INCREASED CONFIDENCE IN AI SYSTEMS WOULD BOOST CRYPTO TRADING
Increased confidence in AI crypto trading tools would encourage non-professional/retail traders to increase their monthly trading, new international research* from GNY.IO Limited, the leading blockchain-based machine learning business, shows.
The study with traders trading at least $5,000 a month on cryptocurrencies in the UK, US, Germany, Brazil, Hong Kong, Singapore, the UAE and South Africa found 95% would trade more on a monthly basis if they had access to AI and machine learning trading tools.
On average they would increase trading by 16% if they had confidence in AI tools which could detect patterns in trading and predict price movements, the research found. Around 3% say they would double the amount they trade each month and 15% would increase the level of trading by more than a quarter.
GNY has developed the free AI-powered GNY Range Report at www.gnyrr.com, a cutting-edge machine learning tool designed specifically to forecast the volatility of the 12 top cryptocurrencies by leveraging multiple data points and advanced algorithms. GNY has further enhanced the tool to use large language models (LLMs) such as OpenAI’s ChatGPT and Meta’s LLaMa 2, making it even easier for users to identify notable changes in trends and signals in the crypto market.
The innovative platform empowers traders with accurate intelligence on potential price fluctuations, helping them make informed investment decisions as well as providing guidance on how to use and read charts, and market wide information. It simplifies the complex world of crypto into digestible information.
GNY now seeks to further refine its already impressive 97% accuracy rate in the 7-day Bitcoin forecast published daily in the GNY Range Report at www.gnyrr.com by harnessing the insights of the masses. The objective is to explore if collective user forecasts can fine-tune the data set that fuels their ML model.
The research found 41% would prefer long-term options when considering AI tools while 19% would prefer short-term options. Around 38% would be equally interested in both. Nearly two out of five (39%) would find AI powered daily summaries of crypto market activity extremely useful while 51% would find them quite useful.
Cosmas Wong, CEO GNY said: “Fabian, our Long Short-Term Memory (LSTM) model is already achieving striking accuracy in its daily 7-day volatility forecasts. The mission now is to elevate this model, with our users leading the way, and gamifying the experience.”
“We are all looking forward to the end of the crypto winter. Our ML tools suggest that momentum is returning to the market. Having reliable and objective data-focused, data-driven tools at hand to navigate the upcoming market swings will be crucial for any crypto trader.”
How to use the report
The GNY Range Report is a cutting-edge machine learning tool designed specifically to forecast the volatility of the 12 top cryptocurrencies. By leveraging multiple data points and advanced algorithms, the innovative platform empowers traders with accurate intel into potential price fluctuations, helping them make more informed trading decisions.
Unlike traditional market analysis tools, the GNY Range Report serves as a centralised hub, gathering and consolidating all relevant information in one place. The GNY Range Report ensures traders have access to the most pertinent data without feeling overwhelmed.
With its user-friendly interface and intuitive design, the GNY Range Report caters to both professional traders and passionate enthusiasts. It is a prosumer product that combines the robustness required for in-depth analysis with the accessibility needed for traders at any level of expertise.
Visit the GNY Range Report and unlock the power of data-driven analytics for the AI-edge in cryptocurrency trading. Visit www.gnyrr.com today and discover a new level of clarity in the crypto market.
Notes to Editors
*GNY.IO commissioned the independent research company Pureprofile to survey 100 cryptocurrency traders who trade at least $5,000 a month. The survey was conducted in July 2023 with respondents from the UK, US, Germany, Brazil, Hong Kong, Singapore, UAE and South Africa.