42)
0.00006
(0.56)
0.00001
(1.52)
+
+ et
a2(abs(OMOt.1))
a©—
0.14
(32.10)
0.009
(36.02)
0.03
(59.6)
2239.3
(18.1)
1403.7
(19.5)
79.25
(23.3)
0.39
(26.2)
Si-
a,
Locr L
0.95
(13.06)
1.16
(24.22)
0.87
(18.59)
0.20
(6.04)
0.16
(4.58)
0.07
(2.96)
0.32
(7.17)
-0.00001
282.64
(10.55)
-0.0000
1959.5
(0.41)
-0.000003 1323.3
(7.12)
-0.0004
-5744.0
(0.008)
0.074
-5473.6
(2.69)
-0.005
-3478.8
(3.78)
-0.00003
-132.2
(4.56)
Notes: Interest rates are in first differences exchange rates are
in log differences. The line in parentheses under the coefficient
values gives t-statistics.
See Tables I and III for additional notes.
Figure 1
EFFE C T O F D T O N DFF
Figure 2
E F F E C T
O F
D T
O N
D 0 3
Figure 3
E F F E C T
O F
D T
O N
D 2 4
Figure 4
E F F E C T
O F
D T
O N
D 2 4 0
Figure 5
EFFECT O F DFF ON DT
Figure 6
E F F E C T
O F
D 6 0
O N
D T
Figure 7
PLOT OF RESPONSES TO DT
o
2
Figure 8
PLOT OF RESPONSES TO DOS
@FedFRASER