does gold love bad news? hedging and safe haven of gold ......gold has many advantages over...

Does Gold Love Bad News?

Hedging and Safe Haven of Gold against Stocks and Bonds

Samar Ashour* University of Texas at Arlington

[email protected] (682) 521-7675

September 16, 2013

*Corresponding author: Samar Ashour, doctoral student, University of Texas at Arlington, Box 19449, Department of Finance and Real Estate, Arlington, Texas 76019.

1

Does Gold Love Bad News?

Hedging and Safe Haven of Gold Against stocks and Bonds

SAMAR ASHOUR

ABSTRACT

This paper examines the contemporaneous and dynamic relation between gold excess returns and the stocks and corporate bonds excess returns. The results show that gold can be used as a hedge and safe haven against bonds and stocks. This paper is the first to use CAPM and Fama French three factor models to check the relation between gold market and the stock market as well as corporate bond market. Over the entire sample period from 1986 to 2012, there is a significant relation between gold excess returns and market excess returns as well as the corporate bonds excess returns even after controlling for Fama French three risk factors. Additionally, during extreme market conditions such as crashes and crises, there is a negative relation between stock returns and gold returns in crashes times and there is a zero correlation between stock and bonds returns and gold returns in crises times, and consequently gold can be used as a hedge against stocks and bonds in the tension times. The dynamic relation between three markets using VAR and IRF indicates that gold can be used as a safe haven against stocks and bonds.

I. Introduction

Gold is a well-known as a precious metal and store of value for hundreds of decades.

Gold is still the most famous precious metal for investment purposes, since many people transfer

their investments from the stock and corporate bonds to mitigate their losses in these risky

markets during the recession periods especially during crashes and crises. Gold trading and

prices setting are similar to stock trading.

The purpose of this study is to investigate the role of gold as a safe haven or hedge

against losses in financial markets through the equity market and corporate bond market by using

recent data and by applying CAPM and Fama French three factor models to examine the static

relation between stocks returns and gold returns, and using vector autoregressive model (VAR)

and impulse response function (IRF) to investigate the dynamic relation between the three

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markets. In particular, I examine the inter-relationships between three different markets – gold

market, stock market, and bond market over the period from 1986 to 2012 and during the bad

states of the economy and extreme market performance especially in financial crashes such as

1987 Stock Market crash (Black Monday), September eleven crash in 2001, as well as the most

recent crises (Asian crisis 1997-1998 and the global housing crisis (2007-2009). The contribution

of this study is twofold. First, unlike Baur and Lucey (2010) that examine the relation between

three markets using GARCH and using data from 1995 to 2006 and find that gold cannot be

hedge against bonds, I used more recent and comprehensive data and the most important asset

pricing models (CAPM and Fama French three factor models) and I find a significant negative

relation between bonds and gold. Second, unlike the existing literature that examines either the

relation between gold prices and stock prices (e.g., Baur and Lucey, 2010, and Baur and

McDermott, 2011) or between gold prices and exchange rates (e.g., Capie, Mills and Wood,

2005), or even investigate the riskiness of the gold (McCown et.al., 2006), this study attempts to

link many streams of literature by examining the co-movements between the gold returns, stock

returns, and bond yields using different models. Third, this article is the first attempt to use

CAPM and Fama French three factor models to know the static relation between gold, stocks,

and bonds. Moreover, this is the first study to vector autoregressive model (VAR) and impulse

response function (IRF) to examine the market interdependencies and the dynamic relation

between the three classes of assets during bad states of the economy whether in financial crashes

or financial crises. A relatively little research has been done in this area. My argument is that the

dependence structure between the three markets is not constant and it may be different between

normal and calm periods. Most investors realized great losses especially in the last financial

crisis because of the significant drop in the stock prices and the experienced substantial losses

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due to this phenomenon. This paper tries to provide a suggestion for investors to include gold in

their investment portfolios especially if gold commove against both stocks and bonds. I find that

the negative relation between stocks and gold is stronger and more economically and statistically

significant than the negative relation between bonds and gold. To verify that these results are not

spurious, I used different models to control for Fama French three factor models; SMB which is

the difference between returns on the small firms and the returns on the large firms, HML the

difference between the high book to market returns and low book to market returns.

Additionally, to know the dynamic relation between three markets, I used the lagged returns of

the three markets and run vector autoregressive regression to make sure that the results are not

spurious due to autocorrelation or the endogenity problem and to get the linkage between three

markets assuming every time that each of them is dependent variables and it is lagged variable as

well as the other two markets in their lagged forms are explanatory variables to this market

return. There is an important study in this area by Baur and McDermott (2011) but they restrict

this study to gold and stocks but my paper will investigate the interrelationship between these

three variables. Moreover Baur and Lucy (2010) use index returns data only to represent stocks

and they did not control for any variables and they did not use subsamples to check the

robustness of the safe haven finding. However, my study uses a novel data set in this area of

literature. My study is distinguished by using the value weighted portfolio of all NYSE,

NASDAQ, and AMEX from CRSP as well as using S&P 500 from CRSP after comparing it with

FRED to correct for missing observation. Additionally, Baur and Lucy (2006) uses MSCI bond

index, but I used both AAA bonds and BAA bonds from Moody’s service by using FRED

website. The results provide convincing evidence that gold can be used as a hedge and safe

haven against stocks and bonds.

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II. Literature Review

Gold has many advantages over investment in stocks and bonds or even foreign exchange

rate. Gold is a tangible good, so that when the investor purchases gold yields an object of

tangible value. First, from the consumption side, the gold investor not only purchases gold for

hedging, but also the investor benefits from using it as jewelry so that the utility of gold is higher

because it is considered consumption good . Second, from the production side the producer can

hold gold inventory to hedge himself form the stock out risk. Third, the gold is very liquid

especially in tension times so that the investor can pay higher prices and realizes lower returns

compared to other risky assets However, people flight to less risky investments during bad states

of economy, and consequently, the price of gold after 2009 is substantially increase. This fact

against the famous investment rule: “buy low, sell high”. This striking high prices lead to an

expectation that it will continue to rise forever, but according to the past gold history, this is not

always the scenario.(Davision, 2013)

My work is related to two strands of literature. One stream focuses on examining the gold

prices, Fama and French (1988) study the relation of metal pricing with business cycles and they

find that positive demand chocks during peak periods lower the metal inventories and causes

severe price conversions according to the theory of storage, while the other strand investigates

the relationship between gold prices and stock prices. Baur and Lucey (2010) investigate whether

gold can serve as a safe haven and hedge against stock and/or bonds during bad times. The

results show that there is a flight to quality from stocks to gold during periods of tension, but not

from bonds to gold. Baur and McDermott (2010) provide international evidence to the role of

gold as a hedge and a safe haven against stock prices. In particular, they run multi-country

analysis using data from 53 international stock markets (which include developed and

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developing markets) from March 1997 to March 2009. Alternatively, Capie, Mills, and Wood

(2005) provide evidence on the role of gold as an exchange rate hedge, and they find that there is

a negative relation between gold prices and Sterling-Dollar and Yen-Dollar exchange rates.

This paper is related to the flight-to-quality literature. Gulko (2002) examines whether

the investors transfer their investments from stocks to bonds in the extreme market conditions

(Gonzalo and Olmo (2005)) stated that investors flight to quality (from stocks to bonds). from

the above discussion, it is clear that there is one strand of literature that finds that Gold is a stock

market hedge, while the other stream provides evidence that Gold is not hedge against corporate

bonds. Given the scarcity of literature on the role of gold as a hedging tool in the financial

markets in general, the contribution of this stems from linking the above two strands of literature

by examining the relation between gold prices, bond prices, and stock prices over the entire

sample period and during the bad states of the economy whether in recessionary and the financial

crises sub periods.

