English #시황분석
Tezos Shows Best Performance in the Past Month: 73.77% Gain
Cardano Offers Higher Returns Than Its Peers With Similar Risk-Level
Daniel Jiwoong Im
등록일: 2019-03-30  수정일: 2019-04-02

OVERVIEW


Released bi-weekly, Coinscious' market report aims to identify broad trends in the cryptocurrency market. In order to reflect the latest developments in this fast-paced and volatile market, the reports plan to focus on metrics derived from a 30-day rolling window of data, this time from February 28, 2019 to March 28, 2019.

Our universe of analysis includes 50 of some of the most widely used and traded cryptocurrencies, and groups them into sectors that reflect similar utility and valuation models. Through analysis of the recent historical performance of individual cryptocurrencies as well as their sectors, we provide a framework for analysis where investors can identify outperforming cryptocurrencies or sectors by comparing their performance relative to peers.

ANALYSIS


The performance of major cryptocurrencies over the past month has been good, with 45 out of the 50  cryptocurrencies that we examined up from their values 30 days ago. Bitcoin (BTC), the largest cryptocurrency by market cap, is trading around $4100, still in the sideways trend that began in November last year. However, it is also up 5.00% compared to 30 days ago.


Outside of cryptocurrencies, the S&P 500 has been relatively flat, only up 1.11% from 30 days ago and closing yesterday at $2815.44.


Figure 1 presents the risk versus return trade-off over the past 30 days by plotting mean daily return versus historical daily volatility for various cryptocurrencies.   

Figure 1. Plot of mean daily return against historical daily volatility for individual cryptocurrencies from February 28, 2019 to March 28, 2019. Higher returns at a given level of risk, measured through historical daily volatility, indicates a better investment.

The best performer overall over the past month was Tezos (XTZ), with a total return of 73.77%. Tezos is a self-amending proof-of-work dApp platform that removes the need to hard fork when implementing protocol amendments.


Stakeholders vote for their preferred proposed protocol amendments through a formal and systematic process that has four discrete periods: the Proposal Period, the Exploration or “Testing” Vote Period, the Testing Period, and the Promotion Vote Period. The Tezos community successfully concluded the first round of voting, the Proposal Period, on March 20 and are currently in the Exploration period, casting votes to decide whether the winning proposal will move on to be deployed to the test network.

This news is significant because it is the first time that the self-amending upgrade process has been put into action. According to ​Tezos​, removing the need to hard fork in order to make protocol amendments is an important because “the suggestion or expectation of a fork can divide the community, alter stakeholder incentives, and disrupt the network effects that are formed over time. Because of self-amendment, coordination and execution costs for protocol upgrades are reduced and future innovations can be seamlessly implemented.” ​Tezos’ price went up in the days leading up to the end of the first voting period, so it is possible that growing enthusiasm and positive news about the protocol upgrade was the underlying cause. The success of the first vote also likely caused the subsequent 31% jump on March 20.

The second and third best performing cryptocurrencies were Cardano (ADA) and Basic Attention Token (BAT) with total returns of 55.14% and 39.56% respectively. Cardano is noteworthy in that it offered higher returns than its peers with similar levels of risk, including several other dApp platforms.

Pundi X (NPXS) was the worst performing cryptocurrency, with total losses of 16.06%.


Figure 2a. Cryptocurrencies with the highest total returns from February 28, 2019 to March 28, 2019.


Figure 2b. Cryptocurrencies with the lowest total returns from February 28, 2019 to March 28, 2019.


Figure 3 shows various performance measures of the nine sectors as well as that of the S&P 500 for comparison and Figure 4 plots the performance over time of each sector. Performance between the sectors was all positive, except for stablecoins with a very small negative return. Total returns ranged from 0.00% (stablecoins) to 23.22% (digital content).

Figure 3. Mean daily returns, historical daily volatility, total returns, maximum drawdown, and ex-post Sharpe ratio for each sector from February 28, 2019 to March 28, 2019. Smaller maximum drawdowns and more positive Sharpe ratios are more desirable. The Sharpe ratio is calculated with the 10 year US Treasury bill rate as the annual risk-free rate.


Figure 4a. Price performance over time of sectors that had positive total returns between February 28, 2019 to March 28, 2019.

Figure 4b. Price performance over time of sectors that had negative total return between February 28, 2019 to March 28, 2019.

Figure 5 shows the correlation between the daily returns of each sector. The S&P 500 had little correlation with most cryptocurrency sectors except for stablecoins, which it had a 0.31 correlation with. Resources, consisting of Siacoin (SC) and Golem (GNT), was the least correlated with the others. Correlations between sectors were more varied and less highly positively correlated than observed in previous months.


Figure 5. Correlation between daily returns of each sector from February 28, 2019 to March 28, 2019. 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.

APPENDIX A: Methodology

The daily price data of cryptocurrencies in USD at 4:00 PM EST from February 28, 2019 to March 28, 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.

 

To analyze performance by sector, the prices of constituent cryptocurrencies was normalized by dividing by the price on February 28, 2019, then averaged. When calculating the daily returns using this averaged normalized price, it is equivalent to if each sector was represented as an equally weighted portfolio of its constituent cryptocurrencies formed starting February 28, 2019 and the daily returns of the portfolio were calculated. Returns used throughout this report refer to simple returns.

 

Daily closing price data of the S&P 500 index from Yahoo Finance was also used as a proxy to represent the US equity market. The latest 10 year US Treasury bill rate from YCharts was used for calculations involving a risk-free rate.

In subsequent reports, we may update our universe, sectors, methodology, and analysis to reflect new developments.



APPENDIX B: Terminology

  • Volatility: A measure of the dispersion in the trading price of an instrument over a certain period of time, defined as the standard deviation of an instrument’s returns.
  • Drawdown: A measure of the decline of the trading price of an instrument or investment since the previous peak during a certain period of time. Less negative, less frequent, and shorter drawdowns are more desirable.
  • Maximum drawdown: The maximum peak to trough decline of the trading price of an instrument or investment over a certain period of time. Less negative maximum drawdowns are more desirable.
  • Sharpe ratio: A risk adjusted measure of return that describes the reward per unit of risk. The reward is the average excess returns of an investment against a benchmark or risk-free rate of return, and the risk is the standard deviation of the excess returns. A higher Sharpe ratio is better. Ex-ante Sharpe ratio is calculated with expected returns whereas ex-post Sharpe ratio is calculated with realized historical returns.
  • 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.


ABOUT US

Coinscious Inc. builds artificial intelligence and data-driven insights for the cryptocurrency market. Coinscious delivers compelling, informative analytics to the cryptocurrency community and uncovers hidden insights and patterns from the data behind the scenes. Coinscious is focused on helping the cryptocurrency community make informed judgements through its services.


Coinscious was established in 2018 and in Canada, Europe and China. Coinscious uses sophisticated financial engineering and quantitative technologies, such as statistical modeling, machine learning, market structure, and risk management techniques, in order to facilitate the maturation of the cryptocurrency market through various tools and data services.

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