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June 2019 Cryptocurrency Market Report

June 2019 Cryptocurrency Market Report

By | Advanced Market Report, Coinscious Lab, Data Analytics | No Comments

Overview

June was an exciting month for cryptocurrencies. The price of Bitcoin, the first and largest cryptocurrency by market capitalization, crossed the $9000, $10000, and $11000 mark all in one month. Bitcoin last traded around the $11000 price level in March 2018 during the bear market that followed after peaking in December 2017. This year’s long bear market, dubbed by many as the “crypto winter” appears to be definitively over following cryptocurrency’s steady resurgence and the crossing of these major psychological thresholds by Bitcoin. 

Bitcoin rose 44.41% in June 2019, and most other cryptocurrencies that we analyzed had positive returns as well.

Cryptocurrency Market Developments in June 2019

Various developments related to new cryptocurrencies and blockchain projects may be responsible for the bullishness surrounding cryptocurrencies this month. In particular, these projects are led by high-profile organizations, raising the interest and demand for cryptocurrencies in general, as well as legitimizing the cryptocurrency space to previously unconvinced market participants.

Global risks and uncertainties may also be making cryptocurrencies more popular as a safe haven.

Cryptocurrency Market Developments in June 2019

Performance

Exhibit 1: Monthly returns of cryptocurrencies over the past year.

Cryptocurrency Market - Monthly Returns Over Past Year

Best and Worst Performers

Performance of cryptocurrencies across two different time frames – June 2018 to June 2019, and only June 2019 – are presented below. Cryptocurrencies that had the highest total returns, lowest total returns, and highest Sharpe ratio are highlighted. In addition, other metrics such as rate of return, alpha, and beta (relative to the Bitwise 100) are shown all as daily, non-annualized values.

Exhibit 2: Cryptocurrencies with the highest total returns in June 2019.

Cryptocurrencies with the highest total returns in June 2019.
  • ChainLink (LINK) had the highest total return in June 2019.
  • LINK is a decentralized data oracle designed to provide reliable real-world data inputs for smart contracts.
  • Recent positive developments for the cryptocurrency in June include an article by Google Cloud titled ““Building hybrid blockchain/cloud applications with Ethereum and Google Cloud” that mentioned LINK, and a new listing on cryptocurrency exchange, CoinbasePro.

Exhibit 3: Cryptocurrencies with the lowest total returns in June 2019.

Cryptocurrencies with the lowest total returns in June 2019
  • Tezos (XTZ) had the lowest total return in June 2019.
  • XTZ is a self-amending proof-of-work dApp platform with built-in mechanisms designed to remove the need to hard fork when implementing protocol amendments.

Exhibit 4: Cryptocurrencies with the highest total returns from June 2018 to June 2019.

Cryptocurrencies with the highest total returns from June 2018 to June 2019. 
  • In addition to being the cryptocurrency with the highest total return in the past year, LINK also had the highest total return over the past year. LINK beat out the next best cryptocurrency, Binance Coin (BNB) by a huge order of magnitude.
  • Bitcoin (BTC) was the third best performing cryptocurrency.

Exhibit 5: Cryptocurrencies with the lowest total returns from June 2018 to June 2019.

Cryptocurrencies with the lowest total returns from June 2018 to June 2019.
  • Pundi X (NPXS) had the lowest total return in the past year.
  • NPXS is a token used for payments and settlements. It is also integrated with their own physical point-of-sale devices.

Exhibit 6: Cryptocurrencies with the largest Sharpe Ratios in June 2019.

Cryptocurrencies with the largest Sharpe Ratios in June 2019
  • HyperCash (HC) had the best performance relative to its risk in June 2019 as measured by the Sharpe ratio.
  • HC belongs to an emerging class of cryptocurrencies called “sidechains” which facilitate the transfer of digital assets between other blockchains.

Exhibit 7: Cryptocurrencies with the largest Sharpe Ratios from June 2018 to June 2019.

Cryptocurrencies with the largest Sharpe Ratios from June 2018 to June 2019. 
  • ChainLink (LINK) had the best performance relative to its risk in the past year as measured by the Sharpe ratio.

Risk vs. Return

Mean Daily Return vs. Daily Volatility

Exhibits 8 and 9 present the risk versus return trade-off by plotting mean daily return versus historical daily volatility for various cryptocurrencies. Higher returns at a given level of risk, measured through historical daily volatility, indicate a relatively better investment.

Exhibit 8: Plot of mean daily return against historical daily volatility for individual cryptocurrencies in June 2019.

Cryptocurrencies June 2019 - Mean daily return vs historical daily volatility
  • ChainLink (LINK) had both the highest mean return and volatility overall.
  • The cluster of cryptocurrencies with close to 0% mean returns and volatility are stablecoins, including Tether (USDT), Paxos Standard Token (PAX), TrueUSD (TUSD), and USD Coin (USDC).

Exhibit 9: Plot of mean daily return against historical daily volatility for individual cryptocurrencies from June 2018 to June 2019.

Cryptocurrencies June 2018 to June 2019 - Mean daily return vs historical daily volatility
  • ChainLink (LINK) was identified earlier as having the best Sharpe ratio – here it can be visualized through LINK’s higher mean daily returns compared to other cryptocurrencies with a similar daily volatility.