Barro and Misra (2013) find that there is a statistically insignificant covariance of change

in the gold’s real rate with consumption and GDP growth rate and they document that the

predicted returns on gold is very close to the risk free rate. Jaffe (1989) justifies why that the

gold return is lower than stocks and bonds by referring to its non-pecuniary benefits. The gold

investor not only purchase gold for hedging but also the investor benefits from using it as jewelry

so that the utility of gold is higher because it is considered consumption good. Moreover, from

the production side the producer can hold gold inventory to hedge himself form the stock out

risk. Finally, the gold is very liquid especially in tension time so that the investor can pay higher

prices and realizes lower returns compared to other risky assets. McCown (2006) study the

degree of the riskiness of gold by using CAPM model and Arbitrage pricing model and find that

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the gold has a great hedging ability because it has very similar expected return of Treasury bill.

They provide convincing evidence that gold is “zero beta asset” and gold have no market risk.

However, my paper tries to provide convincing evidence that gold has negative beta (i.e.,

comovements against market portfolio) and to extend this to see the relation between gold

market, stock market portfolio and corporate bond market after taking into account all Fama

French three risk factors.

III. Methodology

1. Hedging Hypothesis:

My first hypothesis, therefore, is that gold may be used as a hedge instrument against

stocks and bonds if there is a zero or negative relation between gold returns and stocks and bonds

returns during the entire sample period from 1986 to 2011. According to Baur and Lucey (2010),

gold can be considered as a hedge against bond and stocks when there is a zero or negative

relation between gold and bonds and/or stocks on average during periods of calm and tensions.

1.1.CAPM

Since I am interested in the response of gold prices to fluctuations in stock returns, I run

the following CAPM regression:

( ) )1(,,10,, tftStocktftgold RRRR −+=− ββ

Where )( ,tgoldR the daily return on gold prices is, )( ,& tPSR is the daily return on S&P index, and

)( ,tfR is the risk-free rate. In order to examine the interrelations between bonds, stock and gold

markets, I incorporate the daily gold return )( ,tbondR to the above CAPM equation, as follows:

( ) ( ) )2(,2,,1,, ftbondtftStocktftgold RRRRRR −+−+=− ββα

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Equation (2) is the central because it examines the contemporaneous relationship between gold,

stocks, and bond in one equation so that as a robustness, I used many measurement for market

excess returns. I used S&P500, Value weighted returns without excluding dividends which is the

same as market excess return from Fama French Library VWR , value weighted returns

including dividends VWRD, equal weighted returns EWR and equal weighted returns including

dividends EWRD. In empirical result section, I will start by displaying the results of this

equation, and then I will present the results of CAPM and Fama French models.

1.2 Fama French Model:

In order to account for the size and value premium, I regress the return on gold on the

three Fama-French factors, as follows:

( ) ( ) ( ) )3(32,,1,, tttftStockjtftgold SMBHMLRRRR βββα ++−+=−

In addition, I also incorporate the bond returns to equation (3), as follows:

Rgold,t − Rf ,t =α +β1 RStock,t( )+β2 HMLt( ) +β3 SMBt( )+β4 Rbond,t( ) (4)

1.2. Vector Autoregression Model (VAR)

The VAR system treats all of the variables in the model as endogenous variables.

Therefore, the dynamic relation between gold market, stock market, and bond market can be

examined by estimating the following three-vector autoregressive (VAR) system:

Rgold,t − Rf ,t =λ0 + αi Rgold,t−1 − Rf ,ti=1

I

∑ + β j RStock,t− j − Rf ,t + ηkRbond,t−k − Rf ,t +k=1

K

∑ εi,t j=1

J

∑ (5)

)6( 1

,1

,,,,,1

1,0,, ∑ ∑∑= =

−−=

− +−+−+−+=−J

jti

K

ktfktbondktfjtgoldjtf

I

itStockitftStock RRRRRRRR εηβαλ

8

)7( 1

,1

,,,,1

,1,0,, ∑ ∑∑= =

−−=

− +−+−+−+=−J

jti

K

ktfktStockktfjtgoldj

I

itftbonditftbond RRRRRRRR εηβαα

1.3. Impulse Response Function (IRF)

The problem with the variance-covariance estimated from the VAR model is that errors

are unlikely to be diagonal. This means that it is difficult to shock one variable while holding

other variables constant. Therefore, I use the impulse response function (IRF) to measure the

response of gold returns to a lagged unit impulse in stock returns, while the bond returns

constant. Conversely, I focus on examining the impact of the impulse bond returns on gold

returns, while holding the S&P index returns constant.

2. Safe Haven Hypothesis:

My second hypothesis is that there should be flight to quality from corporate bonds and

stock market to gold during extreme market conditions. In other words, the safe haven

hypothesis states that US investors in the stock market and bond market view the gold as a hedge

and safe haven to compensate them for losses during stock market crashes. Gold can be

considered as a safe haven rather than hedge against stocks and bonds if there is a zero or

negative relation between gold returns and bonds and stocks during the tension times only. In

order to examine the safe haven hypothesis, I estimate the following regression models:

( ) )7(,_10,_ tfTensiontStocktfTensiontgold RRRR −+=− ββ

( ) ( ) )8(,,_2,,_10,,_ tftTensionbondtftTensionStocktftTensiongold RRRRRR −+−+=− ααα

( ) ( )( ) )9(_

_

3

2,_,1,_

t

t

Tension

TensiontfTensionttStocktfTensiontgold

SMB

HMLRRRR

β

ββα

+

+−+=−

( ) ( )( ) ( ) )10( _4_3

2,_1,,

fTensiontbondTension

TensiontfTensionStocktftgold

RRSMB

HMLRRRR

t

t

−++

+−+=−

ββ

ββα

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I will also used the VAR and IRF to test the second Hypothesis as follows:

)11( 1

,1

,,_,,_1

,1_0,,_ ∑ ∑∑= =

−−=

− +−+−+−+=−J

jti

K

ktfktTensionbondktfjtTensionStockj

I

itfTensiontgolditftTensiongold RRRRRRRR εηβαλ

)12(1

,1

,_,_,1

1_0,_ ∑ ∑∑= =

−−=

− +−+−+−+=−J

jti

K

ktfkTensiontbondktfjTensiontgoldjtf

I

iTensiontStockitfTensiontStock RRRRRRRR εηβαλ

)13( 1

,1

,_,_1

,1_0,_ ∑ ∑∑= =

−−=

− +−+−+−+=−J

jti

K

ktfkTensiontStockktfjTensiontgoldj

I

itfTensiontbonditfTensiontbond RRRRRRRR εηβαα

Where )( ,_ tTensiongoldR , )( ,_ tTensionStockR , and )( ,_ tTensionbondR are interaction variables of returns and

dummy variable (Tension) that takes value of 1 during the tension time and zero otherwise.

These interaction variables represent daily return on gold, Market index, and bonds during the

crisis period respectively.

IV. Data and Variable Measurement

My sample period is extended from April, 1, 1986 till October 31, 2012. The sample

period will be divided further into different subsamples to cover the periods of four extreme

market conditions (October 1987 Crash, Asian Crisis 1997-1998, September eleven 2001 crash,

and the recent housing crisis 2007-2009). This study uses daily price data from three different

markets - gold, stock and corporate bonds. The gold prices are the gold fixing price 3:0 P.M.

(London time) in London Bullion Market, based on U.S. dollars obtained from London Bullion

Market Association through FRED. Gold prices are expressed in U.S. dollars per troy ounce

from April 3rd, 1986 to December 31st, 2012. I use the log daily returns of the value-weighted

(VWRt) and equal-weighted (EWRt) portfolios obtained from CRSP. The log interest rate

(TBLt) is computed from the one-month Treasury bill which is also obtained from CRSP.

