Does gold or Bitcoin hedge economic policy uncertainty?

Finance Research Letters 31 (2019) 171–178

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Does gold or Bitcoin hedge economic policy uncertainty? Shan Wu a,b , Mu Tong a,b, , Zhongyi Yang b , Abdelkader Derbali c ⁎

T

a

Collaborative Innovation Center of Financial Security, Southwestern University of Finance and Economics, Chengdu, China School of Economic Information Engineering, Southwestern University of Finance and Economics, Chengdu, China c Community College in Madinah, Taibah University, Medina, Saudi Arabia b

ARTICLE INFO

ABSTRACT

JEL classifications: C22 G15

Calculating the hedge and safe-haven properties of gold and Bitcoin via GARCH model and quantile regression with dummy variables. We find that: (1) Neither gold nor Bitcoin can serve as a strong hedge or safe-haven for economic policy uncertainty (EPU) at the average condition. (2) Bitcoin is more responsive to EPU shocks, while gold maintains stability with smaller hedge and safe-haven coefficients. (3) In most cases, both gold and Bitcoin can act as the weak hedge and weak safe-haven against EPU during the extreme bearish and bullish markets, which two can be considered for portfolio diversification during the normal market.

Keywords: Gold Bitcoin Hedge Safe-haven Quantile regression EPU

1. Introduction Economic policies play a vital role in shaping the economic development of an economy, and any uncertainty in the policies slows down its development process (Raza et al., 2018). Thus under the high global uncertainty many articles study which assets can hedge uncertainty. Primarily, gold as a unique commodity has multiple attributes of commodity, currency and risk aversion, it has been traditionally acting as a hedge in portfolio diversification and a safe-haven in times of extreme economic and severe market turmoil (Baur and Lucey, 2010; Baur and McDermott, 2010; Bredin et al., 2015; O'Connor et al., 2015; Lucey et al., 2017; Bilgin et al., 2018). Another attractive asset is Bitcoin, a fully decentralized cryptocurrency born after the global financial crisis and does not depend on any government or agency (Urquhart, 2016; Nadarajah and Chu, 2017). Because of the similar to gold characteristics (see Selgin, 2015; Selmi et al., 2018; Shahzad et al., 2019) and unique pricing mechanism, it has often been argued that Bitcoin was launched to solve the distrust and uncertainty in the existing financial system, if some investors lose trust in mainstream currencies or the entire economy, they might resort to Bitcoin (Dyhrberg, 2016; Bouri et al., 2017a; Wang et al., 2018).1 E.g., during the 2010–2013 European sovereign debt crisis, the 2012–2013 Crypto banking crisis and the 2018 Turkish currency debt crisis, many people resorted to Bitcoin as a hedge or safe-haven to avoid risk and uncertainty (Bouri et al., 2017b; Maurya, 2018; Lucey et al., 2017). In the existing empirical literature, to the best of our knowledge, a limited number of studies have considered Bitcoin hedging uncertainty. These studies use the VIX index (Bouri et al., 2017c), EPU index (Demir et al., 2018; Wang et al., 2018), global financial Corresponding author E-mail addresses: [email protected] (S. Wu), [email protected] (M. Tong), [email protected] (Z. Yang). 1 Many studies highlight that there are very weak correlations between Bitcoin and other markets Dwyer, 2015; Dyhrberg, 2016; Lucey et al., 2017; Bouri et al., 2017a,b,c; Guesmi et al., 2018; Shahzad et al., 2019), also we test the contemptuous return correlations between EPU index and stocks, exchanges, gold ,bitcoin, the results indicate that bitcoin and gold are less affected by EPU. In this paper the term “EPU” denotes economic policy uncertainty, and such terms as “the US EPU index” refer to the US economic policy uncertainty index developed by Baker et al. (2016). ⁎

https://doi.org/10.1016/j.frl.2019.04.001 Received 13 December 2018; Received in revised form 21 February 2019; Accepted 6 April 2019 Available online 08 April 2019 1544-6123/ © 2019 Elsevier Inc. All rights reserved.

