Fan, J. and Zhu, Y. (2016) The impact of monetary policy regime
on gold price dynamics: Evidence from UK index-linked gilt market.
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The impact of monetary policy regime on gold price dynamics:
evidence from UK index-linked gilt market
Jingwen Fan
Yanhui Zhu
(Nottingham Trent University)
(University of West England)
March 2016
Abstract
After the collapse of Bretton-Woods system gold is still believed to be an important monetary commodity (Baur and Lucey (2010)) and provide in‡ation forecasting information content to monetary policy
makers (Tkacz (2007)). However, using a dataset spanning 30 years, Capie et al (2005) highlight the instability in gold price dynamics through time and attribute it to unpredictable political attitudes and events.
In this paper we attempt to investigate gold price dynamics under di¤erent monetary policy regimes using
data from UK index-linked Gilt markets. We show that gold lost the in‡ation hedge role after May 1997,
supporting the view that the Bank of England has been e¤ective in anchoring in‡ation expectations at a
low level after gaining independence. In addition, we show that gold lost the stock market hedge and safe
haven role after March 2009 indicating Quantitative Easing has changed the relationship between gold
and stock market profoundly.
Keywords: Gold price, Hedging, Bank of England independence, Quantitative Easing
JEL Classi…cation: E58, G1, G11, G12
1
Introduction
Recent and ongoing …nancial crisis presents a strong motivation for investors searching for safe haven assets.
Since the beginning of 2016, gold price has risen more than 10% and is considered as the best performing
asset for investor. The conventional wisdom says that gold price and general price level move together as a
Corresponding author: Dr. Yanhui Zhu, Frenchay Campus, Coldharbour Lane, BS16 1QY Bristol. Tel.: +44 (0)117 32
83943 ([email protected])
result gold has been a store of value in many cultures for millennia. Even after the collapse of Bretton-Woods
system gold is still used as currency in many countries (Worthington and Pahlavani, 2007). The literature
on gold indicates three main economic factors related to the demand for gold among which in‡ation is the
most heavily researched. Fisher (1930) establishes the fundamental relationship for studying interest rate
and expected in‡ation and suggests asset expected return rises as expected in‡ation rises. Empirical study on
gold prices and in‡ation has been widely carried out since the 1970s. Jastram (1978), extended by Jastram
and Leyland (2009) is the …rst attempt to empirically examine the long run relationship between price of gold
and in‡ation for England (1560-2007) and United States (1808-2007). Recent studies also support the view
that gold can serve as pro…table investment under extreme market conditions (see Baur and McDermott,
2010, Narayan et al 2013 and Narayan et al 2015).
In this paper we revisit the question of the usefulness of gold hedge roles for in‡ation, currency depreciation
and stock market ‡uctuation for United Kingdom for 1985-2015. Bordo and Schwartz (1994) argue that the
Bank of England could have powerful in‡uence on the money supplies and price levels of other countries in
the gold-standard era “because of the extensive outstanding sterling-denominated assets, and because many
countries used sterling as an international reserve currency (as a substitute for gold), it is argued that the
Bank of England, by manipulating its bank rate, could attract whatever gold it needed and, furthermore, that
other central banks would adjust their discount rates accordingly” (pp.8). Compared to existing studies our
paper provides two distinct features. First we test our hypotheses using market-implied in‡ation expectation
data. The data we use is actually what the recent literature names as break-even in‡ation rate (BEIR), which
is the sum of in‡ation expectation, in‡ation risk premium and liquidity premium. Liu et al (2015) argue
that BEIR has become increasingly used in central bank publications, market commentaries and research as
it provides more reliable indicator of in‡ation expectations (see Joyce et al (2010), Abrahams et al (2013)
and P‡ueger and Viceira (2013) for detailed discussion). Second, our test accounts for structural shifts in
UK monetary policy. There are two major events during the research period (1985-2015). On May 6th 1997
the Government gave the Bank of England responsibility for setting interest rates to meet the Government’s
stated in‡ation target. This marked the beginning of the Bank’s operational independence and its full
commitment to in‡ation targeting. We hypothesise that this change of regime impacts on gold’s role as an
in‡ation hedge. In particular, Bank of England’s operational independence is likely to stop gold price reacting
to in‡ation expectation. Once the market believes the BOE’s ability in anchoring in‡ation at a low and stable
level, any change in in‡ation expectation is more likely to be perceived as temporary and mean reverting.