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Additionally, I obtain the daily data of Corporate Aaa and Baa bonds yields in a percentage form

from the Board of Governors of the Federal Reserve System, which is originated in Moody’s

investor service that includes bonds with remaining maturities as close as possible to 30 years

and drops the bonds if the remaining life falls between 20 years, if the bond is susceptible to

redemption or if the ratings change. Baur uses GARCH to estimate the volatility of stocks

included in his sample. This study also calculates the conditional volatility of gold and stocks

using GARCH (1, 1). I use the excess log daily returns of gold, stocks and bonds. The market

excess returns, the Fama French three risk factors, and the returns on the one month Treasury bill

are obtained from Kenneth French website.

In order to test the safe haven hypothesis, I need to focus on periods of bad states of

economy, specifically speaking, during stock market crashes which are the Black Monday crash

in 1987, Asian crises in 1997, the September 11, 2001 attack, and the recent Housing crisis in

2007. Table (1) presents the starting date for each market crash or financial crisis.

Table (1): Market Crashes and Crisis Periods

V. Empirical Results

1. Preliminary Results:

Figure (1) shows the prices of gold from 1986 to 2012. Although the price of gold was

not changed considerably from 1986 to 2002, it starts to increase dramatically after the recent

financial crisis. In addition, figure (2) show that the gold volatility and stock volatility is very

high during the selected subsamples that is why I concentrated on these four critical periods to

investigate if the gold can be used as a safe haven against stocks and bonds or not.

Crises Starting date Market crash (Black Monday) October 17th, 1987

September eleven Crash September 11, 2001 Asian Crisis July 2nd, 1997

Subprime crisis (Housing Bubble) July 1st, 2007

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Figure (1) Gold prices and stock prices from 1986 to 2012

The gold prices in this paper are the gold fixing 1price 3:0 P.M. (London time) in London Bullion Market, based in U.S. dollars obtained from London Bullion Market Association through FRED. Gold prices are expressed in U.S. dollars per troy ounce from April 3rd, 1986 to December 31st, 2012. S& P500 daily prices and returns from CRSP.

1 The fixings is an open process at which market participants can transact business on the basis o single quoted price. Orders can be changed throughout the proceedings as the price move higher and lower until the price is moved higher and lower until such time as buyers' and sellers' orders are satisfied and the price is said to be 'fixed'. Orders executed at the fixings are conducted as principal-to-principal transactions between the client and the dealer through whom the order is placed.

0

400

800

1200

1600

2000

86 88 90 92 94 96 98 00 02 04 06 08 10 12

GOLDPRICES

(U.S. Do

llars per

Troy on

ce)

200

400

600

800

1000

1200

1400

1600

86 88 90 92 94 96 98 00 02 04 06 08 10 12

LEVEL�OF�THE�S&P�500�INDEX

S&p500

Prices

in U.S.

Dollars

12

Figure (2) Conditional Volatilities (GARCH (1, 1)) of Stocks and Gold

0

400

800

1200

1600

2000

86 88 90 92 94 96 98 00 02 04 06 08 10 12

LEVEL�OF�THE�S&P�500�INDEX Gold Prices

.000

.001

.002

.003

.004

.005

86 88 90 92 94 96 98 00 02 04 06 08 10 12

SP500VOLATILITY

(Percen

t)

.0000

.0002

.0004

.0006

.0008

.0010

86 88 90 92 94 96 98 00 02 04 06 08 10 12

GOLDVOLATILITY

(Percent)

(Percent)

13

Table (2) shows the summary statistics of gold prices, S&P prices, and the bond prices, in

addition to the excess return on gold, bond, and stock. Table (3) presents the correlation matrix

between gold return, bond return, and stock return.

Table (2): Summary Statistics

1986:04:01-2012:10:31(6510obs) Series Mean Standard Deviation Minimum Maximum

GOLDPRICES 542.921 369.44 252.8 1859 S&PPRICES 863.059 418.77 223.92 1565.150

tftgold RR ,, − 0.010 1.02 -7.85 7.68 VWRD-TBL 0.025 1.15 -17.16 9.52 VWR-TBL 0.016 1.15 -17.15 9.53

EWRD-TBL 0.064 0.94 -10.41 9.52 EWR-TBL 0.057 0.94 -10.42 6.90 SP-TBL 0.018 1.20 -20.5 10.79

AAA-TBL 6.95 1.62 3.22 11.06 BAA-TBL 7.95 1.60 4.45 12.04

Table (3): The Correlation Matrix Gold Return, Bond, Stock Returns

1986:04:01-2012:10:31(6510 Obs.)

Series tftgold RR ,, − VWR-TBL

VWRD-TBL EWR-TBL EWERD-TBL SP-TBL AAA-

TBL BAA-TBL

tftgold RR ,, − 1.00 (0.00)

-0.0236 (0.05)

-0.0236 (0.05)

0.004 (0.74)

0.004 (0.75)

-0.0417 (0.00)

-0.04 (0.00)

-0.03 (0.00)

VWR-TBL 1.00 (0.00)

0.99 (0.00)

0.89 (0.00)

0.89 (0.00)

0.98 (0.00)

-0.007 (0.58)

-0.01 (0.47)

VWRD-TBL 1.00 (0.00)

0.89 0.00)

0.89 (0.00)

0.98 (0.00)

-0.005 (0.66)

-0.007 (0.56)

EWR-TBL 1.00 (0.00)

0.89 (0.00)

0.84 (0.00)

-0.004 (-0.76)

-0.0035 (0.77)

EWRD-TBL 1.00 0.83 -0.004 -0.003

.000

.001

.002

.003

.004

.005

86 88 90 92 94 96 98 00 02 04 06 08 10 12

S&P Volatiltiy Gold Volatility

14

(0.00) (0.00) (0.72) (0.75)

SP-TBL 1.00 (0.00)

-0.005 (0.66)

-0.005 (0.66)

AAA-TBL 1.00 (0.00)

0.96 (0.00)

BAA-TBL 1.00 (0.00)

From the correlation matrix, it is obvious that there is a negative correlation

between gold excess returns and stocks and bonds’ excess returns. Additionally there is

insignificant correlation between stocks and bonds excess returns and consequently, both of them

can be included in the same equation without the presence of the problem of multicollinearity.

2. The Empirical Results of testing the Hedging Hypothesis:

2.1. The Contemporaneous relation between gold, stocks, and bonds.

In this section, I examine the first study hypotheses. I investigate whether gold can be

used as a hedge against stocks and bonds or not. If I find significant negative coefficient of the

stocks and bonds over the entire sample period, this means that investors can depend on gold

investment to hedge themselves from the losses in the stock and bond markets.

Table (4) reports the results of regressing the gold excess returns on the stock

returns (S&P500 excess returns, mean excess value weighted returns VWR, and the mean excess

equal weighted returns) and the corporate bond yields (Aaa, and Baa) during the entire sample

period (1986 - 2012). These results provide convincing evidence that there is a negative relation

between the stock returns and the gold prices returns. In other words, if the value weighted

returns of all NYSE, AMEX, NASDAQ portfolio drops on average by 1%, the gold returns move

to the opposite direction by 0.02% and can be used as a hedge against any surprising falls in the

stock prices. This relation is economically and statistically significant. The negative relation

between S&P500 and gold returns are more dramatic and statistically significant because any

15

drop in S&P500 returns by 1% can be partially compensated by increase in the gold returns by

0.4% the t statistics and the P-values show the probabilities of accepting the null hypothesis. The

negative relation between corporate bonds yields and stocks are more statistically but less

economically significant. We can imply from these results that gold can be used as a hedge

against drop in the stock returns. This result is Consistent with Baur and Lucey (2006)) and Baur

and McDermott (2009). Additionally there is a statistically evidence that gold can be used as

hedge against the drop in the corporate bond yields (Inconsistent with Baur and Lucey (2006)).

My results can add to the existing literature by finding significant negative relation between gold

and bonds by using more comprehensive and current dataset for Aaa and Baa corporate bonds.

