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The relationship between the economic policy uncertainty and the cryptocurrency market
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The Relationship between the Economic Policy Uncertainty and the Cryptocurrency Market Hui-Pei Cheng Assistant Professors , Kuang-Chieh Yen Assistant Professors PII: DOI: Reference:
S1544-6123(19)30959-6 https://doi.org/10.1016/j.frl.2019.101308 FRL 101308
To appear in:
Finance Research Letters
Received date: Revised date: Accepted date:
6 September 2019 16 September 2019 6 October 2019
Please cite this article as: Hui-Pei Cheng Assistant Professors , Kuang-Chieh Yen Assistant Professors , The Relationship between the Economic Policy Uncertainty and the Cryptocurrency Market, Finance Research Letters (2019), doi: https://doi.org/10.1016/j.frl.2019.101308
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Inc.
Highlights
This paper investigates whether the economic policy uncertainty (EPU) index provided by Baker et al. (2016) can predict cryptocurrency returns.
We show that the China EPU index can predict the Bitcoin monthly returns.
China’s ban on crypto-trading results in a response in the returns of Bitcoin.
The Relationship between the Economic Policy Uncertainty and the Cryptocurrency Market Hui-Pei Cheng and Kuang-Chieh Yen1
September 2019
Abstract
In this paper, we investigate whether the economic policy uncertainty (EPU) index provided by Baker et al. (2016) can predict cryptocurrency returns. We show that the EPU index of China can predict the Bitcoin monthly returns while that of U.S. or other Asian countries has no predictive power. Furthermore, the China EPU index has no predictive power for the other main cryptocurrencies. Moreover, China’s ban on crypto-trading affects the returns of Bitcoin only among the main cryptocurrencies. JEL: C22, G15, D81 Keywords: Bitcoin, Cryptocurrencies, Economic policy uncertainty, China
1
Hui-Pei Cheng ([email protected]) and Kuang-Chieh Yen (corresponding author: [email protected]) are both Assistant Professors in Department of Economics at Soochow University, Taiwan. Address for correspondence: Department of Economics, School of Business, Soochow University, 56, Kuei-Yang St. Sec. 1, Taipei 100, Taiwan. The authors are grateful to the Ministry of Science and Technology of Taiwan for the financial support provided for this study
1. Introduction The cryptocurrency has become attractive to investors as it is often considered a ―safe haven‖ asset (Dyhrberg, 2016; Wang et al., 2019). Recent studies have begun exploring the predictors of the returns of cryptocurrencies due to the inefficient Bitcoin market (Urquhart, 2016; Hu et al., 2019). 2 For instance, studies find that returns can be predicted by crypto-market factors such as the cryptocurrency’s technical indicators (Gerritsen et al., 2019), the impact of media attention (Philippas et al., 2019), the mean-reverting property of return (Turatti et al., 2019), and the conditional tail risk (Borri, 2019). In addition, several studies show that macroeconomic situations may also be related to the returns of cryptocurrencies (Cheng and Yen, 2019). Few studies discuss whether economic policy uncertainty (EPU) may affect the returns of cryptocurrencies. Demir et al. (2018) show that the U.S. EPU index is negatively related to the Bitcoin daily return. Moreover, Wu et al. (2019) find that Bitcoin and gold cannot hedge well against the U.S. EPU risk. However, no studies explore the impact of EPU across countries on the returns of cryptocurrencies. Therefore, this paper explores whether the EPU index of different countries can predict the returns of cryptocurrencies. To explore this idea, we link the returns of cryptocurrencies to the EPU index developed by Baker et al. (2016). The index, which is on a monthly basis, is designed to measure the economic policy uncertainty of a country. The country samples used in our analysis are the United States (U.S.), China, Japan, and (South) Korea.3 We find
2
Tiwari et al. (2018) and Vidal-Tomás and Ibañez (2019) indicate that Bitcoin has become more efficient than before. Moreover, Corbet et al. (2019) show that cryptocurrency architecture can reduce transaction fees and thus can increase the efficiency of cryptocurrency trading. 3 These four countries are relevant to the development of the cryptocurrency market. The United States has the largest and most popular Bitcoin futures trading capacity. Japan and Korea have more complete
that the change rate of the China EPU can positively predict the Bitcoin monthly returns. However, the change in the U.S. EPU index has no apparent predictive ability for Bitcoin future returns. We also find that Japan and Korea have results similar to those of the United States. Finally, we show that the ban on cryptocurrency trading announced by the Chinese government in September of 2017 can enhance the predictive ability of the China EPU for Bitcoin returns. This finding suggests that the policy itself indeed had a significant effect on Bitcoin returns. In general, the positive linkage between the EPU index and Bitcoin future returns can be explained by the behaviour of investors. When investors observe an increase in EPU, especially from China since the largest Bitcoin mining pools are based in China (Ma et al., 2018), they may expect to suffer a loss in the Bitcoin market. Thus, they short Bitcoin and long other financial assets. However, as time goes by, uncertainty in the Bitcoin market decreases since investors can collect more information from the market.4 Therefore, they may short their other financial assets and long Bitcoin, and then increase the Bitcoin return as the demand for Bitcoin increases. Moreover, policy changes in China may further reduce uncertainty in the Bitcoin market, resulting in an increase in Bitcoin returns. We extend the study of Demir et al. (2018) in two important ways. First, our paper considers not only the EPU index of the U.S. but also that of other countries. We thus can identify which country’s EPU may be relevant to cryptocurrency returns. Second, our paper primarily uses monthly data rather than daily data to investigate the long-term predictive power of the uncertainty index on the cryptocurrency return. The
regulations for cryptocurrency trading than other countries. Moreover, China has the largest capacity for cryptocurrency investors in the world. 4 Investors may also short more Bitcoin if they find the uncertainty in the Bitcoin market will increase in the future, based on the information they have. However, our findings do not support this hypothesis.