Considering the transaction cost associated with buying and selling gold investors may …nd trading in gold is
2
not worthwhile, hence stopping treating gold as an in‡ation hedge. This reasoning is similar to Laurent (1994)
who argues that gold price only reacts to changes in deep-seated in‡ation expectations. If a central bank is
successful in removing the concern for deep-seated in‡ation fear, gold would lose its in‡ation hedge property.
Following this key event the next important monetary policy announcement was on March 5th 2009 when
the Bank of England announced it would purchase £ 75 billion of assets over three months funded by central
bank money. This marked the beginning of the unconventional monetary policy of Quantitative Easing.
There are a large number of literature on the Federal Reserve’s QE programme and the evidence of impact
on bond yields or risk premia was mixed (D’Amico and King (2010), Gagnon et al (2011), Krishnamurthy
and Vissing-Jorgenson (2011), Neely (2011) and Wright (2012)). There is also a good survey on Japanese
case (see Ugai (2007)). However less attentions have given to the UK’s QE programme particularly on its
impact on the …nancial market (see Meier (2009), Joyce et al (2010), Caglar et al (2011)). In particular,
Breedon et al (2012) argue as there is no generally accepted theoretical framework in which to assess QE
hence it is highly controversial both in terms of its e¤ectiveness and its implementation. Joyce et al (2010)
argue QE would cause interest rates to fall and asset prices to rise across classes (see also Krishnamurthy and
Vissing-Jorgensen, 2011). Therefore, we hypothesise that QE may lead gold to stop being a stock market
hedge and safe haven but move in the same direction as stock.
Our main …ndings can be summarised as follows: First, gold has been a good hedge against in‡ation,
currency depreciation and extreme stock market conditions over the period 1985-2015. Second, there are
two important shifts in UK monetary policy, with the …rst taking place in the 1997 (Bank of England
independence) and gold has lost the role of in‡ation hedge (for period 1997-2009). The UK also experienced
a signi…cant money injection in the early 2009 and gold was a safe haven in the pre-QE periods however
failed to rise when stocks su¤ered from big losses in the QE and after-QE period. Finally, our results show
gold has been a reliable currency hedge for investors for both whole period and sub-periods.
The rest of the paper is organised as follows: in section 2 we review the empirical literature on gold’s
hedging ability; in section 3 we discuss the data; section 4 presents the econometric model; section 5 presents
the empirical evidence. Section 6 concludes the paper.
2
Previous Literature
Generally speaking, people demand gold for two reasons. One is for consumption purpose for example use
gold for producing jewellery and coins. The other is for investment purpose where gold is used for hedging
against in‡ation, exchange rate and stock market ‡uctuation. Laurent (1994) argues that the stable relative
3
price of gold is the automatic price stabilisation mechanism of gold standard (see also Mill, 1987 and Barro,
1979). Under gold standard, a rise of the price level of goods relative to gold means a fall in the purchasing
power of gold. This would reduce the incentive to produce gold and divert some of the existing gold stock
from monetary use to consumption use such as jewellery, causing money supply to fall. The fall of money
supply would cause the price level of goods to fall until the relative price of gold rise to its long-term level.
Conversely, a fall of general price level relative to gold would stimulate gold producers to …nd and extract
new gold from ground at a greater cost, causing money supply and price level of goods to rise.
However, under the …at monetary system where the built-in stabilisation mechanism is no longer in place,
gold becomes a commodity just like others. Whether the price of gold relative to general price level remains
stable depends on di¤erent forces (Garner, 1995). A rise in in‡ation expectation may cause investors to shift
their funds from …nancial assets such as money and bond to gold. As the supply of gold is more or less …xed
in the short run, even a small rise in demand would cause gold price to rise sharply. Conversely, general
price level rises gradually because the price of many goods and services only adjust slowly. As a result the
rise in gold price might precede a rise in general price level provided the in‡ation expectation is correct. In
other words, not only the relative price of gold should still be stable in the long run but also the price of gold
should be a leading indicator of in‡ation.