Table (4) Hedging predictability of gold over the period from 1986 to 2012

Table (4) reports the relation between gold returns with stocks returns and bonds yields. The dependent variables is the gold excess return tftgold RR ,, − mean excess value-weighted and equal-weighted portfolios, VWR-TBL EWR-TBL excluding dividends and the mean excess value weighted portfolios including dividends VWRD-TBL EWRD-TBL; and S&P 500 mean excess rerun are all proxy to the stock returns. AAA-TBL and BAA-TBL yields are the bonds returns. All rates are represented in annualized percentage points.. The first number in the third column refers to the t-statistic of the test, and the second number refers to p value under the null hypothesis that the gold cannot be used as a hedge against drop in the stock and bond returns.

The next part use many models to test whether this relation is robust across many models

especially after controlling for Fama-French three factor model.

1986:04:01-2012:10:31 (6510 Obs.) tftgold RR ,, − t-statistic

VWR-TBL -0.0212**

-1.93

(0.054)

VWRD-TBL -0.0212** -1.93 (0.054)

EWR-TBL 0.0041 0.31 (0.76)

EWRD-TBL 0.0040 0.30 (0.76)

SP500-TBL -0.04*** -3.38 (0.00)

AAA-TBL -0.00024***

-3.06 (0.00)

BAA-TBL -0.00021*** -2.72 (0.00)

16

2.2.CAPM and Fama-French Results:

Table (5) reports the relation between the gold returns and stocks and bonds returns.

By using CAPM model to determine if gold has zero beta or negative beta with the market

portfolio. Gold can be a strong hedge because its returns commove against the market return.

After adding the bonds to the CAPM model to determine the relation between bonds returns and

gold returns, we find very significant negative relation between bond returns and gold returns.

Even after controlling for Fama French risk factors, the negative relation between market

excess returns and gold remains robust. However, it is obvious that there is a positive relation

between the between small companies returns and the large companies returns. This implies that

small stocks and gold may move

with the same direction.

However, even after controlling

for this positive relation, the

market excess returns as well as

bonds excess returns commove

against gold returns.

Table (5) CAPM and Fama French Results [the entire sample

period] Table (5) documents the relation between the gold returns with the other two markets for the entire sample period using four models. CAPM model, CAPM model including excess bonds returns in the right-hand side, Fama French three factor models, and Fama French Model including bonds excess returns in the right hand side. The GOLDR-TBL is the gold excess return. VWR-TBL is the excess value-weighted return, and S&P 500 is the excess rerun on S&P index return. AAA-TBL and BAA-TBL yields are the bonds returns. All rates are represented in annualized percentage points. t-statistics are in ().

1986:04:01-2012:10:31(6510 Obs.) Series MKTRF

1-VWR-TBL 2-S&P500-TBL

SMB HML BONDS AAA-TBL BAA-TBL

CAPM -0.0209* (-1.91)

-0.035***

17

3- The Empirical Results of testing the Safe Haven Hypothesis:

3.1. The Contemporaneous relation between gold, stocks, and bonds ( During tension

times) Although the gold proves that it can used as a hedge tool against stocks and bonds risks,

This does not mean that it can be used as a safe have. That is why I interact the stocks and bonds

returns with the tension times- dummy variable to test whether that gold can be used as a safe

haven in the crises and crash times whenever the stocks and bonds prices decreases dramatically.

Table (6) Reports the results of regressing the gold returns in the time of crisis on all

interaction terms that represent that stock and bonds returns in the extreme market conditions.

Results show that gold can be used as a safe haven against stocks. Negative relation between two

variables that ranges from (-0.063) using value weighted return portfolio and -0.077 using S&P

500 as a proxy for stock returns. There is no significant relation between bond retunes and the

gold returns in the tension periods. These results indicate that gold can be used as a safe haven

against stock but not against bonds.

Table (6) The contemporaneous relation between gold, stock and bonds in the tension times

(-3.37) CAPM+Bonds -0.0212**

(-1.93) -0.04** (-3.38)

-0.00024*** (-3.06)

-0.00021*** (-2.72)

FF -0.017* (-1.65)

-0.027** (-2.45)

0.07*** (3.83)

0.08*** (3.33)

-0.000922 (-0.04) 0.003 (0.15)

FF+Bonds -0.017* (-1.65) -0.027* (-2.74)

.08*** (3.8)

-0.07*** (3.27)

0.003 (0.16)

-0.00065 (-0.03)

-0.0002*** (-2.97)

-0.00021*** (-2.97)

18

(Safe haven hypothesis) Table (6) reports the relation between gold returns with stocks returns and bonds yields. The dependent variables is the gold excess returns such as crises or crashes RGOLD_Tension. Mean excess value-weighted and equal-weighted portfolios, VWR-TBL EWR-TBL excluding dividends and the mean excess value weighted portfolios including dividends VWRD-TBL EWRD-TBL; and S&P 500 mean excess rerun are all proxy to the stock returns during tension times. AAA-TBL and BAA-TBL yields are the bonds returns during tension times. All rates are represented in annualized percentage points.. The first number in the third column refers to the t-statistic of the test, and the second number refers to p value under the null hypothesis that the gold cannot be used as a safe haven against drop in the stock and bond returns .

3.2. CAPM and Fama French results:

Table (7) The relationship between gold returns and the sock and bonds returns during

extreme market conditions for the whole sample period from 1986:04:1-2012:10:31 using CAPM and Fama French models (Safe haven hypothesis)

Table (7) documents the relation between the gold returns with the other two markets during extreme market conditions using four models. CAPM model, CAPM model including excess bonds returns in the right-hand side, Fama French three factor models, and Fama French Model including bonds excess returns in the right hand side. The dependent variables is the gold excess return RGOLD_Tension.. The first row of each model documents mean excess value-weighted and equal-weighted portfolios, VWR-TBL which is the same as (MKTRF) mean excess value weighted portfolios excluding; and the second row of each model represents S&P 500 mean excess rerun are all proxy to the stock returns during tension times. AAA-TBL and BAA-TBL yields are the bonds returns during tension times. All rates are represented in annualized percentage points.. t-statistic are in ().

1986:04:01-2012:10:31 RGold_Tension tfR ,− t-statistic

VWR-TBL -0.063*** -3.27 0.00

VWRD-TBL -0.0627*** -3.27 0.00

EWR-TBL -0.058** -2.41 0.02

EWRD-TBL -0.059** -2.43 0.02

SP500-TBL -0.077*** -4.16 0.00

AAA-TBL -0.00044 -1.30 0.2

BAA-TBL -0.000433 -1.10 0.26

1986:04:01-2012:10:31(1440bs.) Series MKTRF

1-VWR-TBL 2-S&P-TBL

SMB HML BONDS AAA BAA

CAPM -0.062***

19

4- Robustness Tests:

4.1.Subsamples

As a check for robustness, I will analyze the relation between the change in the gold

prices with the stock and bond returns in each crisis separately to make sure if the gold can be

used as a safe haven against stocks and corporate bonds returns. I will analyze the relation

between gold prices with the other risky assets in the 20 days after the crash or crisis start.

Moreover, I will analyze the nature of this relation over the entire Asian crisis, and subprime

crisis period. I included here the most important crashes and crises that experienced dramatic

decrease in the stock and bond returns. For the black Monday crash and September eleven crash,

I tested the relation in the twenty days after the start of crashes. I tested the model for Asian and

subprime crises using 20 days after the crisis start and on overall crises period. The flowing four

tables show all the coefficients of stock returns and corporate bonds yields in each specific

subsample.

