Lack of trust in volatility predictions hindering Bitcoin trading

By Puja Sharma

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 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. 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%.

The goal of the GNY Range Report is to provide crypto traders with another data point 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.

Cosmas Wong, CEO of 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,” he added.

Extensive testing of the 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 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.

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, which provides developers that use our platform to create apps a huge advantage,” says Wong. “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 ML marketplace, GNY Data place, which is launching next year.

Key takeaways

• Around 94% would trade more if they had greater confidence in Bitcoin volatility predictive tools
• A lack of confidence in Bitcoin volatility predictive tools is holding back some from trading more in Bitcoin.
• The goal of the GNY Range Report is to provide crypto traders with another data point to approach trading more rationally and less emotionally.