The empirical evidence is generally supportive of the idea that the nominal price of gold and the general
price level move together in the long run. Using the price of gold and the wholesale price index of US
Herbst (1983) and Laurent (1994) show that the former corresponds to the latter quite closely in the last
two centuries even though the price of gold is pegged for substantial sub periods and the wholesale price
increases dramatically. Using the data after the collapse of Bretton Woods system Beckmann and Czudaj
(2013) …nd that the price of gold and the general price level are cointegrated in US, UK, Japan and Euro
area, indicating that a long-term stable linear relationship exists in these major economic areas for the last
four decades. Worthington and Pahlavani (2007) also provide evidence for cointegration in the US after
allowing for endogenous structural breaks in the post-war period. Using threshold cointegration technique
Wang et al (2011) show that the price of gold and general price level in the US are characterised by a linear
cointegration relationship while that of Japan a nonlinear relationship.
However the empirical evidence on the relationship between in‡ation and gold return in the short run is
rather inconclusive. Using the regression method Chua and Woodward (1982) show that actual, expected
and unexpected in‡ation are signi…cant explanatory factors for US gold return between 1975 and 1980 but
are not for Canada,Germany, Japan, Switzerland and UK. Ja¤e (1989) …nds that in the US between 1971
4
and 1987 gold return is signi…cantly related to actual but not expected in‡ation. Laurent (1994) and Garner
(1995) …nd lagged gold returns can explain in‡ation rate but its predictive power is inferior to past in‡ation
rate, general commodity price index and variables that measure economic slack. Mahdavi and Zhou (1997)
employ an out-of-sample forecast method and …nd the model with gold return as a predictor performs the
worst. Cecchetti et al. (2000) use a similar method and …nd gold could improve forecast accuracy but the
result that an increase of gold price precedes future declines in in‡ation seems to be illogical and prevents
them from putting much stock in gold as a predictor of in‡ation. Using the intraday price of gold futures
Cai et al (2001) and Christie-David et al (2000) …nd that the monthly release of in‡ation data increases the
volatility of gold futures. However, using the daily data on the announcement day of the rate of in‡ation
Blose (2010) shows the in‡ation surprise has no impact on the gold return in the US between 1988 and
2008. Erb and Harvey (2013) …nd little evidence that gold has been an e¤ective hedge against unexpected
in‡ation. However, Tkacz (2007) …nds the return on gold predicts in‡ation over12-18 month horizon in most
developed countries with formal in‡ation targeting between 1995 and 2004. He argues that in those countries
the in‡ation expectation is more accurate hence gold’s return is more likely to predict in‡ation accurately
(see also Mahdavi and Zhou (1997)) .
For gold’s role as currency hedge, Sjaastad and Scacciavillani (1996) argue that an appreciation of local
currency could cause the price of gold in that currency to fall. Capie et al. (2005) provide evidence for this
negative relationship between gold price in US Dollars and the value of US Dollar against Japanese Yen and
Pound Sterling between 1971 and 2004. But this relationship varies over time and is much weaker before
1976 and after 1985. Pukthuanthong and Roll (2011) con…rm the negative conditional relationship between
a currency and the gold price denominated in that currency for Yen, Euro and Pound. Using copulas to
examine the role of gold as a safe haven or hedge against the US dollar Reboredo (2013) reveal positive
and signi…cant average dependence and symmetric tail dependence between gold and USD exchange rates,
indicating that gold can act as a hedge and a safe haven against USD movements. Using quantile regressions,
Ciner et al (2013) show that gold can be regarded as a safe haven against exchange rates in US and UK.
Another widely-held belief about gold is that gold is a stock and bond market hedge in normal market
conditions and a safe haven in abnormal times, therefore providing diversi…cation bene…t to portfolio holders.
Hillier et al (2006) show that gold has a small negative beta in normal period and a more negative beta in
volatile market conditions in the US. Baur and McDermott (2010) conduct an extensive study using the data
of di¤erent frequencies over 30 years for 13 countries. They …nd that gold is a hedge and a safe haven for
stock investors in major developed countries. Using wavelet analysis, Bredin et al (2015) …nd that gold acts
5
as a hedge for a variety of international equity and debt markets for horizons of up to one year and gold acts
as a safe haven for equity investors for long-run horizons of up to one year around 1987 “Black Monday”
crash and the global …nancial crisis. However, using a sample of 13 sovereign bonds Agyei-Ampomah et al
(2014) show that other precious metals and industrial metals tend to outperform gold as hedging vehicles
and safe haven assets against losses in sovereign bonds.
