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Economic policy uncertainty and cryptocurrency volatility
Journal Pre-proof
Economic Policy Uncertainty and Cryptocurrency Volatility Kuang-Chieh Yen , Hui-Pei Cheng PII: DOI: Reference:
S1544-6123(19)31018-9 https://doi.org/10.1016/j.frl.2020.101428 FRL 101428
To appear in:
Finance Research Letters
Received date: Revised date: Accepted date:
19 September 2019 18 November 2019 8 January 2020
Please cite this article as: Kuang-Chieh Yen , Hui-Pei Cheng , Economic Policy Uncertainty and Cryptocurrency Volatility, Finance Research Letters (2020), doi: https://doi.org/10.1016/j.frl.2020.101428
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. © 2020 Published by Elsevier Inc.
Highlights
This paper investigates whether the economic policy uncertainty (EPU) index provided by Baker et al. (2016) can predict cryptocurrency volatility.
We show that the China EPU index can predict negatively the Bitcoin monthly volatility.
China’s ban on crypto-trading does not result in a response in the volatility of Bitcoin.
1
Economic Policy Uncertainty and Cryptocurrency Volatility Kuang-Chieh Yen and Hui-Pei Cheng ＊ November 2019
Abstract We investigate the relationship between the economic policy uncertainty index (EPU) and cryptocurrency volatility. We find that a change in EPU of China predicts cryptocurrency volatility, but a change in the EPU of the U.S., Japan, or Korea has no such effect. Moreover, changes in the China EPU are negatively associated with Bitcoin and Litecoin future volatility, which may imply that Bitcoin and Litecoin are hedging tools against the EPU risk. However, changes in China EPU may not affect the cryptocurrency volatility after the Chinese government’s regulation of cryptotrading. JEL: C22, G15, D81 Keywords: Bitcoin, Cryptocurrencies, Economic policy uncertainty, China, Volatility
＊
Hui-Pei Cheng ([email protected]) and Kuang-Chieh Yen ([email protected]) are both Assistant Professors in Department of Economics at Soochow University, Taiwan. Hui-Pei Cheng is the corresponding author. The authors are grateful to the Ministry of Science and Technology of Taiwan for the financial support provided for this study
2
1. Introduction Recent research has explored the predictors of the return on cryptocurrency, since cryptocurrency is increasingly popular with investors because it can act as an alternative financial asset in financial markets. Predictors could be classified into two types: market-based and macro-based factors. Market-based factors include technical indicators (Gerritsen et al., 2019), the three factors of the crypto-pricing model (Shen et al., 2019), and volatility indexes in stock markets (Bouri et al., 2017). Macroeconomic factors include global economic activity (Cheng and Yen, 2019a) and economic policy uncertainty (Demir et al., 2018; Cheng and Yen, 2019b). The economic policy uncertainty index (EPU) of Baker et al. (2016) is considered an important factor in the cryptocurrency market. Demir et al. (2018) observe that uncertainty regarding government decisions can make investors lose trust in their fiat currencies or worry about the overall economy, in particular after the 2008 financial crisis. Thus, a change in the EPU may cause investors to reconsider their portfolio to avoid potential wealth loss. Although the above studies have explored whether the EPU is related to Bitcoin returns, no studies have compared the predictive power of national EPU across countries on cryptocurrency volatility. Therefore, this paper investigates which country’s EPU may play an important role in predicting cryptocurrency volatility. In this paper, we develop two hypotheses based on investor behaviours. The first hypothesis is based on the fear of the investors in the crypto-market. An increase in the EPU will make investors feel that the market conditions of the cryptocurrency are worsening. They may thus move their money from the cryptocurrency market to other financial markets if they think that cryptocurrency returns are negatively related to the
3
economic policy uncertainty. 1 This cash outflow will make the crypto-market less liquid and exaggerate the volatility of the cryptocurrency in the future. The second hypothesis emphasises the hedging effect on the volatility of the cryptocurrency. When the economic uncertainty increases, investors may invest their money in a cryptocurrency if they consider the cryptocurrency to be a safe haven asset. Therefore, the cash inflow to the cryptocurrency market will make the crypto-market more liquid and reduce the volatility of the cryptocurrency in the future. Practically, to avoid the effects of the persistent and mean-reverting property of the volatility, we modify the stochastic volatility model from Wang and Yen (2019) to examine whether national EPU can drive cryptocurrency volatility and test our two hypotheses. We include the EPU of the United States (U.S.), China, Japan, and (South) Korea.2 Our main findings show that only a change in the China EPU is significantly and negatively associated with the future volatility of Bitcoin and Litecoin. This may occur because China possesses the largest mining pools in the world (Ma, et al., 2018). In addition, we do not detect a clear effect of a change in China EPU on the volatility of the Bitcoin after the China government’s crypto-ban policy after September 2017. Overall, our empirical results support that the hedging hypothesis. Therefore, this paper suggests that the cryptocurrency could be a hedge asset against EPU risk. This paper contributes to the literature on volatility forecasting of cryptocurrency in two ways. First, we discuss volatility forecasting using the effect of national EPU on the cryptocurrency market and identify which country is relevant to cryptocurrency volatility. Second, based on our empirical results, we show that cryptocurrency can be a good hedging tool against EPU risk. 1
See the detail discussion in Demir et al. (2018). The four countries are important to the development of the crypto-market. For instance, the U.S. has the largest trading capacity of the Bitcoin futures. Both Japan and Korea, relative to other countries, implement complete regulations for crypto-trade. Furthermore, China has the largest Bitcoin mining pools in the world. 2
4
The remainder of this paper is structured as follows. Section 2 discusses the data, hypothesis and the empirical approach while Section 3 discusses the estimation results. Section 4 concludes.