Value Comparison using CAPM

Previously, we presented a comparison of risk versus return measured by the mean daily volatility and mean daily return, respectively. To build upon the idea of compensating investors sufficiently for a given level of risk, we apply the Capital Asset Pricing Model (CAPM) to determine what is the threshold required return for a cryptocurrency to be worth its risk.

We quantified the systematic risk of individual cryptocurrencies by calculating its beta over the past year. Higher positive betas indicate that the cryptocurrency is more volatile than the market, whereas negative betas indicate that the cryptocurrency moves against the market. The Bitwise 100 cryptocurrency index, a market capitalization weighted index of the top 100 cryptocurrencies, was used as a proxy for the market portfolio in beta calculations.

In Exhibit 10, we plotted individual cryptocurrencies’ beta versus expected return, which was calculated as the daily rate of return using data from June 2018 to June 2019, and assume that historic returns are a sufficiently good measure of future returns. In addition, using the risk-free rate and the expected returns of the Bitwise 100, we constructed a Security Market Line that represents the fair expected return that an investor should be compensated for a cryptocurrency with a given beta.

Using this model, cryptocurrencies above the Security Market Line are theoretically undervalued, and cryptocurrencies below the Security Market Line are overvalued.

Exhibit 10: Plot of the expected return against beta for individual cryptocurrencies and the Security Market Line, calculated with daily returns from June 2018 to June 2019.

Plot of the expected return against beta for individual cryptocurrencies and the Security Market Line, calculated with daily returns from June 2018 to June 2019.
  • Chainlink (LINK) is theoretically the most underpriced and would provide the best value, with its high expected return relative to its systematic risk.
  • Some other cryptocurrencies identified as being underpriced are Bitcoin SV (BSV), Binance Coin (BNB), Bitcoin (BTC), HyperCash (HC), Litecoin (LTC), Dogecoin (DOGE), and Basic Attention Token (BAT).

Correlations

Exhibits 11 to 16 show the overall and rolling 30-day correlation from the past year of the top three cryptocurrencies by market capitalization, the S&P 500 and VIX indices, the Chinese Yuan (CNY) and gold prices.

Correlation measures the linear relationship between two series and can range between -1 and 1. More positive correlations indicate a stronger positive linear relationship while more negative correlations indicate a stronger negative linear relationship. A correlation of 0 or close to 0 indicates little to no linear relationship. 

Exhibit 11: Correlation between BTC, XRP, ETH, VIX, S&P 500, CNY, and gold daily returns from June 2018 to June 2019.

Correlation between BTC, XRP, ETH, VIX, S&P 500, CNY, and gold daily returns from June 2018 to June 2019.
  • The top three cryptocurrencies by market capitalization, Bitcoin (BTC), Ether (ETH), and XRP (XRP), are highly positively correlated with each other.
  • Cryptocurrencies and the S&P 500 are slightly positively correlated.
  • Cryptocurrencies and VIX are slightly negatively correlated.
  • Gold and Bitcoin (BTC), as well as Gold and Ether (ETH) are slightly negatively correlated.
  • CNY has a stronger correlation with XRP (XRP) than with other cryptocurrencies, although it is still a relatively small number.

Exhibit 12: Rolling 30-day correlation between BTC, XRP, ETH daily returns.

Rolling 30-day correlation between BTC, XRP, ETH daily returns.
  • Correlations between the three pairs of cryptocurrencies examined rarely dipped below 0.5.
  • In general, Bitcoin (BTC) and Ether (ETH) were usually more positively correlated than other pairs.

Exhibit 13: Rolling 30-day correlation between BTC, XRP, ETH daily returns and S&P500 daily returns.

Rolling 30-day correlation between BTC, XRP, ETH daily returns and VIX daily returns.

Exhibit 14: Rolling 30-day correlation between BTC, XRP, ETH daily returns and VIX daily returns.

Rolling 30-day correlation between BTC, XRP, ETH daily returns and VIX daily returns.

Exhibit 15: Rolling 30-day correlation between BTC, XRP, ETH daily returns and CNY daily returns.

Rolling 30-day correlation between BTC, XRP, ETH daily returns and CNY daily returns.

Exhibit 16: Rolling 30-day correlation between BTC, XRP, ETH daily returns and gold daily returns.

Rolling 30-day correlation between BTC, XRP, ETH daily returns and gold daily returns.

APPENDIX A: Cryptocurrency Symbols & Names

Below is a complete list of all cryptocurrencies examined in this report as well as their symbol to full name mapping.

Cryptocurrency Symbols and Names

APPENDIX B: Cryptocurrency Distribution Statistics

Below is a complete list of all cryptocurrencies examined in this market report. In addition, we present the mean, standard deviation (volatility), skewness, and kurtosis for each cryptocurrency’s daily returns from June 1, 2019 to June 30, 2019, and from June 30, 2018 to June 30, 2019. 

For cryptocurrencies where data did not reach all the way back to June 30, 2019, statistics were calculated only using as much historical data as was available.