use of monthly data can avoid the potential problem of noisy cryptocurrency data and the daily news-based economic policy index. The remainder of this paper is structured as follows. Section 2 discusses the data and empirical methodology while Section 3 discusses the estimation results. Section 4 concludes.
2. Data and Empirical Method 2.1 Data We obtain the cryptocurrencies data including Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Litecoin (LTC) from the coinmarketcap website. 5 The monthly return is calculated as
, where
is the price of the cryptocurrency in the
last trading day of the month . The monthly EPU index is constructed from Baker et al. (2016).6 In general, our sample period runs from February 2014 to June 2019 while Ethereum runs from September 2015 to June 2019.
2.2 Empirical Method To investigate the return predictability of the EPU for cryptocurrency, we use the following predictive regression model, ∑ where
∑
is the specific cryptocurrency returns at time ;
the EPU index at time t;
,
(1)
is the change rate of
is the vector of year and quarter dummies; and
is the
innovation at time t. The optimal lags of the model above are chosen according to the AIC criteria. Moreover, we adopt the Newey-West standard errors to eliminate the potential heterogeneity and autocorrelation problems (Newey and West, 1987).
3. Empirical Results 5 6
For more detail see https://coinmarketcap.com/ The index can be obtained from the website (http://www.policyuncertainty.com).
3.1 China Economic Policy Uncertainty In this section, we investigate whether the China EPU can predict the Bitcoin monthly returns. In Table 1, the coefficients In Table 2, the coefficients of the lagged Table 3 shows that most coefficients are not significant for the Japan and Korea models. Table 3 shows that the EPU indexes of Japan and Korea offer no significant In Table 4, all coefficients,
The Relationship between the Economic Policy Uncertainty and the Cryptocurrency Market Hui-Pei Cheng Assistant Professors , Kuang-Chieh Yen Assistant Professors PII: DOI: Reference:
S1544-6123(19)30959-6 https://doi.org/10.1016/j.frl.2019.101308 FRL 101308
To appear in:
Finance Research Letters
Received date: Revised date: Accepted date:
6 September 2019 16 September 2019 6 October 2019
Please cite this article as: Hui-Pei Cheng Assistant Professors , Kuang-Chieh Yen Assistant Professors , The Relationship between the Economic Policy Uncertainty and the Cryptocurrency Market, Finance Research Letters (2019), doi: https://doi.org/10.1016/j.frl.2019.101308
This is a PDF file of an article that has undergone enhancements after acceptance, such as the addition of a cover page and metadata, and formatting for readability, but it is not yet the definitive version of record. This version will undergo additional copyediting, typesetting and review before it is published in its final form, but we are providing this version to give early visibility of the article. Please note that, during the production process, errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. © 2019 Published by Elsevier Inc.
Highlights
This paper investigates whether the economic policy uncertainty (EPU) index provided by Baker et al. (2016) can predict cryptocurrency returns.
We show that the China EPU index can predict the Bitcoin monthly returns.
China’s ban on crypto-trading results in a response in the returns of Bitcoin.