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stress index (Bouri et al., 2018) as the proxies as uncertainty and highlight that Bitcoin has different hedge effects against uncertainty under different market conditions. E.g., Bouri et al. (2017c) and Demir et al. (2018) use the wavelet-based quantile-on-quantile method and OLS regression, reveal that Bitcoin return is mainly negatively associated with uncertainty, but Bitcoin can be used for hedging against uncertainty during the times of bull-market. Furthermore, Bouri et al. (2018) use copula-based techniques to examine the quantile conditional dependence and causality between Bitcoin and the global financial stress index, showing that Bitcoin can be a safe-haven against global financial stress. Wang et al. (2018) use multivariate quantile model and Granger causality risk test; they find that the risk spillover effect from EPU to Bitcoin is negligible in most conditions and Bitcoin can be acted as a safe-haven or a diversifier under EPU shocks. Although much empirical research finds that traditional financial assets (e.g., commodity, gold) are somewhat affected by EPU (see Raza et al., 2018; Bilgin et al., 2018; Fang et al., 2018), while these empirical literature cover gold or Bitcoin without making a comparative analysis between their roles against EPU, and these research haven't contended the period of a relatively Bitcoin stability in the second half of 2018.2 Accordingly, we compare the hedge and safe-haven roles of Bitcoin and gold under EPU shock and investigate whether the hedge or safe-haven coefficients are altered significantly if we consider several bullish and bearish periods in the gold and Bitcoin markets. Our study has three contributions to financial literature. Firstly, we combine the GARCH model and quantile regression with dummy variables, which include the extreme situations of the average condition and different quantiles (i.e., bearish, bullish and normal markets), the findings provide potential implications for portfolio diversification and risk management. Secondly, our study compares the hedge and safe-haven roles of gold and Bitcoin against EPU shocks, which is supplementary to the related literature. Thirdly, our study is useful for investors and financial advisors who search for hedge or safe-haven asset, especially during the stress period. The remainder of the paper is as follows. Section 2 describes the methodology and data. Section 3 reports the results and robustness. Section 4 concludes. 2. Methodology and data 2.1. GARCH model with dummy variables According to the research of Baur and Lucey (2010) and Bouri et al. (2017a,b), we consider the GARCH model with dummy variables. The following models are estimated by the maximum likelihood method:

rt = 2 t

+ rt

=

0

+

1

+

2 1 t 1

0 ri, t

+

+

1 D (ri, q90 ) ri, t

+

2 D (ri, q95) ri, t

+

3 D (ri, q99 ) ri, t

+

(1)

t

(2)

2 2 t 1

where the dependent variable rt represents the return of gold or Bitcoin, ri,t is the change of EPU index. D(ri,q90) is the dummy variable of 90% quantile, which means when the change of EPU higher than the 90% quantile, the dummy variable takes 1 and otherwise takes 0. D(ri,q95) and D(ri,q99) represent the dummy variables of 95% and 99%, respectively, the construction methods are same with D (ri,q90). We follow the Iqbal (2017) and Bouri et al. (2017a,b) to determine whether gold or Bitcoin can be a hedge or safe-haven against EPU shocks at the average condition. While considering the EPU index is usually rising consistent with the asset price declining, the hedge or safe-haven in this paper should accord with the characteristics: when the EPU index rises, the asset price not falls. So, in this paper, a weak (strong) hedge is an asset that is uncorrelated (positively correlated) with EPU on average, a weak (strong) safe-haven is an asset that is uncorrelated (positively correlated) with EPU on average during times of stress. Therefore, we extend the 1 Iqbal (2017) and define that if β0 > 0, then gold or Bitcoin is a hedge against EPU; if i = 0 i > 0 , then gold or Bitcoin is a safe-haven 2

against EPU at 90% quantile; if i = 0 i > 0 , then gold or Bitcoin is a safe-haven at 95% quantile of EPU; if Bitcoin is a safe-haven at 99% quantile of EPU.3