Cryptocurrency Distribution Statistics
Cryptocurrency Distribution Statistics

APPENDIX C: Cryptocurrency Performance Metrics

Below is a complete list of all cryptocurrencies examined in this market report. In addition, we present the mean daily returns, historical daily volatility, total returns, and ex-post Sharpe ratio for each cryptocurrency from June 1, 2019 to June 30, 2019, as well as from June 30, 2018 to June 30, 2019.  Rate of return and Alpha are shown as daily, non-annualized values. Beta is calculated using the Bitwise 100 to represent the market portfolio.

Empty values in the Jun-2018 to Jun-2019 Total Return column indicate that data on the cryptocurrency from June 2018 was not available, hence that metric could not be calculated. Furthermore, for those cryptocurrencies, the remaining metrics were calculated only using as much historical data as was available.

Cryptocurrency Performance Metrics
Cryptocurrency Distribution Statistics

APPENDIX D: Data Sources

Our universe of analysis includes 50 of some of the most widely used and traded cryptocurrencies. Cryptocurrencies were selected on the basis of being in the top 50 cryptocurrencies by market capitalization according to CoinMarketCap data where Coinscious also had USD pricing data.

The daily price data of cryptocurrencies in USD at 4:00 PM EST from June 30, 2018 to June 30, 2019 was used for our calculations.

The prices are the volume weighted average price of the cryptocurrency in USD at 4:00 PM EST each day across all exchanges where Coinscious has data. The only exception is Siacoin (SC), where we used the Yahoo Finance price instead due to data quality issues at the time of writing.

Daily closing price data of the S&P500 index and VIX volatility index was obtained from Yahoo Finance. Bitwise 100 index data was provided by Bitwise Asset Management. The 10-year US Treasury bill rate on June 30, 2018 from YCharts was used for calculations involving a risk-free rate. Chinese Yuan to US Dollar rates were obtained from FRED. Gold prices are the morning gold fixing prices in London at 10:30 am, also obtained from FRED.

Disclaimer

The information contained herein is for informational purposes only and is not intended as a research report or investment advice. It should not be construed as Coinscious recommending investment in cryptocurrencies or other products or services, or as a solicitation to buy or sell any security or engage in a particular investment strategy. Investment in the crypto market entails substantial risk. Before acting on any information, you should consider whether it is suitable for your particular circumstances and consult all available material, and, if necessary, seek professional advice.

Coinscious and its partners, directors, shareholders and employees may have a position in entities referred to herein or may make purchases and/or sales from time to time, or they may act, or may have acted in the past, as an advisor to certain companies mentioned herein and may receive, or may have received, a remuneration for their services from those companies.

Neither Coinscious or its partners, directors, shareholders or employees shall be liable for any damage, expense or other loss that you may incur out of reliance on any information contained in this report. Chainlink

TERMINAL

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June 2019 Cryptocurrency Blockchain & Alert Signal Report

June 2019 Blockchain & Alert Signal Analysis

By | Blockchain & Alert Signal Report, Coinscious Lab, Data Analytics | No Comments

Overview

Released monthly, this report consists of the following two sections: 

  1. Blockchain transaction statistics and simple correlation analysis to Bitcoin (BTC)  price, and 
  2. Summary of alert system statistics from June 1, 2019 to June 30, 2019. 

Our blockchain transaction statistics are based on Coinscious’ blockchain data for BTC, Ethererum (ETH), and Tether (USDT). For our analysis, we filter out all transactions that are less than $100,000 USD, 25 BTC, and 750 ETH. Next, we compare the flow of transaction volumes in and out, as well as the transaction amounts throughout the month. We also visualize the net transaction trend using BTC daily price.

In our alert system summary, we look at signals produced by Coinscious’ alert system such as:

  • price pump and dump signals,
  • volume spike and drop signals, and 
  • relative strength indicator (RSI) signals at daily ticks. 

Here, we provide investigate statistics on BTC, ETH, and XRP for USD, CAD, and USDT currencies for different cryptocurrency exchanges. The summary statistics illustrates how often extreme events occur for each market. 

Blockchain Transaction

Figure 1. Price versus net transaction correlation for large-value outstanding transactions between June 1 to June 30, 2019.

Cryptocurrency Blockchain Transaction - Price versus net transaction correlation BTC, ETH, USDT

Figure 1 illustrates BTC price and blockchain transactions going in and out of cryptocurrency exchanges for BTC, ETH, and USDT.  

The first row in Figure 1 demonstrates that BTC price has steadily increased in June. The net USDT transactions into cryptocurrency exchanges are positive throughout June. Interestingly, we see a positive correlation between BTC price and ETH net transactions – the price of BTC rises when ETH net transaction is positive, and the price of BTC falls when ETH net transaction is negative. 

The third row in Figure 1 illustrates that USDT had the most active transactions in June, followed by BTC and ETH. However, even though ETH had the smallest number of transactions, its transaction size is the greatest, followed by BTC and USDT as shown in the second row of Figure 1. 

Alert Signal Analysis

a) Bitstamp { BTC, ETH, XRP } / USD

Figure 2. Price pump and dump signals, volume spike signals, and RSI (14) signals at Bitstamp for BTC/USD, ETH/USD and XRP/USD between June 1 to June 30, 2019.

Blockchain - Price pump and dump signals, volume spike signals, and RSI (14) signals at Bitstamp for BTC/USD, ETH/USD and XRP/USD between June 1 to June 30, 2019.