Table (8) The contemporaneous relation between gold, stock and bonds

(-3.22) -0.08*** (-4.14)

CAPM+Bonds -0.063*** (3.27)

-0.077*** (04.16)

-0.00044 (-1.3)

-0.00043 (-1.1)

FF -0.077*** (-3.43)

-0.08606*** (-3.88)

0.098** (2.58)

0.0708* (1.75)

-0.09** (-2.27)

-0.0937** (-2.41)

FF+Bonds -0.0774*** (-3.44)

-0.086*** (-3.89)

0.098 (2.57) 0.07* (1.73)

-0.09** (-2.38)

-0.089** (-2.25)

-0.0004 (-1.19) -0.0004 (-1.01)

20

in the Black Monday crash Table (8) reports the relation between gold returns with stocks returns and bonds yields during the black Monday crash. The dependent variables is the gold excess return tftgold RR ,, − mean excess value-weighted and equal-weighted portfolios, VWR-TBL EWR-TBL excluding dividends and the mean excess value weighted portfolios including dividends VWRD-TBL EWRD-TBL; and S&P 500 mean excess rerun are all proxy to the stock returns. AAA-TBL and BAA-TBL yields are the bonds returns. All rates are represented in annualized percentage points.. The first number in the third column refers to the t-statistic of the test, and the second number refers to p value under the null hypothesis that the gold cannot be used as a safe haven against drop in the stock and bond returns .The displays the number of observations and R2.

Table (8) reports the relation of the gold with the stock and bonds returns to test whether

the gold can be used as a safe haven in the extreme market condition like Black Monday crash .

The coefficient of the value weighted return in the 20 trading days after the beginning of the

crash is -0.150 and this estimate is statistically and economically significant. There is no

significant relation between the equal weighted return and the gold returns. The coefficient of

S&p500 is very close to the VWR (-0.1512) and there is negative relation between the corporate

bond yields and the gold returns but this relation is insignificant. Table (9) shows that gold

cannot be used as a safe haven against stocks and bonds for Asian crisis.

Table (9) The contemporaneous relation between gold, stock and bonds

In the Asian crisis Table (9) reports the relation between gold returns with stocks returns and bonds yields during the Asian crisis. The dependent variables is the gold excess return tftgold RR ,, − mean excess value-weighted and equal-weighted portfolios, VWR-TBL EWR-TBL excluding dividends and the mean excess value weighted portfolios including

1986:04:01-1986:5:01 (20 Obs.) R2=42% tftgold RR ,, − t-statistic

VWR-TBL -0.150*** -2.67 0.02

VWRD-TBL -0.147*** -2.57 (0.02)

EWR-TBL -0.042 -0.48 (0.64)

EWRD-TBL -0.146 -2.56 (0.02)

SP500-TBL -0.1512*** -3.47 (0.00)

AAA-TBL -0.003 -0.34 (0.74)

BAA-TBL -0.0047 -0.49 (0.63)

21

dividends VWRD-TBL EWRD-TBL; and S&P 500 mean excess rerun are all proxy to the stock returns. AAA-TBL and BAA-TBL yields are the bonds returns. All rates are represented in annualized percentage points.. The first number in the third column refers to the t-statistic of the test, and the second number refers to p value under the null hypothesis that the gold cannot be used as a safe haven against drop in the stock and bond returns .The displays the number of observations and R2.

Table (10) The relation contemporaneous between gold, stock and bonds in the September 11

Crash Table (10) reports the relation between gold returns with stocks returns and bonds yields during September 11 crash. The dependent variables is the gold excess return tftgold RR ,, − mean excess value-weighted and equal-weighted portfolios, VWR-TBL EWR-TBL excluding dividends and the mean excess value weighted portfolios including dividends VWRD-TBL EWRD-TBL; and S&P 500 mean excess rerun are all proxy to the stock returns. AAA-TBL and BAA-TBL yields are the bonds returns. All rates are represented in annualized percentage points.. The first number in the third column refers to the t-statistic of the test, and the second number refers to p value under the null hypothesis that the gold cannot be used as a hedge against drop in the stock and bond returns .The displays the number of observations and R2.

1997:07:02-to1997:08:02 (20 obs.) 20days trading after the starting of

Asian crisis R2=0

1997:01-1998:09(405obs.) The Asian crisis period

R2=0

tftgold RR ,, − t statistic tftgold RR ,, −

t-statistic

VWR-TBL 0.17 0.48 (0.63)

0.055 1.62 (0.11)

VWRD-TBL 0.17 0.48 (0.63)

0.045 1.6 (0.11)

EWR-TBL 0.82 0.48 (0.64)

0.115 2.49 (0.013)

EWRD-TBL 0.81 0.89 (0.39)

0.113 2.33 (0.015)

SP500-TBL 0.17 0.58 (0.57)

0.047 1.49 (0.135)

AAA-TBL -0.02 -0.78 (0.44)

-0.001 -0.96 (0.33)

BAA-TBL -0.02 -0.72 (0.48)

0.002 -1.04 (0.301)

22

Table (10) documents the estimated coefficient from regressing the gold returns on the

stocks returns and corporate bonds yields for twenty days after the starting of the September

eleven crash from. The estimated coefficients indicate that there is a highly significant negative

relation between stocks returns and gold returns in this crash indicating that the gold can be used

as a safe haven in this critical period. However the bonds returns coefficient implies no relation

with the gold returns. Moreover, Table (11) reports the relation between the gold prices change

and the changes in the stock and bond prices in 20 days after the crisis start, during the peak of

the crisis and during the overall subprime crisis period. There is no significant relation between

the gold and stocks in the early stage of the subprime crisis except between S&P500 excess

returns and the gold excess returns. However there is a significant relation between gold prices

change and the stock returns over the peak period of the crisis. The results remain robust in

respective of the ability of the gold to play a role of safe haven against corporate bonds in the

extreme market periods.

Table (11)

The contemporaneous relation between gold, stock and bonds in the subprime crisis Table (11) reports the relation between gold returns with stocks returns and bonds yields during the 20days period after the starting of the subprime crisis, the relation between three markets from the starting of the crisis to the peak of the financial crisis, and for the entire crisis period . The dependent variables is the gold excess return

2001:09:11-2001:09:30 (20 Obs.) R2=50.9

tftgold RR ,, − t-statistic (P value)

VWR-TBL -0.73*** -2.80 (0.02)

VWRD-TBL -0.73*** -2.75 (0.03)

EWR-TBL -0.62** -1.91 (0.09)

EWRD-TBL -0.63** -1.89 (0.09)

SP500-TBL -0.73*** -2.82 (0.02)

AAA-TBL -0.05 -0.99 (0.34)

BAA-TBL -0.05 -1.03 (0.33)

23

tftgold RR ,, − mean excess value-weighted and equal-weighted portfolios, VWR-TBL, EWR-TBL excluding dividends and the mean excess value weighted portfolios including dividends VWRD-TBL EWRD-TBL; and S&P 500 mean excess rerun are all proxy to the stock returns. AAA-TBL and BAA-TBL yields are the bonds returns. All rates are represented in annualized percentage points.. The first number in the third column refers to the t- statistic of the test, and the second number refers to p value under the null hypothesis that the gold cannot be used as a safe haven against drop in the stock and bond returns .The displays the number of observations and R2.