2. Data, Hypothesis and Empirical Approach 2.1 Data We obtain the daily price of Bitcoin (BTC), Litecoin (LTC), and Ripple (XRP), from the coinmarketcap website. 3 The monthly volatility is calculated as the daily returns in each month. The EPU of China, the United States, Japan, and Korea as constructed by
Baker,
et
al.
(2016)
are
obtained
from
the
website
(http://www.policyuncertainty.com). Based on our available database, the sample period runs from February 2014 to June 2019.
2.2 Hypothesis Development In this section, we develop two hypotheses that discuss how EPU is related to cryptocurrency future volatility. Hypothesis 1:
The fear hypothesis in the crypto-market: EPU will have positive predictive power for cryptocurrency volatility. Investors may short their cryptocurrency position and long other financial assets due to their worries about the current situation in the cryptomarket. The cash outflow will make the crypto-market less illiquid and exaggerate the future volatility of the cryptocurrency.
Hypothesis 2:
Hedging hypothesis in the crypto-market: EPU will have negative predictive power for cryptocurrency volatility. Investors may invest more in the crypto-market if they consider the cryptocurrency to be a safe haven asset. Thus, the cash inflow will make the crypto-market more liquid and decrease the volatility of the cryptocurrency.
3
See for more detail in the website (https://coinmarketcap.com/)
5
2.3 Empirical Approach To develop our empirical strategy, we modify the stochastic volatility model of Wang and Yen (2019) as follows: ( where
)
√
is the variance mean-reverting speed;
volatility of the volatility;
,
(1)
is the mean of variance;
is the Brownian innovations; and
is the
is the stochastic
variance jump term. Without the loss of generality, we ignore the stochastic variance jump term (
) to simplify the model complexity. We then discretize the Eq. (1) as
follows. (
)
(
The first difference term, Moreover, the term,
)
√ (
)
(2)
, control for the variance persistent property. , controls for the mean-reverting property of the variance.
We expect that the corresponding coefficient ( ) will be positive. The last term, √ (
) , may be considered an error term that follows the normal
distribution with zero mean. Based on the Eq. (2), we form our regression model: ( where
)
∑
(3)
is the specific cryptocurrency volatility which is measured by the monthly
variance that is calculated by the daily returns at time ; and period;
;
is the difference between
is the specific cryptocurrency’s average variance during our sample is the change rate of the EPU of different country including China,
U.S., Japan, and Korea at time t; is the error term at time t.
is the vector of year and quarter dummies; and
is corresponding to the coefficient
thus it is expected to be positive.
, and
6
in the Eq. (2) and
measure the relationship between the
change in EPU of different country and the crypto-volatility. We adopt the NeweyWest standard errors to eliminate the potential heterogeneity and autocorrelation problems (Newey and West, 1987).