BTC/USD trading pair at Bitstamp had a total of 53 price pump signals and 48 price dump signals.  The average price change was -0.20% within 15 minutes, and the maximum and minimum price changes were 3.76% and -4.04%, respectively. 

ETH/USD trading pair had a total of 40 price pump signals and 47 price dump signals. The average price change was -0.08%, and the maximum and minimum price changes were 1.80% and -3.45%, respectively. 

XRP/USD trading pair had a total of 51 price pump signals and 52 price dump signals. The average price change was -0.20%, and the maximum and minimum price changes were 3.24% and -5.92%. In comparison, the average and maximum price changes for XRP/USD were similar to BTC/USD. However, the largest price dump was 2.00% lower.  

In the second and third column of Figure 2, we can see that both BTC and ETH had higher volume spikes than XRP. RSI (14) on daily tick had several oversold signals (at 30), but did not trigger any overbought signals (at 70).

b) Kraken { BTC, ETH, XRP } / CAD

Figure 3. Price pump and dump signals, volume spike signals, and RSI (14) signals at Kraken for BTC/CAD, ETH/CAD and XRP/CAD between June 1 to June 30, 2019.

Blockchain - Price pump and dump signals, volume spike signals, and RSI (14) signals at Kraken for BTC/USD, ETH/USD and XRP/USD between June 1 to June 30, 2019.

BTC/CAD trading pair at Kraken had a total of 19 price pump signals and 40 price dump signals.  The average price change was -0.13% within 15 minutes, and the maximum and minimum price changes were 5.58% and -9.54%, respectively. 

ETH/CAD trading pairhad a total of 22 price pump signals and 46 price dump signals. The average price change was 0.15%, and the maximum and minimum price changes were 5.08% and -5.00%, respectively. 

XRP/CAD trading pair had a total of 21 price pump signals and 47 price dump signals. The average price change was close to zero percent (-0.03%), whereas the maximum and minimum price changes were 4.28% and -8.06%, respectively.  

Overall, BTC/CAD, ETH/CAD, and XRP/CAD trading pairs at Kraken had were more extreme minimum and maximum price changes than respective USD trading pairs at Bitstamp. 

c) Binance { BTC, ETH, XRP } / USDT

Figure 4. Price pump and dump signals, volume spike signals, and RSI (14) signals at Binance for BTC/USDT, ETH/USDT and XRP/USDT between June 1 to June 30, 2019.

Blockchain - Price pump and dump signals, volume spike signals, and RSI (14) signals at Binance for BTC/USD, ETH/USD and XRP/USD between June 1 to June 30, 2019.

APPENDIX A: Figures

a) BTC/USD price pump and dump at Bitstamp between June 1 to 30, 2019.

Blockchain - BTC/USD price pump and dump at Bitstamp between June 1 to 30, 2019.

b) BTC/USD volume spike & drop at Bitstamp between June 1 to 30, 2019.

Blockchain - BTC/USD volume spike and drop at Bitstamp between June 1 to 30, 2019.

c) BTC/USD RSI(14) signal at Bitstamp between June 1 to 30, 2019.

Blockchain - BTC/USD RSI(14) signal at Bitstamp between June 1 to 30, 2019.

APPENDIX B: Methodology

  • Price pump and dump calculations: calculated based on if the price goes above or below the upper and lower Bollinger bands and the price surpasses the rolling highest value over 6 hours.
  • Volume spike and drop calculations: calculated based on if the volume goes above or below exponential moving average of volume over 10 days.
  • RSI overbought and oversold calculations: calculated based RSI(14) indicator, and used 30 and 70 values for overbought and oversold threshold.

APPENDIX C: Alert System Statistics

Summary of alert system statistics between June 1 to 30, 2019.

BITSTAMP BTC/USD ETH/USD XRP/USD
# Price Pump Signal 53 40 51
# Price Dump Signal 48 47 52
Avg. Price Change  (15min)  -0.20 -0.08 -0.20
Max. Price Change (15min) 3.76 1.80 3.24
Min. Price Change  (15min) -4.04 -3.45 -5.92

 

KRAKEN BTC/CAD ETH/CAD XRP/CAD
# Price Pump Signal 19 22 21
# Price Dump Signal 40 46 47
Avg. Price Change  (15min)  -0.13 0.15 -0.025
Max. Price Change (15min) 5.58 5.08 4.28
Min. Price Change  (15min) -9.54 -5.0 -8.06

 

BINANCE BTC/USDT ETH/USDT XRP/USDT
# Price Pump Signal 56 38 56
# Price Dump Signal 45 44 45
Avg. Price Change  (15min)  -0.24 -0.12 -0.20
Max. Price Change (15min) 2.77 1.85 3.18
Min. Price Change  (15min) -4.87 -3.46 -6.29

Disclaimer

The information contained herein is for informational purposes only and is not intended as a research report or investment advice. It should not be construed as Coinscious recommending investment in cryptocurrencies or other products or services, or as a solicitation to buy or sell any security or engage in a particular investment strategy. Investment in the crypto market entails substantial risk. Before acting on any information, you should consider whether it is suitable for your particular circumstances and consult all available material, and, if necessary, seek professional advice.

Coinscious and its partners, directors, shareholders and employees may have a position in entities referred to herein or may make purchases and/or sales from time to time, or they may act, or may have acted in the past, as an advisor to certain companies mentioned herein and may receive, or may have received, a remuneration for their services from those companies.

