Machine Learning Algorithm Forecasts How Bitcoin Volatility Tools Work
Machine learning algorithms are coming to the forefront in detecting bitcoin volatility trends. However, the latest report on Bitcoin volatility tools has found results from these tools are either average or poor. This is affecting the transaction volume among Bitcoin traders. 94% of the traders would trade more in Bitcoins if the cryptocurrency volatility prediction tools deliver more accurate results.
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Here’s a quick overview on what Bitcoin volatility prediction tools promise to deliver and how Machine Learning is making these tools more powerful and accurate.
One in four (~24%) of those who trade at least $1,000 a month in Bitcoin describes volatility predictive tools and services as average or poor. This is according to new research from GNY, the leading blockchain-based machine learning business, which recently launched BTC Range Report, providing some of the most accurate forecasts around Bitcoin volatility of any platform or service available today.
The study found that just 24% describe the Bitcoin volatility predictive tools available today as excellent, and 52% as good.
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A lack of confidence in Bitcoin volatility predictive tools is holding back some from trading more in Bitcoin. If they had more trust in them, 94% said they would increase their Bitcoin trading. Some 65% believe it would lead to a double-digit percentage increase in their level of trading, with 10% saying it would rise by at least 50%.
| What would happen to your level of Bitcoin trading if you had greater confidence in Bitcoin volatility predictive tools | Percentage of serious Bitcoin traders |
| Increase by up to 5% | 7% |
| Increase by between 5% and 10% | 22% |
| Increase by between 10% and 20% | 19% |
| Increase by between 20% and 30% | 20% |
| Increase by between 30% and 40% | 11% |
| Increase by between 40% and 50% | 5% |
| Increase by between 50% and 75% | 5% |
| Increase by between 75% and 100% | 3% |
| Increase by over 100% | 2% |
| It would not change | 4% |
Cosmas Wong, CEO GNY said: “There are a growing number of tools and services focusing on the future volatility of Bitcoin, but our research reveals many traders don’t have a huge amount of confidence in them.
“As the market develops and we have more data on the price movement in Bitcoin and what drives these, and we make greater use of artificial intelligence, the quality of the volatility predictive tools should improve.”
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.
The BTC Range Report uses proprietary machine learning to forecast Bitcoin volatility. The tool is the first consumer-facing product offered by GNY and uses specialized neural nets and a custom RSI to generate optimized forecasting for the projected daily range for Bitcoin.
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The BTC Range Report is issued every Tuesday 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
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.
Research Methodology
IO commissioned the research company Pureprofile to survey 100 Bitcoin traders who trade at least $1,000 a month in the cryptocurrency. The survey was conducted in December 2021 with respondents from the UK, US, Germany, Netherlands, Nigeria, Switzerland, Vietnam, and the Philippines – countries that have some of the largest Bitcoin trading markets in the world.
GNY is building transformative new technology at the intersection of machine learning and blockchain. “Our Level 1 blockchain solution is constructed with machine learning requirements built into our core code and data structures,” says Cosmas Wong, GNY CEO “which provides developers that use our platform to create dApps a huge advantage. Building with GNY means that all of your data will be inherently primed for the insights, monetization opportunities and sustainability goals that only integrated machine learning can bring.”
The BTC Range Report is the first of many ML-powered tools the company plans to release, as part of its forthcoming Machine Learning marketplace, GNY Dataplace, which is launching next year. GNY Dataplace will provide a structured and secure way to partner with collaborators on machine learning without sharing raw data, build custom ML solutions that can be licensed on the platform, and use GNY’s Machine Learning engines to monetize predictions of their own. GNY believes that Web 3.0 will be defined by the ability to move ML out of siloed use, opening the door to collaborative data environments that are safe, scalable, and secure.
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