3
Data
For the econometric investigation on gold price dynamics we use data for in‡ation expectation, exchange
rate and stock market return as explanatory variables. For gold, we use London PM …xing price in Sterling
Pound. For in‡ation expectation, we use implied in‡ation expectation calculated by Bank of England using
the data on index-linked Gilts and conventional Gilts. Ex-ante 10-year and 5-year in‡ation expectations and
real interest rates are estimate using a spline-based technique method (Anderson and Maule, 2014). For
exchange rate, we use US Dollar per UK Pound. And for stock market, we use FTSE 100 stock index. All
data except FTSE 100 index is collected from Bank of England’s website. The FTSE 100 index data is
collected from DataStream. Our data consists of daily observations and covers the period between Jan 02nd,
1985 and March 19th, 2015. Table (1) reports the descriptive statistics. Data for Gold, $/£ and FTSE 100
are all in log di¤erence formats. Inf Exp 10 and Inf Exp 5 are calculated by taking the di¤erences.
FTSE 100 has higher average return than gold and it is more volatile. Sterling Pound appreciates against
US Dollar in this period. The returns are all insigni…cantly di¤erent from zero and exhibit fat tails. On
average UK’s 10-year in‡ation expectation has gone down by 0.06 basis points per day in the period. This is
not surprising as the sample starts from January 1985 when in‡ation expectation is 7.44% and ends in March
2015 when in‡ation expectation is 2.69%. The daily changes in in‡ation expectations are insigni…cantly
di¤erent from zero.
Gold
$/£
FTSE 100
Inf Exp 10
Inf Exp 5
Mean (%) Std.Dev (%) Maximum (%) Minimum (%)
0.014
1.032
6.676
-9.624
0.003
0.622
4.644
-3.960
0.023
1.112
9.384
-13.029
-0.001
0.475
0.423
-0.513
-0.001
0.564
0.466
-0.690
Skew
-0.218
0.030
-0.495
-0.199
-0.362
Kurtosis Observations
9.025
7628
7.296
7628
12.704
7628
10.992
7628
15.567
7628
Table 1: Descriptive Statistics
N otes on T able: $/£ exchange rate is the exchange rate and gold is presented in £ . Inf Exp 10 and Inf Exp 5
denote the daily change in the 10-year and 5-year in‡ation expectation respectively.
6
4
Econometric model on gold price dynamics
The baseline model is described by equations (1) and (2) below
rGold;t =
0
+
1
e
p;t
+
ht =
0
2 r$;t
+
3 rF T SE;t
+
(ut ) +
2
1
+
4 rF T SE(q);t
+ ut
2 ht 1
Note that rGold;t is the return of gold price in £ in period t,
(1)
(2)
e
p;t
is the change in p-year UK in‡ation
expectation in period t (where p = 5 or 10), r$;t is the rate of change of £ against dollar in period t, rF T SE;t
is the return of UK stock market measured by FTSE 100 index in period t and ut is the error term. Following
Baur and Lucey (2010), we use rF T SE(q);t (q = 1% or 5%) to account for the extreme negative shocks to
the stock market. If the stock return is in the q lower quantile, rF T SE(q);t equals stock return, otherwise, it
equals zero. In other words, it is a multiplicative dummy variable de…ned by the extreme negative shock of
stock market. Similar to Baur and Lucey (2010) and Baur and McDermott (2010), we use it to test whether
gold is a hedge or a safe haven asset for stock market investors. The error term, ut , is assumed to follow a
GARCH (1, 1) process with a time varying variance, ht . The GARCH (1, 1) process is used to control for
heteroskedasticity in the data which is common in daily …nancial data. If
hedge as gold price increases with in‡ation expectation. If
priced in £ decreases when £ appreciates. Finally, if
3+ 4
5
3
2
1
is positive, gold is an in‡ation
is negative, gold is a currency hedge as gold
is zero or negative, gold is a hedge for stock and if
is zero or negative, gold is a safe haven asset.