Neither Coinscious or its partners, directors, shareholders or employees shall be liable for any damage, expense or other loss that you may incur out of reliance on any information contained in this report. Chainlink

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SIGN-UP FREE: MARKET DATA API  |  ALERT API

Investigating Crypto Exchange Price & Volume Patterns

By | Coinscious Lab, Data Analytics, Exchange Report | No Comments

Overview

Released monthly, this report aims to analyze and characterize cryptocurrency exchanges according to their volume for the past month, this time from February 16, 2019 to March 16, 2019.

Our universe of analysis uses public exchange data from 18 of some of the most popular exchanges1 (see Figure 1). Through analysis of the recent historical volume and price of individual exchanges we provide a framework for analysis where investors can identify better or fairer exchanges.

Using daily volume data from some of the most widely used cryptocurrency exchanges, we were able to cluster exchanges into three groups based on similarity in volume trends. Some of our findings include the following:

  • OKEx and HitBTC go against the market both in terms of volume correlation and price-volume correlation.
  • Although OKEx has reported the biggest traded volume between February 16, 2019 to March 16, 2019, PCA analysis separates it from the other top exchanges (i.e. Binance and HuobiPro), and shows a low correlation with the market in terms of traded volume.

Performance

Figure 1. Total monthly volume, mean daily volume, max daily volume, mean hourly volume and max hourly volume for each exchange from February 16, 2019 to March 16, 2019 in USD. Monitor exchange performance daily through our Market & Trading Strategy Dashboard: dashboard.coinscious.io

According to the public exchange data, OKEx has reported the biggest mean daily and hourly volume for the past month.

In the past month, OKEx took first place with a total of $28 billion traded between February 16 to March 16, compared to $25 billion for ZB (2nd) and $20 billion for Binance (3rd) (see Figure 1).

We chose ETH/BTC trading pair to analyze exchange volumes in more depth. ZB traded volume for ETH/BTC was the highest overall, following the trend described in our previous Exchange Report. However, OKEx took first place on March 5 when its volume changed from $78 million to $107 million in a single day. It remained at the top spot until March 12, when its volume dropped back down to $39 million; ZB retook first place. Interestingly, according to BeinCrypto, on March 5 ethereum’s price began to increase rapidly from $130 throughout the earlier part of the day, and reached a daily highly of $143.83 on March 6 [1].

Figure 2. ETH/BTC pair daily volume for each exchange from February 16, 2019 to March 16, 2019 in USD.

Observations

The cryptocurrency market was on an uptrend starting from the morning of Wednesday, April 3, 2019 – the price of BTC went up from $4,000 to $4,800. In fact, because of the BTC pump, we observed that there were huge volume changes for all exchanges except Fcoin; their volume changes remained low.

Figure 3a. Top 10 crypto exchange volume changes on April 3, 2019.

As you can see in Figure 3a, the top 10 exchanges have 1-day volume changes ranging between 73.35% to 315.18%. However, Fcoin is the only exchange with a much lower volume change of 9.25%.

Three days later, on the morning of Saturday, April 6, 2019, the market started to slow down and became tranquil. Again, we can observe this from 1-day volume changes in Figure 3b, where most of the exchanges’ volume changes decreased to around 22-60%. Nevertheless, Fcoin and HitBTC volume changes were up by 18% and 19% respectively.

Figure 3b. Top 10 crypto exchange volume changes on April 6, 2019.  

These strong indications reveal that Fcoin (and possibly HitBTC) is likely faking its volume. The next section delves into a deeper analysis and looks at which specific exchanges violate volume trends in comparison to all exchanges overall.

Analysis

In order to categorize exchanges and investigate their trends during the past month, we performed a dimensionality reduction analysis using PCA2 for ETH/BTC pair daily volume. By plotting crypto exchanges according to their first two principal components, we identified a cluster and some outliers (see Figures 3a and 3b). The two first principal components explain more than 80% of the variance in our data set and the relative position along the x- and y-axes indicate similarities between exchanges in terms of traded volume. Thus, exchanges clustered together present similar volume trends, while outliers, namely Okex, HuobiPro, Binance, Fcoin, HitBTC, and ZB, show trends that diverge from the market mean.

If we zoom in on the market mean, we can identify subgroups of exchanges that are closely related inside the market mean (Figure 3b).

Figure 3a. PCA Volume analysis for ETH/BTC. The biplot, where the two main principal components are used to represent the exchanges allows us to identify clusters or groups of exchanges that might be correlated according to volume.

Figure 3b. PCA Volume analysis excluding outliers in the first analysis.

To understand the meaning of the two principal components and characterize the outliers, we decided to look at correlation between exchanges. We used volume for the ETH/BTC pair to identify a general trend in the market and determine whether exchanges follow or are against the trend (see Figure 5). Although most exchanges show a similar trend (that is, they follow a similar daily volume trend), OKEx, Bitflyer, BigOne and HitBTC show a daily volume trend that goes against the market. Interestingly, ZB and Zaif follow the mean market trend this time. Also note that compared to the PCA biplot using daily volume data from January 16 to February 16, OKEx and ZB have swapped positions (see Figure 3 from the previous Exchange Report)

Figure 5a. Top 5 negative volume correlations

Figure 5b. Top 5 positive volume correlations

Figure 6. Daily volume correlations between exchanges from February 16, 2019 to March 16, 2019 for ETH/BTC. Correlation ranges between -1 and 1. Correlation close to 1 indicates a more positive relationship between the pair of cryptocurrency returns and correlation close to -1 indicates a more negative linear relationship. Correlation close to 0 indicates no linear relationship.