2007:07:01-2007:08:01(20 Obs.) 20days trading after the start of

Subprime crisis R2=11.5%

2007:7:18-2008:10:10(304 Obs.) during the peak Subprime

crisis R2=1.5%

2007:7:18-2009:04:02(529 Obs.) The entire period of the Subprime

crisis R2=2%

tftgold RR ,, − t-statistic (p value) tftgold RR ,, − t-statistic

(p value) tftgold RR ,, − t-statistic (p value)

VWR-TBL

0.194 1.46 (0.18)

-0.09* -1.60 (0.17)

0.003 0.11 (0.91)

VWRD-TBL

0.193 1.45 (0.18)

-0.10* -1.66* (0.17)

0.003 0.11 (0.90)

EWR-TBL

0.26 1.54 (0.16)

-0.08 -1.65* (0.134)

0.009 0.26 (0.79)

EWRD-TBL

0.26 1.55 (0.16)

-0.09 -1.63 (0.161)

0.009 0.26 (0.79)

SP500-TBL

0.17 -1.93* (0.05)

-0.10** -1.93* (0.05)

-0.016 -0.47 (0.63)

AAA-TBL 0.014 -0.8 (0.28)

-0.001 -0.19 (0.84)

-0.002 -0.20 (0.90)

BAA-TBL -0.012 -0.7 (0.30)

-0.002 -0.95 (0.34)

-0.003 -0.85 (0.28)

3.2.CAPM and Fama French Results ( Subsamples)

This section displays the results of the safe haven hypothesis using four different models

during four different stock market crashes. The gold can be used as a safe haven against stocks

even after controlling for FF three risk factors. Additionally, gold can be used as a safe haven

against bonds risk because there is zero correlation between two markets.

Table (12) CAPM and Fama French Results for Black Monday Crash

Black Monday (Market crash) (20bs.) Series MKTRF SMB HML BONDS

24

Table (13)

CAPM and Fama French Results: Asian Crisis

Table (14) CAPM and Fama French Results: September 11, 2001 Attack

1-VWR-TBL 2-S&P-TBL

AAA BAA

CAPM -0.140*** (-2.76) -0.146 (-3.67)

CAPM+Bonds -0.150*** (-2.67) -0.151 (-3.47)

-0.003 (-0.34) -0.005) (-0.49)

FF -0.155** (-2.04) -0.152 (-2.18)

0.17* (1.75) 0.103 (0.91)

-0.36 (-1.29) -0.36

(-1.34)

FF+Bonds -0.141* (-1.65) -0.142 (-1.69)

0.18* (1.69) 0.19 (0.9)

-0.34 (-1.1) -.34

(1.17)

0.002 (0.32) 0.003 (0.28)

Asian crisis months (405)obs.) Series MKTRF

1-VWR-TBL 2-S&P-TBL


CAPM 0.056 (1.62) 0.047 (1.49)

CAPM+Bonds FF 0.148**

(2.34) 0.152** (2.37)

0.09 (1.3) 0.140 (1.66)

0.190 (1.59) 0.204 (1.65)

FF+Bonds 0.164** (2.57)

0.170*8 (2.61)

0.117 (1.56) 0.166* (1.73)

0.223 (1.83) 0.126 (1.9)

-0.001 (-1.4) -.001

(-1.45)

25

Table (15)

CAPM and Fama French Results: Subprime Crisis

September 11 crash (20bs.) Series MKTRF

1-VWR-TBL 2-S&P-TBL


CAPM -0.70*** (-2.76)

-0.68*** (-2.68)

CAPM+Bonds -0.73*** (-2.8)

-0.73*** (-2.82)

-0.05 (-0.99) -0.05

(-1.03) FF -0.764***

(-4.46) -0.746***

(-4.24)

1.15 (1.81) 1.001 (1.56)

0.106 (0.15) 0.073 (0.10)

FF+Bonds -0.765*** (-4.13)

-0.764*** (-3.91)

1.15 (1.74) 1.93

(2.69)

0.110 (0.14) 0.07

(0.09)

-0.0003 (-0.01) -0.0001 (-0.00)

Panel (A): Subprime crisis first 20 trading days (20bs.) Series MKTRF

1-VWR-TBL 2-S&P-TBL


CAPM -0.194 (1.46) 0.173 (1.39)

CAPM+Bonds 0.194 (1.45) 0.17

(1.37)

-0.014 (0.69) -0.012 (-0.33)

FF 0.183 (1.24) 0.16

(1.12)

-0.172 (-0.54) -0.15

(-0.45)

-0.006 (-0.01) -0.002 (-0.01)

FF+Bonds 0.160 (1.07) 0.135 (0.94)

-0.29 (-0.85) -0.27 -0.77)

-0.13 (-0.26) -0.128 (-0.26)

0.02 (0.95) -0.01

(-0.16)

Panel (B): Subprime crisis from July 2007 to 0ct 2008 (304bs.)

26

4.2 The dynamic relation between gold, stocks, and bonds.

4.2.1 VAR Results:

It is important to examine the lagged impact of stock returns and corporate bond yields

on the gold returns. I will present the results of using VAR model that takes into consideration

the lagged impact of the gold lagged returns as well as the stock return and bond lagged returns,

Series MKTRF 1-VWR-TBL 2-S&P-TBL


CAPM -0.075 (-1.38) -0.10* (-1.93)

CAPM+Bonds -0.09* (-1.65) -0.10* (-1.93)

-0.001 (-0.19) -0.95

(-0.34) FF -0.063

(-1.02) -0.10

(-1.58)

0.210 (1.53) 0.19

(1.38)

-0.001 (-0.01)

0.03 (0.29)

-0.001 (-0.25) -0.001 (-0.25)

FF+Bonds -0.063 (-1.03) -0.097 (-1.6)

0.21 (1.53) 0.19

(1.38)

-001 (-0.01) 0.013 (0.12)

-0.002 (-0.25) 0.002

(-1.07))

Panel (C): Subprime crisis whole period from July 2007 to April 2009 (528bs.) Series MKTRF

1-VWR-TBL 2-S&P-TBL


CAPM 0.00318 (0.09) -0.016 (-0.47)

CAPM+Bonds 0.003 (0.09) -0.016 (-0.48)

-0.005*** (-2.01) -0.001 (-1.00)

FF 0.044 (1.07)

0.01 (0.09)

-0.15* (-1.69)

FF+Bonds 0.04 (1.00)

0.09 (0.98)

-0.14** (-1.98)

-0.001 (-1.08)

27

because in most cases the negative stock returns are followed by positive stocks. This change in

the direction of stocks returns changes the relation between stocks and gold completely. In most

cases, the negative stock returns at time t motivate investors to investors to purchase gold at time

t+1, then the gold prices may be affected and the returns on gold may drop at time t+1. The merit

of using VAR is that it considers all the variables in the model as endogenous variables so that

we can know the effect of all variables in the lagged form on the dependent variable at time t.

The following tables show that there is no dynamic relation between gold, stocks and bonds. As I

mensioned before, If the gold is zero or negatively correlated with stocks and bonds during

extreme market periods, then it will be considered as a safe haven against these two markets.

Table (16) presents the VAR estimates of the dynamic relation between gold, stocks, and

bonds for the entire sample period during all calm and tension states of economy. VAR accounts

of the lagged impact of the stocks returns and corporate bonds yields on the returns on gold.

I include the lagged returns up to 3 periods to account for the time series effect and know how

the stocks and bonds returns in t-1, t-2, t-3 affect the returns of gold today. The relation between

three markets is totally different from the contemporaneous relation between the three markets.

The gold returns on time t is negatively affected by the gold returns. The significant negative

relation between stocks and gold’s returns is no longer exists. However, there is a significant

negative relation between the corporate bond yields in t-1 and the gold returns at time t.

Tables (16) panel (b) reports the VAR estimates of the dynamic relation between gold

returns, corporate bond yields, and equity return during two market crashes (Black Monday, and

September 11), and two global financial crises (Asian crisis and subprime crisis), respectively.

Table (17) documents the VAR estimates of the three markets during market crash 1987

and September 11 crash in 2001. During the Market crash, the gold prices is negatively affected

28

by the stock returns on t-1 and t-3 however, there is a positive relation between gold returns at

time t and stocks returns at time t-2. This result implies that gold was considered a safe haven

against risky change in corporate bond yields during September 2001 crash.