Estimation Results
The empirical evidences are presented in Table (2). The result in column (1) shows a positive relationship
between the return on gold and movements in the in‡ation expectation. On average, a 1 percent movement in
10-year in‡ation expectation is associated with a 1.031 percent change in the price of gold. Also as expected,
there is a negative relationship between the return on gold and movements in £ exchange rate. On average,
a 1 percent appreciation of £ against $ is associated with a 0.599 percent fall in the price of gold. There
is no signi…cant relationship between the return on gold and that of stock, suggesting gold is a good stock
market hedge. The signi…cance of the F test statistics of the hypothesis
7
3
+
4
= 0 indicates gold is the
safe haven asset for investors. Column (2) present the results where 5-year in‡ation expectation is used and
results are very similar to those presented in column (1). Columns (3) and (4) present the results with 5%
lower quantile for a robustness check. Overall, our results o¤er evidence for gold’s role as an in‡ation hedge,
currency hedge and stock market hedge and a safe haven.
Estimated Equations
rGold;t =
0+ 1
(1)
e
p;t + 2 r$;t + 3 rF T SE;t + 4 rF T SE(q);t +ut
2
ht = 0 + 1 (ut ) + 2 ht 1
(2)
(3)
q = 1%
p = 10
-0.001(0.009)
1.031(0.144)***
1
-0.599(0.012)***
2
0.006(0.009)
3
-0.076(0.010)***
4
0.009(0.001)***
0
0.079(0.002)***
1
0.916(0.003)***
2
Durbin-Watson statistic
2.063
Q(10)
8.859
2
Q(10)
9.985
F-Wald test, H0 : 3 + 4 = 0
136.003***
S.E.of regression
0.979
0
(4)
q = 5%
p=5
p = 10
p=5
-0.002(0.009)
0.662(0.130)***
-0.603(0.012)***
0.003(0.009)
-0.075(0.010)***
0.009(0.001)***
0.079(0.002)***
0.916(0.003)***
2.063
9.173
9.976
140.912***
0.980
-0.001(0.009)
0.983(0.145)***
-0.600(0.012)***
-0.002(0.010)
-0.025(0.0123)***
0.009(0.001)***
0.079(0.002)***
0.917(0.003)***
2.065
8.629
10.141
14.700***
0.980
-0.001(0.009)
0.610(0.131)***
-0.604(0.012)***
-0.006(0.010)
-0.023(0.012)
0.009(0.001)***
0.079(0.002)***
0.916(0.003)***
2.067
8.949
10.100
16.491***
0.981
Table 2: Whole sample results
N otes on T able: standard errors in parentheses. *** indicates signi…cance at 1%. q is the extreme stock market
2
dummy and p = 10 and p = 5 denote 10-year and 5-year in‡ation expectation respectively. Q(10) and Q(10) are
test statistics for autocorrelation.
In order to gain insights on whether the monetary policy regime impacts on the gold properties, we divide
our sample period into three sub-periods and repeat the estimation - January 2nd 1985 to May 5th 1997,
May 6th 1997 to March 4th 2009 and March 5th 2009 to March 19th 2015. The …ndings for p = 10 and
q = 1% are reported in Table (3). Detailed test results can be found in Appendix A.
Column (1) presents the estimation results using the data before BOE independence. Similar to the
pervious estimation, the coe¢ cient for in‡ation expectation is positive and highly signi…cant, indicating
that gold was treated as an in‡ation hedge. In particular, the return on gold rises with 10-year in‡ation
expectation. However, this positive and signi…cant relationship disappeared in the second sub-sample, as
shown in column (2). Gold stopped reacting to changes in in‡ation expectation, indicating it was losing
8
the role as in‡ation hedge. This can be viewed as evidence for the success of BOE’s in‡ation targeting.
After gaining independence, BOE managed to convince the market that long-term in‡ation rate was going
to be stable and low, removing the incentives to buy or sell gold in the short term. Column (3) presents the
puzzling result that gold return is negative when in‡ation expectation rises in the QE period. This could be
caused by the poor quality of implied in‡ation expectation data around the crisis period due to the sharp
increase in liquidity premium in the yields of index-linked gilts (D’Amico et al, 2014).