3. Empirical Results 3.1 The Effect of EPU on Bitcoin Volatility In this section, we apply Eq. (3) to investigate whether the EPU of these four countries (China, U.S., Japan, and Korea) can predict the Bitcoin monthly volatility. In Table 1, the coefficient In Table 2, the coefficients of those lagged terms of China ( In Table 3, we find that the coefficients ( However, the results in Table 4 indicate that all the coefficients In Table 5, the coefficient of the China EPU lagged term, In Table 6, the coefficients,
Economic Policy Uncertainty and Cryptocurrency Volatility Kuang-Chieh Yen , Hui-Pei Cheng PII: DOI: Reference:
S1544-6123(19)31018-9 https://doi.org/10.1016/j.frl.2020.101428 FRL 101428
To appear in:
Finance Research Letters
Received date: Revised date: Accepted date:
19 September 2019 18 November 2019 8 January 2020
Please cite this article as: Kuang-Chieh Yen , Hui-Pei Cheng , Economic Policy Uncertainty and Cryptocurrency Volatility, Finance Research Letters (2020), doi: https://doi.org/10.1016/j.frl.2020.101428
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. © 2020 Published by Elsevier Inc.
Highlights
This paper investigates whether the economic policy uncertainty (EPU) index provided by Baker et al. (2016) can predict cryptocurrency volatility.
We show that the China EPU index can predict negatively the Bitcoin monthly volatility.
China’s ban on crypto-trading does not result in a response in the volatility of Bitcoin.
1
Economic Policy Uncertainty and Cryptocurrency Volatility Kuang-Chieh Yen and Hui-Pei Cheng ＊ November 2019
Abstract We investigate the relationship between the economic policy uncertainty index (EPU) and cryptocurrency volatility. We find that a change in EPU of China predicts cryptocurrency volatility, but a change in the EPU of the U.S., Japan, or Korea has no such effect. Moreover, changes in the China EPU are negatively associated with Bitcoin and Litecoin future volatility, which may imply that Bitcoin and Litecoin are hedging tools against the EPU risk. However, changes in China EPU may not affect the cryptocurrency volatility after the Chinese government’s regulation of cryptotrading. JEL: C22, G15, D81 Keywords: Bitcoin, Cryptocurrencies, Economic policy uncertainty, China, Volatility
＊
Hui-Pei Cheng ([email protected]) and Kuang-Chieh Yen ([email protected]) are both Assistant Professors in Department of Economics at Soochow University, Taiwan. Hui-Pei Cheng is the corresponding author. The authors are grateful to the Ministry of Science and Technology of Taiwan for the financial support provided for this study
2
1. Introduction Recent research has explored the predictors of the return on cryptocurrency, since cryptocurrency is increasingly popular with investors because it can act as an alternative financial asset in financial markets. Predictors could be classified into two types: market-based and macro-based factors. Market-based factors include technical indicators (Gerritsen et al., 2019), the three factors of the crypto-pricing model (Shen et al., 2019), and volatility indexes in stock markets (Bouri et al., 2017). Macroeconomic factors include global economic activity (Cheng and Yen, 2019a) and economic policy uncertainty (Demir et al., 2018; Cheng and Yen, 2019b). The economic policy uncertainty index (EPU) of Baker et al. (2016) is considered an important factor in the cryptocurrency market. Demir et al. (2018) observe that uncertainty regarding government decisions can make investors lose trust in their fiat currencies or worry about the overall economy, in particular after the 2008 financial crisis. Thus, a change in the EPU may cause investors to reconsider their portfolio to avoid potential wealth loss. Although the above studies have explored whether the EPU is related to Bitcoin returns, no studies have compared the predictive power of national EPU across countries on cryptocurrency volatility. Therefore, this paper investigates which country’s EPU may play an important role in predicting cryptocurrency volatility. In this paper, we develop two hypotheses based on investor behaviours. The first hypothesis is based on the fear of the investors in the crypto-market. An increase in the EPU will make investors feel that the market conditions of the cryptocurrency are worsening. They may thus move their money from the cryptocurrency market to other financial markets if they think that cryptocurrency returns are negatively related to the
3
