Bitcoin return: Impacts from the introduction of new altcoins

Nội dung text: Bitcoin return: Impacts from the introduction of new altcoins

1. BITCOIN RETURN: IMPACTS FROM THE INTRODUCTION OF NEW ALTCOINS Nguyen Cong Thanh1, Phung Truong Thinh2 1School of Accounting–Finance–Banking, Ho Chi Minh City University of Technology 2School of Economics, University of Economics and Finance ABSTRACT The model predicting Bitcoin price formation remains a mystery to academia and investors. Newly invented cryptocurrencies (alternative coins – altcoins) with enhanced features may be-come close substitutes to Bitcoin in terms of risk diversification. Employing Autoregressive-Distributed-Lag (ARDL) estimations, we document the evidence that the introduction of a new altcoin tends to lower Bitcoin return by 0.7% which is substantial given that the average and median daily returns of Bitcoin are 0.63% and 0.27%, respectively. Our study suggests that the negative impact of an Initial Public Offering on existing stock prices can also be observed in the cryptocurrency market: altcoin introductions reduce Bitcoin return. Keywords: Bitcoin, Altcoins, Price formation. 1. INTRODUCTION Bitcoin has recently been observed to function more as a speculative asset than a medium of exchange [1]. With low spreads and sufficient market depth, Bitcoin is argued to be an investible asset [2]. The research on Bitcoin price formation is growing and the extant literature provides evidence that Bitcoin exhibits relatively independent price behaviour from other traditional financial assets, such as stocks, bonds and commodities, and hence, may become beneficial to portfolio di-versification purposes [1, 3]. However, Bitcoin is found to influence the price performance of other alternative cryptocurrencies (altcoins) [4], which suggests the high price correlation between Bitcoin and altcoins. Fry and Cheah [5] find evidence of a spillover effect from Ripple (an altcoin) to Bitcoin during negative bubbles, which ex-acerbates subsequent price falls in Bitcoin. Even though Bitcoin has the largest market capitalization, other top cryptocurrencies‟ returns may be higher from time to time, suggesting certain levels of competition among cryptocurrencies [6]. We raise the question whether the introduction of new altcoins will affect the price of Bitcoin. The answer to this question will reveal whether speculators view altcoins as substitutes to Bitcoin for risk diversification purposes. The literature has documented the negative impacts of the introduction of new stocks to existing stock prices [7], yet, this topic remains unexplored in the cryptocurrency market. Although Bitcoin price formation is uncorrelated with traditional financial assets [1, 3], the impacts of Initial Public Offerings (IPOs) on stock prices may provide implications to the relationship between new altcoins introduction and Bitcoin return. Braun and Larrain [7] developed a framework conceptualizing the negative impact of IPOs on the prices of existing assets in the stock market. The adverse effect of IPOs will be permanent if investors rebalance their portfolios by replacing their current holdings with newly introduced assets [7]. In line with this argument, Braun and Larrain [7] find that the price depressing effect from IPOs is stronger on assets that are highly correlated with those IPOs. On the other hand, the effect will be transitory as 303