OKEx, in particular, shows negative correlations with all exchanges except for HitBTC and HuobiPro. This suggests that OKEx, Bitflyer, HitBTC and BigONE are acting against the market.

Again, Upbit and Bittrex show the highest correlation for all exchange pairs, suggesting that they share the same order book [2]. This was also noted in our previous Exchange Report.

To explore what other factors could contribute to the clustering in different groups after Volume PCA, we calculated the correlation between ETH/BTC price and volume for every exchange pair (see Figure 6).

Figure 7. Daily price-volume correlations between exchanges from February 16, 2019 to March 16, 2019 for ETH/BTC. Correlation ranges between -1 and 1. Correlation close to 1 indicates a more positive relationship between the pair of cryptocurrency returns and correlation close to -1 indicates a more negative linear relationship. Correlation close to 0 indicates no linear relationship.

OKEx and HitBTC stand out as exchanges with the highest negative correlation between ETC/BTC price and volume for all exchanges. This shows that not only their volume, but also their ETH prices go against the market. While most exchanges show a positive trend (higher volumes associated with higher prices), OKEx, HitBTC, HuobiPro and BigOne show a negative trend (higher volumes associated with lower prices, and vice versa).

Summary

Using daily volume data from 18 of some of the most widely used cryptocurrency exchanges and principal component analysis, we identified three clusters of exchanges sharing similar volume trends. We mainly looked at volume correlations and price-volume correlations. Our findings include:

  • Okex and HitBTC go against the market both in terms of volume correlation and price-volume correlation.
  • Although Okex has reported the biggest traded volume in the past month, PCA analysis separates it from the other top exchanges (i.e. Binance and HuobiPro) and shows a low correlation with the market in terms of traded volume.

Here, these findings are simple observations of possibly correlated variables. We share this from the point-of-view of something to look out for. Overall, our exchange analysis has proven useful to study patterns of volume and price activity in the market and identify potential manipulation, that could be confirmed using blockchain data.

Footnotes

1 The scope of this report does not cover futures contracts.

2 PCA is a technique that finds underlying variables that best differentiates your data points. In this article, we visualize and analyze along the two dimensions which the data points varies the most (see Appendix B).

APPENDIX A: Methodology

The daily volume of cryptocurrencies in USD at 4:00 PM EST from February 16, 2019 to March 16, 2019 was used for our volume ranking. Daily volume and price for the pair ethereum_bitcoin was used for the same time period for the PCA analysis and correlation analysis. Price and volume were normalized such that its distribution had mean value 0 and standard deviation of 1 in order to perform principal component analysis and calculate price-volume correlations. In subsequent reports, we may update our universe, sectors, methodology, and analysis to reflect new developments.

APPENDIX B: Terminology

  • Correlation: A measure of the linear relationship between two series of random variables, which in the context of finance, can be two series of returns. Correlation ranges between -1 and 1. Correlation close to 1 indicates a more positive relationship between the pair of cryptocurrency returns and correlation close to -1 indicates a more negative linear relationship. Correlation close to 0 indicates no linear relationship.
  • PCA: A statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components, in order to maximize the explained variance.

References

[1] T. (2018, December 11). Binance Losses Top Cryptocurrency Exchange Position to OKEX and ZB.Com. Retrieved from https://coingape.com/

[2] Lavere, M. (2019, February 13). Ethereum (ETH) Mining Reward Hits Lowest Ever.  Retrieved from https://ethereumworldnews.com/

[3] Bitking74. (2017, October 24). UPbit and Bittrex are sharing the same order book. This is a win win for both sides: bring some Korean liquidity to Bittrex, also the Korean users start with nicely filled order books from Bittrex. Go NEO. Neotrader [Online forum]. Retrieved from https://www.reddit.com/r/Neotrader/comments/78fztu/upbit_and_bittrex_are_sharing_the_same_order_book/

[4] J. (2018, September 18). Chinese Investor Loses 700,000 Yuan Due To Fcoin Crypto Manipulation. Retrieved from https://www.coindaily.co/

[5] Sillers, A. (2018, September 12). The evidence of OKex’s fraudulent behavior, which may point to HitBTC as well. Retrieved from https://www.chepicap.com/

Disclaimer

The information contained herein is for informational purposes only and is not intended as a research report or investment advice. It should not be construed as Coinscious recommending investment in cryptocurrencies or other products or services, or as a solicitation to buy or sell any security or engage in a particular investment strategy. Investment in the crypto market entails substantial risk. Before acting on any information, you should consider whether it is suitable for your particular circumstances and consult all available material, and, if necessary, seek professional advice.

Coinscious and its partners, directors, shareholders and employees may have a position in entities referred to herein or may make purchases and/or sales from time to time, or they may act, or may have acted in the past, as an advisor to certain companies mentioned herein and may receive, or may have received, a remuneration for their services from those companies.

