Cryptocurrency price has seen several rounds of marked decline in 2018. Especially in the second half of 2018, crypto volatility has reportedly been flattening. You may know that higher volatility will contribute to quantitative . The more volatile crypto market is, the more returns will be harvested from quantitative strategies. Many crypto traders are concerned that the current flattening crypto volatility is not fit for applying quantitative strategies anymore. However, after a comprehensive and thorough analysis of the market data, we are still positive about the feasibility of quantitative strategies.
The following formula will be used to analyze volatility of from 2014 through Apr. 2019.
Volatility Ratio= (peak price — bottom price)/average price (in a certain time span)
The following is ’s Quarterly Volatility Trend:
The highest and lowest points on the right side happened in the 3rd and 4th quarter in 2018 as well as in the first quarter in 2019, respectively. price seems less volatile compared with that of its close time span beforehand. The fourth quarter of 2017 witnessed the highest volatility when soared from $8,000 from $20,000. Volatility following ’s peak price was also relatively high in the first half of 2018. So the relative lackluster volatility of since mid-2018 easily led many investors to compare the market conditions in 2017 with that of the first half of 2018 and assert that volatility is shrinking.
Volatility on a Quarterly Basis (data of 2017 and the first half of 2018 deleted)
This chart is the same with the previous one except that we have removed the dada of 2017 and the first half of 2018. You will not have the impression that volatility is going away. You see that price volatility was still there in the second half of 2018 and in 2019. Plus, volatility was high in the fourth quarter of 2018 due to the marked price decline in November and rebound in December. In fact, we applied CTA strategy and it worked quite well in November and December. Though volatility was flattening in the first quarter of 2019, it still stayed close to the average volatility level on this chart, not like some people’s assertion that volatility is going away.
Volatility on a Monthly Basis
The same as this chart when we remove the dada of 2017 and of the first half of 2018. The curving line on the right side of the red solid line represents the volatility of the second half of 2018 and 2019 to date, we can find that volatility range stays to the long term average volatility level, which is, in fact, a bit higher than the average volatility of 2016. Note that volatility was much bigger in Nov. 2018.
Volatility on a Weekly Basis
Through the weekly data, we can see that volatility breaking above 20 %( yellow line) happened multiple time before Sep.2018. But since then, volatility stayed under 20% most of the time (on the right side of the red line). It represented the real reason why the performance of quantitative strategies has slid. There is less frequency of high volatility in the market. It used to be once or twice a week, now it’s once or twice a month.
In a word, the market is changing non-stop, and we need to keep learning and make customized quantitative strategies to adapt to new market changes. Our mission is to bring more benefits to our clients with the best use of quantitative strategies.
About the Author:
The article was provided by Aether Technologies. Aether Technologies was founded in August 2018, a leading investment bank mainly engaged in the secondary market quantitative services of digital currency. Based on mathematical statistics and mathematical modeling, the company uses computer technology to provide programmatic operations for . The core service concept of Aether Technologies is to use an effective quantitative model to conduct 24-hour non-stop in the global digital market, helping to seek low-risk, stable portfolios to meet customer needs.
Its Chief Investment Officer, Kevin Zhou, is a former founding partner of Niankong Data Technology Center. Kevin holds a dual degree in finance and computer science at MIT and has 20 years of experience in the areas of quantitative investment, fund management, risk control, and . Plus, their core team is mainly from the United States, all with rich experience in financial markets, financial derivatives , and quantitative models.
Disclaimer: This material should not be the basis for making investment decisions, nor be construed as a recommendation to engage in investment transactions. Please make your own investment decisions and take only the risks you can afford.
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Published at Sun, 14 Apr 2019 13:14:57 +0000