3 i=0 i

> 0 , then gold or

2.2. Quantile regression with dummy variables Let Y denote the return of gold or Bitcoin, and X denote the change of EPU index. Then, we consider Y as a real-valued random variable with cumulative distribution function FY(y) = P(Y ≤ y), the ξth conditional quantile of Y given X = x is defined as:

QY | x ( ) = FY |1x ( ) = inf {y : Fy | x (y )

};

(3)

[0, 1]

Where QY|x(ξ) = x′β(ξ), β(ξ) is the coefficient vector for x at the ξth quantile, thus

^

( )

= argmin

(yi

x )

(4)

2 The price and market capitalization of Bitcoin reached their record high of $19343.04 and $326 billion on 16-17 December 2017, respectively, while at 31, June 2018, these values fell to $6391.7 and $109.43 billion respectively; until to December 31, 2018 the values fell to $3830.5 and $67.47 billion respectively, thus the second half of 2018 is a relatively stable period of Bitcoin. k 3 In this paper, the calculation of i = 0 i (k = 1, 2, 3) are based on the variance-covariance matrices.

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ρξ(y) = y(ξ − I(y < 0)), I (.) is the indicator function. On the basis, we set up the following model to test whether gold or Bitcoin is the hedge or safe-haven for EPU at different quantiles:

QY | x ( ) = µ +

0( ) ri, t

+

1( ) D (ri, q90 ) ri, t

+

2( ) D (ri, q95) ri, t

+

3( ) D (ri, q99 ) ri, t

+ et

(5)

In which the variables D(ri,q90), D(ri,q95) and D(ri,q99) represent the dummy variables that assume value 1 if the change of EPU index exceeds the respective quantiles and 0 elsewhere. At ξth quantile, the hedge and safe-haven properties of gold and Bitcoin are determined in the same way as the average condition. 2.3. Data In our analysis, the sample includes the gold price, USD price of Bitcoin, US EPU index.4 The time series cover the period from February 02, 2012 to December 31, 2018, 1532 daily groups based on data availability. Data for the gold price and Bitcoin price of Bitfinex exchange are obtained from https://investing.com/, the US EPU index collected from http://www.policyuncertainty.com/. We employ the logarithmic returns of Bitcoin, gold or change of the EPU index, i.e., ui,t = 100*[log (pi,t) − log (pi,t − 1)], where pi,t is the price sequence at the t period of each variable. The summary statistics for the daily returns and change are shown in Table 1. Bitcoin has the lowest negative mean return and US EPU has the biggest standard deviation, gold has a positive mean return. The skewness and kurtosis statistics suggest that all series have the “high peak and fat tail” distributions. The ADF unit root test results indicate that the variables are stationary series. All series are non-normally distributed, as indicated by the Jarque–Bera test. 3. Results and robustness 3.1. Empirical results Table 2 presents the estimation results between returns of Bitcoin, gold, and change of US EPU via GARCH model with dummy variables, which aim to test the hedge and safe-haven properties of gold and Bitcoin at the average condition. What we can see the hedge or safe-haven coefficients of gold: β0 < 0 and significant at the 1% level indicate that gold does not act as a hedge against EPU; 1 >0 suggests that gold is a weak safe-haven for EPU at 90% quantile, in other cases, gold is not a safe-haven. Moreover, for i=0 i k