2. IPOs absorb market liquidity, and hence sizable IPOs have been found to negatively affect the whole stock market performance [8]. While Braun and Larrain [7] and Shi, Sun [8] view the IPO effect from the supply side, Li, Sun [9] argue that the demand effect also exists as investors adjust their portfolios in the expectation of IPOs. Li, Sun [9] find evidence that the negative impact of IPOs on stock markets occur around IPO approval announcement dates although no IPO shares are actually traded at that time. Hsu, Reed [10] also document that IPOs with new competitive advantages, such as knowledge capital, deplete not only industry competitors‟ stock prices but also their operating performance. Although altcoins are developed on similar blockchain technology as Bitcoin, the former present some competitive features4 compared to Bitcoin (see Ciaian and Rajcaniova [4]). Therefore, one would argue that speculators may adjust their portfolios in the expectation of the enhanced features of new altcoins, causing Bitcoin price decrease. We empirically test this argument by examining the impacts of the introduction of new altcoins on Bitcoin return. This study contributes to the literature on two fronts. First, the study extends the theories on portfolio adjustment behaviours of investors on stock markets to the cryptocurrency market. Second, the study sheds light on the substitutability of altcoins for Bitcoin from investors‟ perspective. The study finds that during the introduction period of a new altcoin, Bitcoin return falls significantly. This suggests that investors adjust down their Bitcoin holdings in the expectation of new altcoins with some enhanced features. The remainder of the study is structured as followings: section two presents methodology and data, section three discusses the regression results, followed by concluding remarks in section four. 2. DATA AND METHODOLOGY We use daily data from 04/28/2013 to 08/15/2018 (1936 observations). Data on Bitcoin and altcoins are from coin-marketcap.com, whereas the macroeconomic variables are fetched from the Federal Reserve Economic Data (FRED), the European Central Bank and the World Gold Council. Table 1 displays the descriptive statistics of all variables. The dummy variable New Coin takes the value of one for the period of one day before, on the day, and one day after the first trading day of an altcoin (and zero otherwise). Our sample includes the 62 largest altcoins in terms of market capitalization in the cryptocurrency market, with the smallest one (MintCoin) having a value of 2,361,768 USD (on 15 August 2018). The list of those 62 altcoins can be found in Appendix 1. Bitcoin returns are calculated as the percentage change in the average Bitcoin price on a daily basis. Augmented Dickey-Fuller (ADF) tests indicate that all variables are either integrated of order one (I(1)) or zero (I(0)). Table 1. Descriptive statistics of all variables ADF test ADF test statistic of Variable Mean Std. Dev. Min Max statistic first difference BTC return 0.634 2.847 −11.493 28.015 −9.9138 −17.216 NewCoin 0.084 0.277 0 1 −18.764 −44.921 BTC Supply 1.47E+07 1,803,499 −1.11E+07 1.72E+07 −2.802 −3.513 BTC 23,800.86 31,155.91 6023 347,624 −3.117 −21.105 Demand 4 Ciaian et al. (2018) summarises the evolvement of altcoins, for example, Litecoin is more energy efficient, Peercoin improves currency security, Dash enhances privacy protection, Bitshares and Ethereum support smart contracts. 304
