**Overview**

Released bi-weekly, this report by Coinscious 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 March 16, 2019 to April 14, 2019.

Our universe of analysis includes 50 of some of the most widely used and traded cryptocurrencies. Please see Appendix A for the complete list.

**Analysis**

The performance of major cryptocurrencies over the past month has been good, with 41 out of the 50 cryptocurrencies that we examined up from their values 30 days ago. Bitcoin (BTC), the largest cryptocurrency by market capitalization, finally breaks above the $4,200 overhead resistance level on April 1; BTC surges to $5105. Various other cryptocurrencies, including second and third largest cryptocurrencies ether (ETH) and XRP (XRP) also experienced large upwards movements on the same day.

Outside of cryptocurrencies, the S&P 500 is up 3.01% from 30 days ago and closed last Friday at $2907.41.

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 March 16, 2019 to April 14, 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 110.60%. Tezos is a self-amending proof-of-work dApp platform that removes the need to hard fork when implementing protocol amendments.

The second and third best performing cryptocurrencies were Bitcoin Cash (BCH) and IOST (IOST), with total returns of 80.40% and 71.34% respectively.

Nano (NANO) was the worst performing cryptocurrency, with total losses of 53.49%. Nano is a low-latency payment platform designed for peer-to-peer transactions. The second and third worst performing cryptocurrencies were Maker (MKR) and Steem (STEEM) with total losses of 11.49% and 11.42% respectively.

*Figure 2a. Mean daily returns, historical daily volatility, total returns, and ex-post Sharpe ratio for each cryptocurrencies with the highest total returns from March 16, 2019 to April 18, 2019. 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 2b. Mean daily returns, historical daily volatility, total returns, and ex-post Sharpe ratio for cryptocurrencies with the lowest total returns from March 16, 2019 to April 18, 2019. 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 3 plots daily candlesticks of the prices of Bitcoin ( BTC ) and Ether (ETH), the two largest cryptocurrencies by market capitalization, as well as the top performer of the past month, Tezos (XTZ). In addition, the following commonly used technical analysis indicators are shown:

Simple moving averages (SMA) with periods of 50, 100, and 200 days

Relative strength index (RSI) with a period of 14 days

Moving average convergence divergence (MACD) with a fast EMA period of 12 days, slow EMA period of 26 days,

and a signal period of 9 days

*Figure 3a. Price of Bitcoin (BTC) in USD at Bitstamp from March 16, 2019 to April 14, 2019.*

*Figure 3b. Price of Ether (ETH) in USD at Bitstamp from March 16, 2019 to April 14, 2019.*

*Figure 3c. Price of Tezos (XTZ) in USD at Bitfinex from March 16, 2019 to April 14, 2019.*

**Appendix A: Cryptocurrencies**

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 March 16, 2019 to April 18, 2019. 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.

**Appendix B: Methodology**

The daily price data of cryptocurrencies in USD at 4:00 PM EST from March 16, 2019 to April 14, 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&P 500 index was obtained from from Yahoo Finance. 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 C: 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.