London Business News: Bitcoin volatility peaks at 3pm before the New York Stock Exchange closes as well as spiking at 3am Eastern Standard Time, according to new analysis (1) from GNY, the leading blockchain based machine learning business.
Its analysis of trading data throughout 2021 found 3pm in the US – or 8pm in the UK – is the time to avoid for Bitcoin traders wanting to minimize volatility while 3am in the US – 1.30pm in India – is also a time for high volatility.
GNY’s analysis of 25 input data features found that trading data – whether volumes are high or low on average or whether Bitcoin prices are seeing major positive or negative moves – is the only mathematical relationship with volatility.
Factors such as LIBOR, gold prices, the Federal Funds rate or US inflation have no mathematical relationship with Bitcoin volatility.
GNY analysis reveals daily average Bitcoin volatility was 4.1% last year with daily volatility ranging between 4% and 10% when trading volume is above average and between 2% and 5% when volumes are below average.
GNY’s analysis of the most volatile days for Bitcoin trading in 2021 found August 2nd was the most volatile day with average daily volatility of 18.79% followed by May 19th with 13.83% and January 21st with 13.28%.
Its own research (2) shows one in five (22%) Bitcoin traders who trade at least $1,000 a month in the cryptocurrency expect the level of volatility to increase dramatically in 2022, and further 57% say it will increase slightly. Only 18% expect it to fall or stay the same
Cosmas Wong, CEO GNY said: “Our mission at GNY is to bring machine learning tools to the crypto community to facilitate smarter business and trading decisions. Predicting Bitcoin volatility is the most impactful metric in blockchain right now.
“Our research has helped us understand the time based fluctuations in price and volume, as well as the patterns generated by market activity. Our nuanced machine learning models allow us to create a superior BTC prediction model.”
GNY recently launched the BTC Range Report, providing some of the most accurate forecasts around Bitcoin volatility of any platform or service available today. Extensive testing of BTC Range Report has delivered a mean absolute percentage error (MAPE) of between 3% and 7% making it one of the most powerful BTC prediction tools in the market. The average of the majority of competitor BTC prediction tools tested by GNY was 10%, but it was as high as 17% for some platforms.
GNY believes that today’s altcoin traders will be tomorrow’s bitcoin traders. So to launch the BTC Range Report GNY entered into an exclusive partnership with CoinSniper which is widely regarded as the #1 source for the best new cryptocurrency projects. Subscribers to the CoinSniper GNY newsletter providers traders with exclusive content and previews to measure the Range Report’s accuracy for themselves.
The BTC Range Report is available every Tuesday at 9am EST and spans a seven-day period. For the price of just $10, it can be purchased with ETH or GNY tokens, and access is provided directly through the user’s Metamask wallet. Version 1 of the GNY BTC Range Report offers:
- GNY’s daily projected volatility range for BTC as a graph and a table
- a forecast of which day will hold the weekly high and the weekly low
- forecast of daily volumes
- historical daily high and low prediction graph for the last two weeks VS BTC Actuals
- mean absolute percentage error (MAPE) for GNY historical daily high and low predictions VS BTC Actuals for the previous two weeks
- How To Use The Report
- The GNY Range Report is not financial advice and should not be taken as that. It is not meant to predict future Bitcoin prices but can be used to track millions of data points to identify patterns in Bitcoin trading. The goal of the GNY Range Report is to provide crypto traders with another data point in order to approach trading more rationally and less emotionally. The GNY team will continue to evolve the report, share its accuracy, and develop additional reports for other tokens in the future.