Bitcoin, β0 > 0 indicates that Bitcoin is a weak hedge against EPU; i = 0 i <0 (k = 1,2,3) suggest that Bitcoin is not a safe-haven against EPU. To sum up, neither gold nor Bitcoin can serve as a strong hedge or safe-haven against EPU at the average condition. In order to get the results of different quantiles, we use the quantile regression with dummy variables to analysis the hedge and safe-haven properties of gold and Bitcoin. Table 3 presents the estimation results between the return of gold and change of US EPU index via quantile regression model. β0 > 0 at the lower quantiles (10% and 25%) suggest that gold is a weak hedge against the lower k EPU condition, while it could not serve as a hedge asset in other cases. The safe-haven coefficients i = 0 i >0(k = 1,2,3) at 95% quanitle, which indicates that gold can serve as a weak safe-haven for the higher EPU condition, at the same time the gold market is 3 bullish. i = 0 i >0 at 1% significant level on the 10% quantile, which suggests that gold is a strong safe-haven at lower EPU condition. In Table 4, we present the estimation results between return of Bitcoin and change of US EPU index via quantile regression with dummy variables. The hedge coefficient β0 > 0 at the 10% significant level on 10% quantile, indicate that Bitcoin is a strong hedge for lower EPU shock, while at the medium and higher quantiles (25%, 40%, 55% and 70%, 95%), it turned to be a weak hedge against k EPU. The safe-haven coefficients i = 0 i (k = 1,2,3) are positive at the lower quantiles (10% and 25%) and higher quantiles (85% and 95%) mostly, which suggest that Bitcoin could serve as a weak safe-haven during its extreme bearish and bullish markets for both lower and higher EPU shocks. Furthermore, we calculate the hedge and safe-haven coefficients of gold and Bitcoin with 95% confidence bands associated with Eq. (5), showing in Fig. 1 and Fig. 2, respectively. It is evident that Bitcoin reacts strongly to uncertainty at both lower and higher quantiles, while gold maintains stability with smaller hedge and safe-haven coefficients. In most cases, both gold and Bitcoin can serve as a weak hedge and weak safe-haven against uncertainty at the extreme bearish and bullish market (10% and 90% quantile). 3.2. Robustness check In order to get more rigorous conclusion, we take the UK EPU index as the robustness test; the conclusions are mostly consistent with the results of US EPU. The estimation results of GARCH model with dummy variables indicate that gold is a weak hedge and weak safe-haven against UK EPU, Bitcoin is not a hedge and sometimes a weak safe-haven, that is, neither gold nor Bitcoin can serve as a strong hedge or safe-haven against uncertainty at the average condition. As for the results of quantile regression with dummy variables, the hedge coefficients of gold and Bitcoin β0 > 0 at lower quantiles (10%), which indicate that gold and Bitcoin are weak hedge against the lower EPU; the safe-haven coefficients indicate that in most cases, both gold and Bitcoin can be used as weak hedge and weak safe-haven against EPU during the bearish and bullish markets. Moreover, in the normal market, gold is still a weak hedge and weak safe-haven against uncertainty, while Bitcoin tends to be a portfolio diversification. Bitcoin is more responsive to uncertainty and gold maintains stability with smaller hedge and safe-haven coefficients. Detailed estimation results are given in the appendix. 4

We use US EPU index as the measure of economic policy uncertainty and UK EPU index as the robustness check. 173

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Table 1 Descriptive statistics on returns of gold, Bitcoin and change of the US EPU index. Variable

Mean

Std. Dev.

Min

Max

Skew

Kurt

ADF test

Jarque-Bera test

Gold Bitcoin US EPU

0.022 −0.420 −0.062

0.988 5.759 53.967

−5.014 −38.049 −321.562

9.596 35.059 290.386

0.780 0.118 −0.176

11.602 11.137 5.032

−39.314*** −36.595*** −60.634***

4887.962 (0.000) 4238.307 (0.000) 272.003 (0.000)

Notes: ***, ** and * represent significance at 1%, 5%, and 10% levels, respectively. ADF is the Augmented Dickey-Fuller test for the unit root. The number in parenthesis is the P-value of the Jarque-Bera test. Table 2 Estimation results between gold, Bitcoin and US EPU index via GARCH model with dummy variables. Parameters Panel A: Gold Panel B: Bitcoin

λ

β0

0.0122 (0.0299)

−0.00130** (0.000536)

0.000334 (0.00150)

−0.000219 (0.00104)

0.0605** (0.0306)

0.00198 (0.00211)

−0.0166*** (0.00403)

−0.00701 (0.00702)

1 i=0 i

θ0

θ1

θ2

−0.00018 (0.00196)

0.00185 (0.00127)

0.0134*** (0.00210)

0.984*** (0.00271)

−0.0142*** (0.00411)

1.350*** (0.165)

0.214*** (0.0211)

0.773*** (0.0172)