Neither Coinscious or its partners, directors, shareholders or employees shall be liable for any damage, expense or other loss that you may incur out of reliance on any information contained in this report.

Investigating Disruptive Patterns of Crypto Exchanges

By | Coinscious Lab, Data Analytics, Exchange Report | No Comments

Overview

Released monthly, this report aims to analyze and characterize cryptocurrency exchanges according to their volume for the past month, this time from January 16, 2019 to February 16, 2019.

Our universe of analysis uses public exchange data from 18 of some of the most popular exchanges1 (see Figure 1). Through analysis of the recent historical volume and price of individual exchanges we provide a framework for analysis where investors can identify better or fairer exchanges.

Using daily volume data from some of the most widely used cryptocurrency exchanges, we were able to cluster exchanges into three groups based on similarity in volume trends. Some of our findings include the following:

  • Fcoin and HitBTC go against the market both in terms of volume correlation and price-volume correlation.
  • Not only does volume and price seem to go against the market, but returns and volume are positively correlated only for Fcoin and HitBTC, while returns and volume are negatively correlated for the rest of exchanges.
  • Although ZB has reported the biggest traded volume in the past month, ZB volume trend patterns were different from the other top exchanges (Binance, HuobiPro, and OKEx). Generally, it showed a low correlation with the market in terms of traded volume.
  • It is also interesting to note that our analysis (Figure 4b. Top 5 positive correlations) accidentally reveals a shared order book between Upbit and Bittrex.

Performance

Figure 1. Total monthly volume, mean daily volume, max daily volume, mean hourly volume and max hourly volume for each exchange from January 16, 2019 to February 16, 2019 in USD. Monitor exchange performance daily through our Market & Trading Strategy Dashboard: dashboard.coinscious.io

According to the public exchange data, ZB has reported the biggest mean daily and hourly volume for the past month. Binance reportedly lost the crown as the king of cryptocurrency by trade volume on December 11, 2018 to be replaced by OKEx, who held the 1st place at that time, while ZB held 2nd [1].

In the past month, ZB has taken the first spot, with a total of 16 billion dollar traded between January 16th to February 16th, compared to 14 billion USD for OKEx (2nd) and Binance (3rd) (see Figure 1).

We then chose ETH/BTC pair to look at the volume more closely and analyze it in more depth. ZB traded volume for ETH/BTC is low during the whole period, with Binance, HuobiPro and OKEx as top exchanges. However, there was a rapid surge on February 11th, when volume changed from $500,000 USD to $67 million USD in one day, and it has remained high since then (see Figure 2). That same day,  according to Etherscan, daily mining rewards for Ethereum fell to their lowest recorded levels [2].

Figure 2. ETH/BTC pair daily volume for each exchange from January 16, 2019 to February 16, 2019 in USD.

Analysis

In order to categorize exchanges and investigate their trends during the past month, we performed a dimensionality reduction analysis using PCA2 for ETH/BTC pair daily volume. By plotting crypto exchanges according to their first two principal components, we could identify a cluster and some outliers (see Figure 3). The two first principal components explain more than 80% of the variance in our data set and the relative position along the x and y axis indicates similarity between exchanges in terms of traded volume. Thus, exchanges clustered together present similar volume trends, while outliers, namely Okex, HuobiPro, Binance, Fcoin, HitBTC, and ZB, show trends that diverge from the market mean.

Figure 3. PCA Volume analysis for ETH/BTC. The biplot, where the two main principal components are used to represent the exchanges allows us to identify clusters or groups of exchanges that might be correlated according to volume.

To understand the meaning of the two principal components and characterize the outliers, we decided to look at correlation between exchanges using volume for the ETH/BTC pair, to identify a general trend in the market and whether exchanges follow or are against the trend (see Figure 5). Although most exchanges show a similar trends (this is, they follow a similar daily volume trend), Bitflyer, ZB, Zaif, Fcoin, and HitBTC show a daily volume trend that goes against the market.

Figure 4a. Top 5 negative volume correlations

Figure 4b. Top 5 positive volume correlations

Figure 5. Daily volume correlations between exchanges from January 16, 2019 to February 16, 2019 for ETH/BTC. Correlation ranges between -1 and 1. Correlation close to 1 indicates a more positive relationship between the pair of cryptocurrency returns and correlation close to -1 indicates a more negative linear relationship. Correlation close to 0 indicates no linear relationship.

Fcoin in particular shows negative correlations with all exchanges except for HitBTC. This suggests that Bitflyer, ZB, Zaif, Fcoin, and HitBTC are acting against the market. Moreover, it’s interesting to see that Bitflyer, ZB, Zaif, Fcoin, and HitBTC are all based in Asian countries.

On the other hand, Upbit and Bittrex show the highest correlation for all exchange pairs. This similarity in volume is in line with reports suggesting that they share the same order book, although further analysis of blockchain data will be needed to confirm these claims [3].  

To explore what other factors could contribute to the clustering in different groups after Volume PCA, we calculated the correlation between ETH/BTC price and volume for every exchange pair (see Figure 6).

Figure 6. Daily price-volume correlations between exchanges from January 16, 2019 to February 16, 2019 for ETH/BTC. Correlation ranges between -1 and 1. Correlation close to 1 indicates a more positive relationship between the pair of cryptocurrency returns and correlation close to -1 indicates a more negative linear relationship. Correlation close to 0 indicates no linear relationship.