economic policy uncertainty. 1 This cash outflow will make the crypto-market less liquid and exaggerate the volatility of the cryptocurrency in the future. The second hypothesis emphasises the hedging effect on the volatility of the cryptocurrency. When the economic uncertainty increases, investors may invest their money in a cryptocurrency if they consider the cryptocurrency to be a safe haven asset. Therefore, the cash inflow to the cryptocurrency market will make the crypto-market more liquid and reduce the volatility of the cryptocurrency in the future. Practically, to avoid the effects of the persistent and mean-reverting property of the volatility, we modify the stochastic volatility model from Wang and Yen (2019) to examine whether national EPU can drive cryptocurrency volatility and test our two hypotheses. We include the EPU of the United States (U.S.), China, Japan, and (South) Korea.2 Our main findings show that only a change in the China EPU is significantly and negatively associated with the future volatility of Bitcoin and Litecoin. This may occur because China possesses the largest mining pools in the world (Ma, et al., 2018). In addition, we do not detect a clear effect of a change in China EPU on the volatility of the Bitcoin after the China government’s crypto-ban policy after September 2017. Overall, our empirical results support that the hedging hypothesis. Therefore, this paper suggests that the cryptocurrency could be a hedge asset against EPU risk. This paper contributes to the literature on volatility forecasting of cryptocurrency in two ways. First, we discuss volatility forecasting using the effect of national EPU on the cryptocurrency market and identify which country is relevant to cryptocurrency volatility. Second, based on our empirical results, we show that cryptocurrency can be a good hedging tool against EPU risk. 1
See the detail discussion in Demir et al. (2018). The four countries are important to the development of the crypto-market. For instance, the U.S. has the largest trading capacity of the Bitcoin futures. Both Japan and Korea, relative to other countries, implement complete regulations for crypto-trade. Furthermore, China has the largest Bitcoin mining pools in the world. 2
4
The remainder of this paper is structured as follows. Section 2 discusses the data, hypothesis and the empirical approach while Section 3 discusses the estimation results. Section 4 concludes.
2. Data, Hypothesis and Empirical Approach 2.1 Data We obtain the daily price of Bitcoin (BTC), Litecoin (LTC), and Ripple (XRP), from the coinmarketcap website. 3 The monthly volatility is calculated as the daily returns in each month. The EPU of China, the United States, Japan, and Korea as constructed by
Baker,
et
al.
(2016)
are
obtained
from
the
website
(http://www.policyuncertainty.com). Based on our available database, the sample period runs from February 2014 to June 2019.
2.2 Hypothesis Development In this section, we develop two hypotheses that discuss how EPU is related to cryptocurrency future volatility. Hypothesis 1:
The fear hypothesis in the crypto-market: EPU will have positive predictive power for cryptocurrency volatility. Investors may short their cryptocurrency position and long other financial assets due to their worries about the current situation in the cryptomarket. The cash outflow will make the crypto-market less illiquid and exaggerate the future volatility of the cryptocurrency.
Hypothesis 2:
Hedging hypothesis in the crypto-market: EPU will have negative predictive power for cryptocurrency volatility. Investors may invest more in the crypto-market if they consider the cryptocurrency to be a safe haven asset. Thus, the cash inflow will make the crypto-market more liquid and decrease the volatility of the cryptocurrency.
3
See for more detail in the website (https://coinmarketcap.com/)
5
2.3 Empirical Approach To develop our empirical strategy, we modify the stochastic volatility model of Wang and Yen (2019) as follows: ( where
)
√
is the variance mean-reverting speed;
volatility of the volatility;
,
(1)
is the mean of variance;
is the Brownian innovations; and
is the
is the stochastic
variance jump term. Without the loss of generality, we ignore the stochastic variance jump term (
) to simplify the model complexity. We then discretize the Eq. (1) as
follows. (
)
(
The first difference term, Moreover, the term,
)
√ (
)
(2)
, control for the variance persistent property. , controls for the mean-reverting property of the variance.
We expect that the corresponding coefficient ( ) will be positive. The last term, √ (
) , may be considered an error term that follows the normal
distribution with zero mean. Based on the Eq. (2), we form our regression model: ( where
)
∑
(3)
is the specific cryptocurrency volatility which is measured by the monthly
variance that is calculated by the daily returns at time ; and period;
;
is the difference between
is the specific cryptocurrency’s average variance during our sample is the change rate of the EPU of different country including China,
U.S., Japan, and Korea at time t; is the error term at time t.
is the vector of year and quarter dummies; and
is corresponding to the coefficient
thus it is expected to be positive.
, and
6
in the Eq. (2) and
measure the relationship between the
change in EPU of different country and the crypto-volatility. We adopt the NeweyWest standard errors to eliminate the potential heterogeneity and autocorrelation problems (Newey and West, 1987).
3. Empirical Results 3.1 The Effect of EPU on Bitcoin Volatility In this section, we apply Eq. (3) to investigate whether the EPU of these four countries (China, U.S., Japan, and Korea) can predict the Bitcoin monthly volatility.