2 i=0 i

3 i=0 i

Notes: Numbers in parentheses are standard errors of the corresponding estimated coefficients. ***, ** and * represent significance at 1%, 5%, and 10% levels, respectively. Table 3 Estimation results between gold and US EPU index via quantile regression with dummy variables. Quantile Panel A: Gold β0 1 i=0 i

2 i=0 i 3 i=0 i

10%

25%

40%

55%

70%

85%

95%

0.000567 (0.00109) 0.000350

0.0000154 (0.000745) 0.0000209

−0.000320 (0.000497) 0.000558

−0.000329 (0.000678) −0.0000365

−0.00102* (0.000603) 0.000338

−0.00111 (0.00107) −0.000974

−0.00401 (0.00350) 0.00173

(0.00203) −0.00509

(0.00134) −0.000247

0.00196 0.000426

(0.00153) −0.000638

(0.00115) −0.000941

(0.00281) 0.00088

(0.00481) 0.00342

(0.00334) 0.00234**

(0.00197) 0.000455

(0.00138) −0.000867

(0.00119) −0.00193**

(0.00158) −0.00158

(0.00274) 0.0000698

(0.00364) 0.00266

(0.00103)

(0.00111)

(0.000866)

(0.000946)

(0.00218)

(0.00424)

(0.00325)

Notes: Numbers in parentheses are standard errors of the corresponding estimated coefficients. ***, ** and * represent significance at 1%, 5%, and 10% levels, respectively. Table 4 Estimation results between Bitcoin and US EPU index via quantile regression with dummy variables. Quantile Panel B: Bitcoin β0 1 i=0 i

2 i=0 i 3 i=0 i

10%

25%

40%

55%

70%

85%

95%

0.00813* (0.00482) 0.0113

0.00191 (0.00439) 0.00716

0.000545 (0.00198) −0.00362

0 (0.00115) −0.00223

0.000399 (0.00294) −0.00142

−0.00376 (0.00507) −0.0081

0.0011 (0.0125) 0.0146

(0.0193) 0.000813

(0.00698) −0.00168

(0.00451) −0.00633

(0.00295) −0.0048

(0.00724) −0.00261

(0.0084) 0.0151

(0.0257) 0.0276

(0.0142) −0.0326

(0.0106) 0.00287

(0.00519) −0.0000608

(0.00346) −3.47e-18

(0.00871) 0.000256

(0.0204) 0.00748

(0.0473) 0.0645

(0.0325)

(0.0357)

(0.00441)

(0.0127)

(0.0102)

(0.0314)

(0.0494)

Notes: Numbers in parentheses are standard errors of the corresponding estimated coefficients. ***, ** and * represent significance at 1%, 5%, and 10% levels, respectively.

4. Conclusion This paper examines whether gold or Bitcoin can serve as a hedge or safe-haven against EPU by GARCH model and quantile regression with dummy variables. We find that neither gold nor Bitcoin can serve as a strong hedge or safe-haven against EPU at the average condition, while in most cases, both gold and Bitcoin can serve as a weak hedge and weak safe-haven against EPU during the 174

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Fig. 1. Hedge and safe-haven coefficients of gold with 95% confidence bands at extreme 90%,95%,99% quantiles of US EPU index.

Fig. 2. Hedge and safe-haven coefficients of Bitcoin with 95% confidence bands at extreme 90%,95%,99% quantiles of the US EPU index.

extreme bearish and bullish markets. Which means the hedge and safe-haven effects of gold and Bitcoin are correlated with their bearish or bullish market situation, and these two assets can be considered for portfolio diversification during the normal market. Bitcoin reacts more responsive to EPU shocks and gold maintains stability with smaller hedge and safe-haven coefficients. Our results suggest that Bitcoin can be an alternative instrument just like gold for hedging against uncertainty, which are partly in line with Bouri et al. (2017c), Demir et al. (2018) and Wang et al. (2018), these findings provide potential implications for portfolio diversification and risk management. It is also noteworthy to note that future research can use other uncertainty measures to analyse their effects on gold and cryptocurrency markets of different countries. Moreover, future papers can analysis the predictive power of different countries’ EPU on the gold or Bitcoin price of different exchanges. 175

