Market Overview - October 2019

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Relative Returns

At the beginning of October, most pairs traded in somewhat of a trading range. As seen on the graph above, about half of the pairs traded lower, the other half traded up but only by a small margin. On October 23rd markets fell, with BTC_USDT falling ~13% in the span of a few hours. However, the move was not sustained for very long; And in typical Crypto market fashion, on October 25th, BTC_USDT gained almost 30% throughout the day, reversing the selling pressure and closing at a months high, last seen in September. The outperformer this month was Tron, with TRX_USDT gaining as much as 32% at months end breaking the previous Resistance lines and reaching a high of $0.02295 which we have not seen since mid August.

Overall the month saw positive returns for almost all pairs included in this report. TRX outperformed the market, however most other projects also finished with a positive margin, besides Ethereum which experienced a small monthly loss in October.

October 2019, Biggest Changes
10-Hour Rolling Volatility

Looking at the volatility of these pairs throughout the month of October seems to coincide with the takeaways from the Relative Returns. Volatility was bound at ~0.015 for most of the month, but then the two big moves of the month happened. Around October 27th volatilities for most projects spiked, with the biggest move occuring in BTC. Interestingly enough is that the outperformer based on Returns, TRX_USDT, seemed to experience a spike in volatility shortly after all the other projects, and also kept a relatively high volatility when compared to the other pairs. However, most of the other pairs finished the month at a similar reading than what they started at, hinting that the price move has been priced in and indecisiveness has entered the market again.

Correlations

The correlation matrix for the monthly correlation between assets shows some different readings than initially expected. First of all, at the time of writing the assumption was that correlations, especially in regards to BTC would be much higher. This assumption stems from the fact that the Bitcoin dominance index stood above 60% at the time of writing. However looking at the correlation of TRX to BTC, the slight shift in when prices peaked can be a factor indicating why they correlations are below 0.5. However, correlations of around 0.5 still show that there is a relation between price moves of separate assets, however these readings would not fit on a straight line when plotted against each other. Higher correlations can be observed between EOS and LTC, as well as between LTC , ETH and BTC with each other respectively.

Notable News & Announcements

1.1https://techcrunch.com/2019/10/23/zuckerberg-testimony/

1.2 https://www.wired.com/story/how-watch-mark-zuckerbergs-libra-testimony-congress/

2.1https://www.cnbc.com/2019/10/28/bitcoin-btc-price-climbs-as-chinas-xi-jinping-embraces-blockchain.html

2.2https://www.wsj.com/articles/bitcoin-and-chinese-tech-stocks-surge-after-xi-jinping-touts-blockchain-11572259762

3.1https://medium.com/bakkt-blog/bakkt-bitcoin-options-on-futures-to-launch-december-9-an-industry-first-8fb2bd686abb

3.2https://www.coindesk.com/bakkt-to-launch-options-on-its-bitcoin-futures-dec-9

4.1https://business.financialpost.com/pmn/press-releases-pmn/business-wire-news-releases-pmn/3iqs-the-bitcoin-fund-receives-favourable-ruling-from-ontario-securities-commission-panel

4.2https://osc.gov.on.ca/en/Proceedings_enr_20191030_3iq.htm


About Consilium

Consilium Crypto is a big data company that provides quantitative and qualitative insights to market participants in the digital asset space, including funds, family offices and exchanges.

Consilium analyzes 17,000 trading pairs, over 1000 assets, across 50+ exchanges, and tracks trading activity to the millisecond. Our system monitors raw transaction data, as well as complete price and liquidity information from order books around the globe. These data pipelines power our core products, designed to help funds find alpha and place large orders efficiently in times of thin liquidity.

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