Again, Fcoin stands out as the exchange with a highest negative correlation between ETC/BTC price and volume for all exchanges showing that, not only the volume, but ETH price is also against the market3. While most exchanges show a positive trend, with high volumes associated to higher prices, Fcoin shows a negative trend, where higher volumes during the analyzed period are associated with lower prices and vice versa.

This raised suspicions that Fcoin might be manipulating price and volume, especially for the pair that we have analyzed (ETH/BTC). Fcoin has been accused of manipulation in the past. In September, a Chinese investor filed a complaint against the exchange, which presumably induced sudden drops in price through manipulation after investing huge amounts in Fcoin token [4].

Finally, if we look at the correlation between returns (instead of price) and volume for ETH/BTC (Figure 7), HitBTC and Fcoin are again the exchanges going against the general trend. High returns in HitBTC and Fcoin are associated with an increase in volume, while high returns elicit a decrease in volume for the rest of exchanges (negative correlation between returns and volume). Interestingly, HitBTC has also been accused of volume manipulation [5].

Figure 7. Daily returns-volume correlations between exchanges from January 16, 2019 to February 16, 2019 for ETH/BTC. Correlation ranges between -1 and 1. Correlation close to 1 indicates a more positive relationship between the pair of cryptocurrency returns and correlation close to -1 indicates a more negative linear relationship. Correlation close to 0 indicates no linear relationship.

Summary

Using daily volume data from 18 of some of the most widely used cryptocurrency exchanges and principal component analysis, we identified three clusters of exchanges sharing similar volume trends. We mainly looked at volume correlations and price-volume correlations. Our findings include:

  • Fcoin and HitBTC go against the market both in terms of volume correlation and price-volume correlation.
  • Not only volume and price seem to go against the market, but returns and volume are positively correlated only for Fcoin and HitBTC, while returns and volume are negatively correlated for the rest of exchanges.
  • Although ZB has reported the biggest traded volume in the past month, PCA analysis separates it from the other top exchanges (Binance, HuobiPro, and OKEx) and show a low correlation with the market in terms of traded volume.
  • It is also interesting to note that our analysis (Figure 4b Top 5 positive correlations) accidentally reveals a shared orderbook between Upbit and Bittrex

Here, these findings are simple observations of possibly correlated variables. We share this from the point-of-view of something to look out for. Overall, our exchange analysis has proven useful to study patterns of volume and price activity in the market and identify potential manipulation, that could be confirmed using blockchain data.

Footnotes

1 The scope of this report does not cover futures contracts.

2 PCA is a technique that finds underlying variables that best differentiates your data points. In this article, we visualize and analyze along the two dimensions which the data points varies the most (see Appendix B).

3 Here, the market is refers to the trend of majority of the exchanges.

APPENDIX A: Methodology

The daily volume of cryptocurrencies in USD at 4:00 PM EST from January 16, 2019 to February 16, 2019 was used for our volume ranking. Daily volume and price for the pair ethereum_bitcoin was used for the same time period for the PCA analysis and correlation analysis. Price and volume were normalized such that its distribution had mean value 0 and standard deviation of 1 in order to perform principal component analysis and calculate price-volume correlations. In subsequent reports, we may update our universe, sectors, methodology, and analysis to reflect new developments.

APPENDIX B: Terminology

  • Correlation: A measure of the linear relationship between two series of random variables, which in the context of finance, can be two series of returns. Correlation ranges between -1 and 1. Correlation close to 1 indicates a more positive relationship between the pair of cryptocurrency returns and correlation close to -1 indicates a more negative linear relationship. Correlation close to 0 indicates no linear relationship.
  • PCA: A statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components, in order to maximize the explained variance.

References

[1] T. (2018, December 11). Binance Losses Top Cryptocurrency Exchange Position to OKEX and ZB.Com. Retrieved from https://coingape.com/

[2] Lavere, M. (2019, February 13). Ethereum (ETH) Mining Reward Hits Lowest Ever.  Retrieved from https://ethereumworldnews.com/

[3] Bitking74. (2017, October 24). UPbit and Bittrex are sharing the same order book. This is a win win for both sides: bring some Korean liquidity to Bittrex, also the Korean users start with nicely filled order books from Bittrex. Go NEO. Neotrader [Online forum]. Retrieved from https://www.reddit.com/r/Neotrader/comments/78fztu/upbit_and_bittrex_are_sharing_the_same_order_book/

[4] J. (2018, September 18). Chinese Investor Loses 700,000 Yuan Due To Fcoin Crypto Manipulation. Retrieved from https://www.coindaily.co/

[5] Sillers, A. (2018, September 12). The evidence of OKex’s fraudulent behavior, which may point to HitBTC as well. Retrieved from https://www.chepicap.com/

Disclaimer

The information contained herein is for informational purposes only and is not intended as a research report or investment advice. It should not be construed as Coinscious recommending investment in cryptocurrencies or other products or services, or as a solicitation to buy or sell any security or engage in a particular investment strategy. Investment in the crypto market entails substantial risk. Before acting on any information, you should consider whether it is suitable for your particular circumstances and consult all available material, and, if necessary, seek professional advice.

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