The Relationship between the Economic Policy Uncertainty and the Cryptocurrency Market Hui-Pei Cheng and Kuang-Chieh Yen1
September 2019
Abstract
In this paper, we investigate whether the economic policy uncertainty (EPU) index provided by Baker et al. (2016) can predict cryptocurrency returns. We show that the EPU index of China can predict the Bitcoin monthly returns while that of U.S. or other Asian countries has no predictive power. Furthermore, the China EPU index has no predictive power for the other main cryptocurrencies. Moreover, China’s ban on crypto-trading affects the returns of Bitcoin only among the main cryptocurrencies. JEL: C22, G15, D81 Keywords: Bitcoin, Cryptocurrencies, Economic policy uncertainty, China
1
Hui-Pei Cheng ([email protected]) and Kuang-Chieh Yen (corresponding author: [email protected]) are both Assistant Professors in Department of Economics at Soochow University, Taiwan. Address for correspondence: Department of Economics, School of Business, Soochow University, 56, Kuei-Yang St. Sec. 1, Taipei 100, Taiwan. The authors are grateful to the Ministry of Science and Technology of Taiwan for the financial support provided for this study
1. Introduction The cryptocurrency has become attractive to investors as it is often considered a ―safe haven‖ asset (Dyhrberg, 2016; Wang et al., 2019). Recent studies have begun exploring the predictors of the returns of cryptocurrencies due to the inefficient Bitcoin market (Urquhart, 2016; Hu et al., 2019). 2 For instance, studies find that returns can be predicted by crypto-market factors such as the cryptocurrency’s technical indicators (Gerritsen et al., 2019), the impact of media attention (Philippas et al., 2019), the mean-reverting property of return (Turatti et al., 2019), and the conditional tail risk (Borri, 2019). In addition, several studies show that macroeconomic situations may also be related to the returns of cryptocurrencies (Cheng and Yen, 2019). Few studies discuss whether economic policy uncertainty (EPU) may affect the returns of cryptocurrencies. Demir et al. (2018) show that the U.S. EPU index is negatively related to the Bitcoin daily return. Moreover, Wu et al. (2019) find that Bitcoin and gold cannot hedge well against the U.S. EPU risk. However, no studies explore the impact of EPU across countries on the returns of cryptocurrencies. Therefore, this paper explores whether the EPU index of different countries can predict the returns of cryptocurrencies. To explore this idea, we link the returns of cryptocurrencies to the EPU index developed by Baker et al. (2016). The index, which is on a monthly basis, is designed to measure the economic policy uncertainty of a country. The country samples used in our analysis are the United States (U.S.), China, Japan, and (South) Korea.3 We find
2
Tiwari et al. (2018) and Vidal-Tomás and Ibañez (2019) indicate that Bitcoin has become more efficient than before. Moreover, Corbet et al. (2019) show that cryptocurrency architecture can reduce transaction fees and thus can increase the efficiency of cryptocurrency trading. 3 These four countries are relevant to the development of the cryptocurrency market. The United States has the largest and most popular Bitcoin futures trading capacity. Japan and Korea have more complete
that the change rate of the China EPU can positively predict the Bitcoin monthly returns. However, the change in the U.S. EPU index has no apparent predictive ability for Bitcoin future returns. We also find that Japan and Korea have results similar to those of the United States. Finally, we show that the ban on cryptocurrency trading announced by the Chinese government in September of 2017 can enhance the predictive ability of the China EPU for Bitcoin returns. This finding suggests that the policy itself indeed had a significant effect on Bitcoin returns. In general, the positive linkage between the EPU index and Bitcoin future returns can be explained by the behaviour of investors. When investors observe an increase in EPU, especially from China since the largest Bitcoin mining pools are based in China (Ma et al., 2018), they may expect to suffer a loss in the Bitcoin market. Thus, they short Bitcoin and long other financial assets. However, as time goes by, uncertainty in the Bitcoin market decreases since investors can collect more information from the market.4 Therefore, they may short their other financial assets and long Bitcoin, and then increase the Bitcoin return as the demand for Bitcoin increases. Moreover, policy changes in China may further reduce uncertainty in the Bitcoin market, resulting in an increase in Bitcoin returns. We extend the study of Demir et al. (2018) in two important ways. First, our paper considers not only the EPU index of the U.S. but also that of other countries. We thus can identify which country’s EPU may be relevant to cryptocurrency returns. Second, our paper primarily uses monthly data rather than daily data to investigate the long-term predictive power of the uncertainty index on the cryptocurrency return. The
regulations for cryptocurrency trading than other countries. Moreover, China has the largest capacity for cryptocurrency investors in the world. 4 Investors may also short more Bitcoin if they find the uncertainty in the Bitcoin market will increase in the future, based on the information they have. However, our findings do not support this hypothesis.
use of monthly data can avoid the potential problem of noisy cryptocurrency data and the daily news-based economic policy index. The remainder of this paper is structured as follows. Section 2 discusses the data and empirical methodology while Section 3 discusses the estimation results. Section 4 concludes.
2. Data and Empirical Method 2.1 Data We obtain the cryptocurrencies data including Bitcoin (BTC), Ethereum (ETH), Ripple (XRP), and Litecoin (LTC) from the coinmarketcap website. 5 The monthly return is calculated as
, where
is the price of the cryptocurrency in the
last trading day of the month . The monthly EPU index is constructed from Baker et al. (2016).6 In general, our sample period runs from February 2014 to June 2019 while Ethereum runs from September 2015 to June 2019.
2.2 Empirical Method To investigate the return predictability of the EPU for cryptocurrency, we use the following predictive regression model, ∑ where
∑
is the specific cryptocurrency returns at time ;
the EPU index at time t;
,
(1)
is the change rate of
is the vector of year and quarter dummies; and
is the
innovation at time t. The optimal lags of the model above are chosen according to the AIC criteria. Moreover, we adopt the Newey-West standard errors to eliminate the potential heterogeneity and autocorrelation problems (Newey and West, 1987).
3. Empirical Results 5 6
For more detail see https://coinmarketcap.com/ The index can be obtained from the website (http://www.policyuncertainty.com).
3.1 China Economic Policy Uncertainty In this section, we investigate whether the China EPU can predict the Bitcoin monthly returns.