Table (16) VAR Estimates of the relationship between gold, stocks and bonds returns (Entire

Sample Period) The table (16) presents the VAR parameter estimates of testing the dynamic relationship between gold

excess return tftgold RR ,, − , tftStock RR ,, − the stock returns using SP500. ftbond RR −, yields as estimated by

equations (1), (2), and (3) during the overall and tension periods (1986-2012). t-statistics are in [ ]. All variables are treaded as endogenous state variables All rates are represented in annualized percentage points.. The first number in the third column refers to the t-statistic of the test, and the second number refers to p value under the null hypothesis that the gold can not be used as a hedge against drop in the stock and bond returns.

Panel (a) Hedging: Whole sample Panel (b) Safe haven: tension periods

tftgold RR ,, −

tftStock RR ,, −

ftbond RR −,

tf

tTensiongold

RR

,

,_

−

tf

TensiontStock

RR

,

_

−

tfktTensionbond RR ,,_ −−

tftgold RR ,, − (-1) -0.02145* [-1.72595]

0.004369 [ 0.30016]

0.095803 [ 1.56331] tftTensiongold RR ,,_ −

(-1) -0.049864* [ -1.88178]

-0.04741 [-1.36582]

0.081546 [ 0.38296]

tftgold RR ,, − (-2) 0.002437 [ 0.19610]

0.017371 [ 1.19344]

0.253926*** [ 4.14328] tftTensiongold RR ,,_ −

(-2) 0.036676 [ 1.38070]

0.02456 [ 0.70576]

0.069584 [ 0.32598]

tftgold RR ,, − (-3) 0.00715 [ 0.57519]

-0.00343 [-0.23552]

-0.05689 [-0.92835] tftTensiongold RR ,,_ −

(-3) 0.01819

[ 0.68423] 0.005277 [ 0.15151]

-0.00899 [-0.04208]

tftStock RR ,, − (-1) 0.01538 [ 1.44501]

-0.04253*** [-3.41256]

-0.21338*** [-4.06604]

tfjtTensionStock RR ,,_ −−

(-1) -0.00993

[-0.49130] -0.03052

[-1.15219] -0.25554

[-1.57281]

tftStock RR ,, − (-2) 0.012796 [ 1.20119]

-0.03936 [-3.15520]

-0.17447*** [-3.32168]


(-2) 0.011218 [ 0.58957]

-0.07536*** [-3.02311]

-0.47649*** [-3.11638]

tftStock RR ,, − (-3) -0.00249 [-0.23425]

-0.00683 [-0.54962]

-0.04185 [-0.79950]


(-3) -0.00942

[-0.49521] -0.03838

[-1.53946] -0.09256

[-0.60529]

ftbond RR −, (-1) -0.00445* [-1.76021]

-0.00738** [-2.49182]

1.006033*** [ 80.7121] tfktTensionbond RR ,,_ −− (-1)

-0.00029 [-0.08893]

-0.01121*** [-2.60064]

0.99108*** [ 37.4927]

ftbond RR −, (-2) 0.002632 [ 0.73325]

0.005579 [ 1.32753]

-0.01776 [-1.00377] tfktTensionbond RR ,,_ −− (-2)

-0.00243 [-0.52782]

0.010225* [ 1.69438]

0.018094 [ 0.48881]

ftbond RR −, (-3) 0.001577 [ 0.62425]

0.001767 [ 0.59743]

0.011583 [ 0.93024] tfktTensionbond RR ,,_ −− (-3)

0.002305 [ 0.70918]

0.001435 [ 0.33692]

-0.02276 [-0.87129]

29

Table (17): VAR Estimates - The Black Monday crash and September 11 crash

The table (5) presents the VAR parameter estimates of testing the dynamic relationship between gold excess return

tftgold RR ,, − and the stock returns ( tftStock RR ,, − and ftbond RR −, yields as estimated by equations (1), (2), and (3) during the crashes periods. t-statistics are in [ ]. All variables are treaded as endogenous state variables All rates are represented in annualized percentage points.. The first number in the third column refers to the t-statistic of the test, and the second number refers to p value under the null hypothesis that the gold cannot be used as a hedge against drop in the stock and bond returns.

Table (18) documents the VAR estimates of the three markets during Asian crisis and

recent global financial crisis. During the Asian crisis, the gold prices are negatively affected by

the stock returns and bonds returns on t-1, t-2 and t-3. Overall, there is no significant relation

between gold and stock and bonds returns during crisis, and consequently the gold can be

considered as a safe haven even after taking into consideration the dynamic effect between the

three markets and taking the lagged returns effect into consideration.

Market crash September 11 crash

tftgold RR ,, − tftStock RR ,, − ftbond RR −,

tftgold RR ,, − tftStock RR ,, −

ftbond RR −,

tftgold RR ,, − (-1) -0.56050* [-1.65265]

0.782132 [ 0.75630]

-0.40901 [-0.16115] tftgold RR ,, − (-1) -0.61198***

[-2.22290] 0.246491 [ 0.26600]

-0.40485 [-0.22411]

tftgold RR ,, − (-2) 0.299549 [ 0.89060]

0.0946 [ 0.09238]

1.327673 [ 0.52829] tftgold RR ,, − (-2) 0.088735

[ 0.52113] 0.064334 [ 0.11225]

-0.71861 [-0.64318]

tftgold RR ,, − (-3) -0.0251 [-0.08772]

0.9066 [ 1.04077]

-0.99369 [-0.46482] tftgold RR ,, − (-3) 0.224813*

[ 1.67116] -0.50771

[-1.12124] 0.581162 [ 0.65839]

tftStock RR ,, − (-1) -0.02913 [-0.34511]

0.029154 [ 0.11345]

0.045259 [ 0.07177] tftStock RR ,, − (-1) -0.21926

[-1.54438] -0.10937

[-0.22887] 0.211626 [ 0.22717]

tftStock RR ,, − (-2) 0.007059 [ 0.11815]

0.013251 [ 0.07285]

-0.09991 [-0.22380] tftStock RR ,, − (-2) 0.110339

[ 0.90481] -0.18414

[-0.44862] -1.70318** [-2.12852]

tftStock RR ,, − (-3) -0.0523 [-1.05583]

-0.15757 [-1.04492]

-0.25517 [-0.68949] tftStock RR ,, − (-3) 0.26257

[ 1.43222] -0.39819

[-0.64527] -0.19638

[-0.16324]

ftbond RR −, (-1) -0.01514 [-0.26560]

-0.08953 [-0.51598]

0.706857 [ 1.65990] ftbond RR −, (-1) 0.109051*

[ 1.69984] -0.25493

[-1.18054] 0.872131** [ 2.07180]

ftbond RR −, (-2) -0.06943 [-1.33731]

0.434136*** [ 2.74658]

0.056314 [ 0.14517] ftbond RR −, (-2) -0.18129***

[-2.45382] 0.20804

[ 0.83656] 0.010872 [ 0.02243]

ftbond RR −, (-3) 0.076238*** [ 2.67925]

-0.34316*** [-3.96102]

0.025139 [ 0.11824] ftbond RR −, (-3) -0.201***

[ 3.38039] -0.1921

[-0.02375] 0.019

[-0.36882]

30

Table (18) VAR Estimates – the Asian Crisis and the Subprime Crisis

The table (5) presents the VAR parameter estimates of testing the dynamic relationship between gold excess return

tftgold RR ,, − and the stock returns tftStock RR ,, − and bond yields ftbond RR −, as estimated by equations (1), (2), and (3) during the crisis periods. t-statistics are in [ ]. All variables are treaded as endogenous state variables All rates are represented in annualized percentage points.. The first number in the third column refers to the t-statistic of the test, and the second number refers to p value under the null hypothesis that the gold cannot be used as a hedge against drop in the stock and bond returns.