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Acknowledgments The authors gratefully acknowledge the support of the National Natural Science Foundation of China (grant nos. 71473201 and 71603031). Data availability statement The data used to support the findings of this study are available from the corresponding author upon request. Supplementary materials Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.frl.2019.04.001. Appendix Table A1 Estimation results between gold, Bitcoin and UK EPU index via GARCH model with dummy variables. Parameters Panel A: Gold Panel B: Bitcoin

λ

β0

0.0111 (0.0298)

0.000196 (0.000612)

0.000529 (0.00142)

0.000164 (0.00155)

0.0659** (0.0297)

−0.00221 (0.00263)

0.00697 (0.00688)

−0.00983*** (0.005)

1 i=0 i

θ0

θ1

θ2

0.000877 (0.00155)

0.00194 (0.00131)

0.0131*** (0.00204)

0.985*** (0.00272)

0.00619 (0.0073)

1.505*** (0.155)

0.196*** (0.0202)

0.778*** (0.0175)

2 i=0 i

3 i=0 i

Notes: Numbers in parentheses are standard errors of the corresponding estimated coefficients. ***, ** and * represent significance at 1%, 5%, and 10% levels, respectively. Table A2 Estimation results between gold and UK EPU index via quantile regression with dummy variables. Quantile Panel A: Gold β0 1 i=0 i

2 i=0 i 3 i=0 i

10%

25%

40%

55%

70%

85%

95%

0.00226 (0.00175) −0.00575*

0.000658 (0.000736) −0.00469

−0.000178 (0.000575) 0.00101

0.000160 (0.000648) 0.000819

0.00114* (0.000626) 0.00127

0.000814 (0.00106) 0.000378

−0.00137 (0.00247) 0.00841

(0.00299) 0.00357**

(0.00386) −0.000124

(0.0021) 0.00125

(0.00219) 0.000256

(0.00154) −0.001189

(0.00276) 0.000383

(0.00897) −0.00325

(0.00182) 0.00189

(0.00136) 0.000476

(0.00107) 0.000639

(0.000923) 0.00168

(0.00149) 0.00446

(0.00153) 0.00302

(0.00547) 0.00759*

(0.00135)

(0.00158)

(0.00184)

(0.00273)

(0.00374)

(0.00374)

(0.00469)

Notes: Numbers in parentheses are standard errors of the corresponding estimated coefficients. ***, ** and * represent significance at 1%, 5%, and 10% levels, respectively.

Table A3 Estimation results between Bitcoin and UK EPU index via quantile regression with dummy variables. Bitcoin

10%

25%

40%

55%

70%

85%

95%

−0.000433 (0.00325) 0.00486

−0.00354* (0.00208) 0.00228

0 (0.00147) 0.00122

−0.00195 (0.00352) −0.00604

−0.00580 (0.00756) −0.0163

−0.0144 (0.0176) 0.0106

(0.0232) −0.0458

(0.00962) −0.00863

(0.00585) −0.00501

(0.00512) −0.00642

(0.00548) −0.00229

(0.0227) −0.0144

(0.0381) −0.0188

(0.0365) −0.0376

(0.0105) −0.0115

(0.00523) 0.00668

(0.00532) 0.00423

(0.00618) 0.00943

(0.0133) 0.00768

(0.0953) 0.0622

(0.0313)

(0.0271)

(0.0182)

(0.00664)

(0.00898)

(0.0106)

(0.0423)

Panel B: Bitcoin β0 0.0165* (0.00873) 1 0.00402 i=0 i

2 i=0 i 3 i=0 i

Notes: Numbers in parentheses are standard errors of the corresponding estimated coefficients. ***, ** and * represent significance at 1%, 5%, and 10% levels, respectively. 176

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Fig. A1. Hedge and safe-haven coefficients of gold with 95% confidence bands at extreme 90%,95%,99% quantiles of the UK EPU index.

Fig. A2. Hedge and safe-haven coefficients of Bitcoin with 95% confidence bands at extreme 90%,95%,99% quantiles of the UK EPU index.

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