The estimates for currency coe¢ cient are similar across sub-periods and they are all negative and highly
signi…cant. This indicates that gold has been a reliable currency hedge for UK investors in the last 30 years.
However both the level of signi…cance and the absolute value of the coe¢ cient have declined over years.
The estimates for stock market hedge coe¢ cient exhibit signi…cant changes across sub-periods. Before
the QE period, the coe¢ cient
3
is either signi…cantly negative or insigni…cantly positive, indicating gold
is a stock market hedge in normal time. During the QE period, however, it becomes positive and highly
signi…cant, suggesting that gold tended to move in the same direction as the stock market and lost its stock
market hedge property. Moreover, the test statistics for the hypothesis
3
+
4
= 0 are highly signi…cant
in the pre-QE periods, indicating that gold was a safe haven asset for stock investors. But the F statistics
is not signi…cant in the QE period, indicating gold price failed to rise when stocks su¤ered from big losses.
While the results for pre-QE periods are consistent with those in Baur and Lucy (2010), the results in QE
period raise an interesting question. It seems that QE not only caused interest rates to fall and asset prices
to rise in general but also changed the long-term relationship between gold and stock.
9
Estimated Equations
rGold;t =
0+ 1
p = 10
q = 1%
(1)
03.01.85-05.05.97
-0.011(0.012)
0
0.856(0.171)***
1
-0.779(0.014)***
2
-0.041(0.014)***
3
-0.015(0.016)
4
0.003(0.001)***
0
0.073(0.004)***
1
0.927(0.004)***
2
Durbin-Watson statistic
2.157
Q(10)
12.537
2
Q(10)
5.403
F-Wald test, H0 : 3 + 4 = 0
64.126***
S.E.of regression
0.818
e
p;t + 2 r$;t + 3 rF T SE;t + 4 rF T SE(q);t +ut
2
ht = 0 + 1 (ut ) + 2 ht 1
(2)
06.05.97-04.03.09
0.010(0.016)
0.297(0.390)
-0.336(0.025)***
0.021(0.013)
-0.109(0.201)***
0.025(0.003)***
0.097(0.006)***
0.883(0.007)***
2.014
9.871
11.996
29.249***
1.052
(3)
05.03.09-19.03.15
0.028(0.026)
-2.145(0.641)***
-0.267(0.045)***
0.115(0.025)***
-0.106(0.073)
0.041(0.007)***
0.077(0.007)***
0.889(0.009)***
2.025
10.457
4.917
0.016
1.084
Table 3: Subsample results
N otes on T able: standard errors in parentheses. *** indicates signi…cance at 1%. q is the extreme stock market
2
dummy and p = 10 denotes 10-year in‡ation expectation. Q(10) and Q(10) are test statistics for autocorrelation.
6
Conclusion
This paper tests the hypotheses that gold acts as in‡ation hedge, currency hedge, stock market diversi…er
and stock market safe haven for United Kingdom over the period 1985-2015. Overall our …ndings con…rm its
suitability as a good hedge investment over whole period but results are di¤erent for sub periods. Before BOE
independence (1985-1997) the coe¢ cient for in‡ation expectation is positive and highly signi…cant, indicating
that gold was a good in‡ation hedge. However, this positive and signi…cant relationship disappeared during
1997-2009 and gold stopped reacting to changes in in‡ation expectation. This evidences that BOE’s success
in in‡ation targeting. Gold was a safe haven asset in the pre-QE period however failed to rise when stocks
su¤ered from big losses. Fortunately, for investors seek for eliminating currency risk gold can be a good hedge
investment.