4.2.2 IRF Results:

Using Impulse response Function technique (IRF), figure (3) shows the response of gold

returns to shocks in the stock returns and corporate bonds yields during October 1987 crash as

well as the September 11, 2001 attack. The figure shows that gold prices at time t commove

against the bonds and stocks returns shocks on the day t-1. However, gold prices at time t

commoves with the bonds and stock prices at time t-2 and t-3 and then for the rest of the trading

Asian Crisis Subprime crisis tftgold RR ,, − tftStock RR ,, −

ftbond RR −, tftgold RR ,, − tftStock RR ,, −

ftbond RR −,

tftgold RR ,, − (-1) -0.72572*** [-2.60719]

-0.27909 [-1.38309]

0.465419 [ 0.42818] tftgold RR ,, − (-1) 0.003391

[ 0.01013] -0.10722

[-0.21735] 1.140999 [ 0.90048]

tftgold RR ,, − (-2) -0.34287 [-1.12238]

0.490459** [ 2.21473]

-0.7963 [-0.66752] tftgold RR ,, − (-2) -0.36065

[-1.13930] 0.559027 [ 1.19831]

1.744518 [ 1.45586]

tftgold RR ,, − (-3) 0.205145 [ 0.60956]

-0.08416 [-0.34496]

0.781419 [ 0.59459]*** tftgold RR ,, − (-3) 0.569437*

[ 1.60197] 0.184668 [ 0.35252]

0.456178 [ 0.33902]

tftStock RR ,, − (-1) -0.92496** [-1.71022]

0.383291 [ 0.97761]

-2.89824 [-1.37228]** tftStock RR ,, − (-1) 0.022728

[ 0.06555] -0.93467** [-1.82919]

-1.47157 [-1.12121]

tftStock RR ,, − (-2) -0.25674 [-0.68374]

-0.57123** [-2.09850]

2.362404 [ 1.61112] tftStock RR ,, − (-2) -0.09614

[-0.27987] -0.79291

[-1.56625] -1.79291

[-1.37881]

tftStock RR ,, − (-3) -0.57455 [-1.38730]

-0.1115 [-0.37139]

0.046798 [ 0.02894] tftStock RR ,, − (-3) -0.06123

[-0.26745] -0.22186

[-0.65755] -1.01045

[-1.16591]

ftbond RR −, (-1) 0.045765 [ 0.48004]

0.082825 [ 1.19843]

0.812182** [ 2.18161] ftbond RR −, (-1) -0.07289

[-0.59271] 0.087591 [ 0.48330]

0.908285** [ 1.95113]

ftbond RR −, (-2) -0.02586 [-0.18569]

-0.12275 [-1.21570]

0.230201 [ 0.42325] ftbond RR −, (-2) -0.05186

[-0.41233] 0.012473 [ 0.06729]

0.233786 [ 0.49101]

ftbond RR −, (-3) -0.1007 [-0.93279]

0.043458 [ 0.55533]

-0.08808 [-0.20895] ftbond RR −, (-3) 0.037615

[ 0.35311] -0.1357

[-0.86438] -0.19981

[-0.49551]

31

month (20 days) after the crash the chocks in the stocks and bonds do not affect the gold returns.

During September 11 crash, the response of gold is relatively higher to chocks in bonds holding

stocks returns constant. The results show that gold move against chocks in bonds returns. This

figure along with the table (17) proves that there is a significant negative relation between gold

returns and corporate bonds yields chocks during the September 11 crash.

Figure (4) shows the results of the impulse response function during the 20 days period

after the start of the Asian crisis and the entire crisis period. It is obvious that there is negative or

zero relation between the gold and the stock market but there is a positive relation between gold

prices and the stock prices over the Asian crisis period. Figure (5) presents the IRF results during

the subprime crisis, and the figure shows that there is a negative but insignificant relation

between gold prices at time t and all the lagged returns of the stock and bonds returns except the

stock returns at t-1 and the bonds returns at t-3.

32

Figure (3)

Impulse Response Function for the Market Crashes Response Functions to gold, stock, and corporate bonds chocks. Calculations based on the VAR of table (11). Each chock changes the other variable of interest holding the others constant. GOLDEXR refers to the gold excess returns. EXSP refers to the excess returns on S&P used as a proxy of market index and EXxaa corporate bonds represent the excess returns on bonds. Panel (a) refers to IRF during the 20 days after the start of the Black Monday and panel (b) displays the IRF during 20 days after the starting of September 11 crash.

Panel (a): Market Crash 1987 and Panel (b): September 11

-.004

-.002

.000

.002

.004

.006

.008

.010

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA

Response of GOLDEXR to CholeskyOne S.D. Innovations

-.010

-.005

.000

.005

.010

.015

.020

.025

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA

Response of EXSP to CholeskyOne S.D. Innovations

.00

.01

.02

.03

.04

.05

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA

Response of EXAAA to CholeskyOne S.D. Innovations

-.006

-.004

-.002

.000

.002

.004

.006

.008

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


-.015

-.010

-.005

.000

.005

.010

.015

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


-.04

-.03

-.02

-.01

.00

.01

.02

.03

.04

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


33

Figure (4) Impulse Response Function for the Asian Crisis

Response Functions to gold, stock, and corporate bonds chocks. Calculations based on the VAR of table (12). Each chock changes the other variable of interest holding the others constant. GOLDEXR refers to the gold excess returns. EXSP refers to the excess returns on S&P used as a proxy of market index and EXxaa corporate bonds represent the excess returns on bonds. Panel (a) refers to the IRF during twenty days after the start of the crisis. Panel (b) refers to the IRF for the entire crisis period

Panel (a) The beginning of Asian crisis: Panel (b) Asian Crisis peak:

-.006

-.004

-.002

.000

.002

.004

.006

.008

.010

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


-.006

-.004

-.002

.000

.002

.004

.006

.008

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


-.01

.00

.01

.02

.03

.04

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


-.02

-.01

.00

.01

.02

.03

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


-.04

-.03

-.02

-.01

.00

.01

.02

.03

.04

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


-.06

-.04

-.02

.00

.02

.04

.06

.08

.10

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


34

Figure (5) Impulse Response Function for the Subprime Crisis

Response Functions to gold, stock, and corporate bonds chocks. Calculations based on the VAR of table (12). Each chock changes the other variable of interest holding the others constant. GOLDEXR refers to the gold excess returns. EXSP refers to the excess returns on S&P used as a proxy of market index and EXAAA corporate bonds represent the excess returns on bonds. Panel (a) refers to the IRF during twenty days after the start of the crisis. Panel (b) refers to the IRF for the whole crisis period.

Subprime start Panel (a) Subprime peak Panel (b)

-.004

-.002

.000

.002

.004

.006

.008

.010

.012

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


-.015

-.010

-.005

.000

.005

.010

.015

.020

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


.01

.02

.03

.04

.05

.06

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


-.02

-.01

.00

.01

.02

.03

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


-.04

-.03

-.02

-.01

.00

.01

.02

.03

.04

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


-.06

-.04

-.02

.00

.02

.04

.06

.08

.10

2 4 6 8 10 12 14 16 18 20

GOLDEXR EXSP EXAAA


35

VI. Conclusions

This paper examines the hedging and safe haven properties of stocks using daily data

over the period 1986 to 2012 using many different market indexes for stocks and corporate

bonds. I find that gold can be used as a hedge and safe haven during the calm and crashes

periods. During Asian crisis, gold cannot be used a safe haven against stock after controlling for

Fama French three factor models but can be used as a safe haven against bonds. The dynamic

relation between three markets take different style using VAR and IRF that shows in most cases

that gold has zero relation with the lagged stock returns and lagged corporate bonds yields, and

consequently can be a very effective safe haven against these markets fluctuations. The

durability for safe haven and hedging ability of stocks during recent years need further research

especially after price Jumping of gold in 2010. I think gold may lose its advantages if the trend

of the gold prices remains upward. If all investors flight from stocks and bonds to gold and

realized its advantages, the price of gold turned to be higher than stock and bonds prices and

consequently may lose its hedging and safe haven characteristics. This expectation depends on

the investor behaviors and this issue is left for future research.

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