3. ADF test ADF test statistic of Variable Mean Std. Dev. Min Max statistic first difference GoldPrice 1251.94 75.8205 1050.6 1476.5 −1.684 −32.997 NASDAQ 4731.05 1147.15 2848.2 7508.59 −2.864 −35.483 OilPrice 69.196 25.523 26.01 117.15 −3.743 −34.397 Yuan_USD 6.414 0.266 6.04 6.958 −1.232 −32.388 USD_EUR 1.193 0.104 1.037 1.392 −2.034 −35.140 Treasury 2.265 0.446 1.277 3.11 −2.547 −34.425 Rate The table summarizes the descriptive and Augmented Dickey-Fuller test statistics of all variables for the sample period. indicates the rejection of the null hypothesis of the variable containing a unit root at 1% level, at 5% level and * at 10% level. Figure 1. New coins, Bitcoin price and return, 2018M1–2018M4. The shaded areas denote the periods with New Coin events Figure 1 depicts the introductions of new altcoins, Bitcoin price and return for the period 2018M1– 2018M4. On the New Coin events, Bitcoin prices and returns are substantially decreased5. For example, in January 2018, Bitcoin return fell by 11% and 8% during the introduction periods of IOST coin and MOAC coin, respectively. Table 2 further strengthens this anecdotal evidence: The New Coin variable is significantly negatively correlated with Bitcoin return. 5 The figure focusses on the most recent coin introductions, but similar patterns can be observed for other periods as well. 305
4. To test whether the New Coin events significantly affect Bitcoin return, we estimate Autoregressive- Distributed-Lag (ARDL) models with the following form6. pq T BitcoinReturnt   i BitcoinReturn t 1  NewCoin t  i X t i EC Term u t ii 10 T Where X ti contains the first difference of all control variables, i is the corresponding coefficient vector and ut is a random error term. Moreover, we also allow for a long-run relationship among the variables by including an error correction term ( EC Term) in the spirit of Pesaran, Shin [11]. We account for the findings of previous studies and use a large set of control variables including Bitcoin supply (number of coins), Bitcoin demand (Wikipedia reads on Bitcoin), Gold price, the NASDAQ index, Oil price, US treasury rate, the Yuan/USD and the USD/EUR exchange rates. 3. ESTIMATION RESULTS Table 3 reports estimation results for different specifications of equation (1). Model 1 and Model 2 do not include the auto-regressive component of Bitcoin return and include only the first lag of the control variables in the estimations. Model 3, Model 4 and Model 5 account for the lags of Bitcoin return, the control variables as well as the error correction term,4 with Model 5 excluding Bitcoin demand variable which is only available since July 2015. The numbers of lags are chosen by the Schwarz information criterion. In all five estimations, the introduction of a new altcoin has a significant and negative impact on Bitcoin return. In particular, a New Coin event reduces Bitcoin return by roughly 0.7%. This amount is quite substantial considering that the average and median daily returns of Bitcoin are 0.63% and 0.27%, respectively. These results suggest that investors may (partly) substitute Bitcoin and invest in new altcoins to diversify their cryptocurrency risk instead of holding Bitcoin only. In addition, the error correction terms in Model 3, Model 4 and Model 5 are highly significant and this result is line with the findings of Ciaian and Rajcaniova [4] who find long-term relationships between Bitcoin price, alternative coin price and macroeconomic variables. 6 Ciaian et al. (2018) estimate a similar econometric model to test for long-run and short-run relationships in the prices of Bitcoin and alternative cryptocurrencies. Since all variables are I(1) or I(0) we also believe that ARDL models are appropriate to capture the relationships of the variables. 306