10
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13
AppendixA
Sub-period estimation results
AppendixA.1
For p = 5 and q = 1%
Estimated Equations
rGold;t =
0+ 1
p=5
q = 1%
(1)
03.01.85-05.05.97
-0.011(0.012)
0
0.461(0.150)***
1
-0.786(0.014)***
2
-0.051(0.014)***
3
-0.007(0.016)
4
0.004(0.001)***
0
0.073(0.004)***
1
0.927(0.004)***
2
Durbin-Watson statistic
2.159
Q(10)
12.924
2
Q(10)
5.246
F-Wald test, H0 : 3 + 4 = 0
68.950***
S.E.of regression
0.820
e
p;t + 2 r$;t + 3 rF T SE;t + 4 rF T SE(q);t +ut
2
ht = 0 + 1 (ut ) + 2 ht 1
(2)
06.05.97-04.03.09
0.010(0.016)
0.271(0.325)
-0.337(0.025)***
0.021(0.013)
-0.109(0.021)***
0.025(0.003)***
0.097(0.006)***
0.883(0.007)***
2.014
9.812
11.906
29.603***
1.051
(3)
05.03.09-19.03.15
0.029(0.025)
-1.847(0.588)***
-0.269(0.044)***
0.112(0.025)***
-0.109(0.073)
0.040(0.007)***
0.076(0.007)***
0.890(0.009)***
2.022
10.863
4.504
0.002
1.085
Table 4: Subsample results
N otes on T able: standard errors in parentheses. *** indicates signi…cance at 1%. q is the extreme stock market
2
dummy and p = 5 denotes 5-year in‡ation expectation. Q(10) and Q(10) are test statistics for autocorrelation.
14
AppendixA.2
For p = 10 and q = 5%
Estimated Equations
rGold;t =
0+ 1
p = 10
q = 5%
(1)
03.01.85-05.05.97
-0.013(0.012)
0
0.904(0.169)***
1
-0.777(0.014)***
2
-0.027(0.015)*
3
-0.045(0.017)***
4
0.004(0.001)***
0
0.073(0.004)***
1
0.927(0.004)***
2
Durbin-Watson statistic
2.156
Q(10)
12.270
2
Q(10)
5.388
F-Wald test, H0 : 3 + 4 = 0
128.358***
S.E.of regression
0.818
e
p;t + 2 r$;t + 3 rF T SE;t + 4 rF T SE(q);t +ut
2
ht = 0 + 1 (ut ) + 2 ht 1
(2)
06.05.97-04.03.09
0.023(0.016)
0.249(0.389)
-0.342(0.015)***
-0.009(0.015)
0.046(0.022)**
0.030(0.003)***
0.109(0.007)***
0.866(0.008)***
2.027
8.822
9.248
6.236**
1.054
(3)
05.03.09-19.03.15
0.030(0.027)
-2.142(0.638***)
-0.269(0.045)***
0.110(0.031)***
0.002(0.045)
0.041(0.007)
0.077(0.007)
0.890(0.009)
2.023
10.262
5.048
10.399***
1.085
Table 5: Subsample results
N otes on T able: standard errors in parentheses. *** indicates signi…cance at 1%. q is the extreme stock market
2
dummy and p = 10 denotes 10-year in‡ation expectation. Q(10) and Q(10) are test statistics for autocorrelation.
15
AppendixA.3
For p = 5 and q = 5%
Estimated Equations
rGold;t =
0+ 1
p=5
q = 5%
(1)
03.01.85-05.05.97
-0.013(0.012)
0
0.511(0.148)***
1
-0.784(0.014)***
2
-0.037(0.015)**
3
-0.0.039(0.017)**
4
0.004(0.001)***
0
0.074(0.004)***
1
0.926(0.004)***
2
Durbin-Watson statistic
2.158
Q(10)
12.631
2
Q(10)
5.263
F-Wald test, H0 : 3 + 4 = 0
141.164***
S.E.of regression
0.820
e
p;t + 2 r$;t + 3 rF T SE;t + 4 rF T SE(q);t +ut
2
ht = 0 + 1 (ut ) + 2 ht 1
(2)
06.05.97-04.03.09
0.022(0.016)
0.201(0.323)
-0.343(0.025)***
-0.008(0.015)
0.045(0.022)**
0.030(0.003)***
0.109(0.007)***
0.866(0.008)***
2.027
8.786
9.196
6.116**
1.054
(3)
05.03.09-19.03.15
0.031(0.027)
-1.840(0.588)***
-0.271(0.045)***
0.108(0.031)***
0.001(0.045)
0.040(0.007)***
0.076(0.007)***
0.891(0.009)***
2.019
10.672
4.630
9.782***
1.086
Table 6: Subsample results
N otes on T able: standard errors in parentheses. *** indicates signi…cance at 1%. q is the extreme stock market
2
dummy and p = 5 denotes 5-year in‡ation expectation. Q(10) and Q(10) are test statistics for autocorrelation.
16