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Exchange Report

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.

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.