5. Table 3. The impact of New Coin introductions on Bitcoin return using OLS OLS BTC Return Model 1 Model 2 -0.725 -0.731 NewCoin (0.250) (0.252) -0.000100 -0.000110 BTC Supply (7.84e-05) (7.89e-05) 4.23e-05 4.27e-05 BTC Demand (7.79e-06) (7.81e-06) 0.0167* GoldPrice (0.0101) -0.00207 NASDAQ (0.00185) -0.0610 OilPrice (0.0876) -1.056 Yuan_USD (6.933) -15.12 USD_EUR (17.03) 0.378 Treasury Rate (2.518) 0.957 0.989 Constant (0.218) (0.220) Observations 1,096 1,096 R-squared 0.035 0.039 Adjusted R-squared 0.032 0.031 F-statistic 13.17 4.940 Prob. 0.000 0.000 Standard errors in parentheses p<0.01, p<0.05, * p<0.1 307
6. Table 4. The impact of New Coin introductions on Bitcoin return using ARDL Model 3 Model 4 Model 5 BTC Return Short-run Long-run Short-run Long-run Short-run Long-run -0.675 -1.018 -0.712 -1.061 -0.764 -1.344 NewCoin (0.219) (0.336) (0.229) (0.347) (0.204) (0.364) 0.145 0.149328 0.105 Bitcoin Return L(1) (0.037) (0.037) (0.029) -0.132 -0.131808 -0.170944 Bitcoin Return L(2) (0.033) (0.033) (0.025) 0.000 0.000 0.000 0.000 0.000 0.000 Bitcoin Supply (0.000) (0.000) (0.000) (0.000) (0.000) (0.000) 0.00003 0.000022 0.00003 0.00002 Bitcoin Demand (0.000) (0.000) (0.000) (0.000) -0.00003 -0.00003 Bitcoin Demand L(1) (0.000008) (0.000008) -0.661 -0.671 -0.568 Error correction term (0.043) (0.043) (0.031) -0.00168 -0.002504 -0.000427 -0.000751 GoldPrice (0.002) (0.003) (0.001) (0.002) -0.000164 -0.000244 0.000067 0.000118 NASDAQ (0.000) (0.000) (0.000161) (0.000283) 0.010175 0.015169 0.000276 0.000486 OilPrice (0.016) (0.024) (0.008557) (0.015058) 1.080945 1.611482 0.709* 1.248* Yuan_USD (0.779) (1.160) (0.411) (0.719) 3.880458 5.785022 1.734176 3.051683 USD_EUR (4.135) (6.166) (1.728) (3.034) -0.053004 -0.079019 0.010422 0.01834 Treasury Rate (0.474) (0.347) (0.224) (0.394) Constant 0.038 -12.75 -10.54 (1.462) (10.82) (5.212) Observations 1006 1006 1669 Durbin-Watson stat 1.872 1.873 1.833 R-squared 0.249 0.251 0.241 Adjusted R-squared 0.242 0.24 0.236 F-statistic 41.22 23.71 47.87 Prob. 0.000 0.000 0.000 ARDL Bound Test I0 Bound I1 Bound I0 Bound I1 Bound I0 Bound I1 Bound Critical Value 10% 3.17 4.14 1.95 3.06 1.95 3.06 5% 3.79 4.85 2.22 3.39 2.22 3.39 2.50% 4.41 5.52 2.48 3.7 2.48 3.7 1% 5.15 6.36 2.79 4.1 2.79 4.1 F-statistic 79.67 26.89 36.66 Standard errors are in brackets. indicates significant impact at 1% level, at 5% level and * at 10% level. 308
7. 4. CONCLUDING REMARKS Although Bitcoin is the largest cryptocurrency with regard to market capitalization, it is vulnerable to potential competition from the introduction of new altcoins as investors tend to balance down Bitcoin holding. Our study finds that the negative impact of new altcoin introduction is significant and substantial relative to average/median Bitcoin daily returns. This finding is interesting as it indicates that the negative price effect of IPOs on existing stock prices can also be observed in the cryptocurrency market when new altcoins are introduced. APPENDIX 1 LIST OF 62 ALTCOINS Altcoin Altcoin name First trading date ETH Ethereum 08/08/2015 XRP Ripple 04/08/2013 LTC Litecoin 28/04/2013 ADA Cardano 01/10/2017 BCH Bitcoin Cash 23/07/2017 BNB Binance Coin 25/07/2017 BTS BitShares 21/07/2014 DASH Dash 14/02/2014 DOGE Dogecoin 15/12/2013 EOS EOS 01/07/2017 ETC Ethereum Classic 24/07/2016 IOTA IOTA 13/06/2017 MINT MintCoin 19/02/2014 NEO NEO 09/09/2016 NMC Namecoin 28/04/2013 NVC Novacoin 29/04/2013 NXT Nxt 04/12/2013 PPC Peercoin 29/04/2013 TRX TRON 13/09/2017 USDT Tether 25/02/2015 XCP Counterparty 17/02/2014 XEM NEM 01/04/2015 XLM Stellar 05/08/2014 XMR Monero 06/06/2014 ZEC Zcash 29/10/2016 OMG OmiseGO 14/07/2017 LSK Lisk 06/04/2016 ZRX 0x 16/08/2017 NANO Nano 30/03/2017 BCN Bytecoin 18/06/2014 BTG Bitcoin Gold 23/10/2017 ICX ICON 27/10/2017 ZIL Zilliqa 25/01/2013 QTUM Qtum 24/05/2017 DCR Decred 10/02/2016 DGB DigiByte 06/02/2014 309
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