The Impact of AI Confidence on Retail Crypto Trading
The Impact of AI Confidence on Retail Crypto Trading
  • Yoo Mi-ja
  • 승인 2023.10.25 12:49
  • 댓글 0
이 기사를 공유합니다

- Retail crypto traders may trade more frequently, according to GNY research.
- GNY Range Report Uses Advanced AI Crypto Intelligence to Predict Cryptocurrency Volatility.

New international research from GNY Limited, a blockchain-based machine learning company, suggests that greater confidence in AI-driven crypto trading tools could encourage non-professional/retail traders to increase their monthly trading activity.

The study involved traders from the UK, US, Germany, Brazil, Hong Kong, Singapore, UAE and South Africa who trade at least $5,000 in cryptocurrencies per month. It found that 95% of these traders would consider trading more frequently if they had access to AI and machine learning trading tools. On average, they could increase their trading frequency by 16% if they had confidence in AI tools that could identify trading patterns and predict price movements. Approximately 3% would consider doubling their monthly trading volume, and 15% would consider increasing their trading activity by more than a quarter.

GNY has launched the free AI-powered GNY Range Report, an advanced machine learning tool dedicated to predicting the volatility of the top 12 cryptocurrencies. It leverages various data points and advanced algorithms, now even including large language models (LLMs) such as OpenAI's ChatGPT and Meta's LLaMa 2. These additions make it easier for users to identify significant changes in crypto market trends and signals.

This innovative platform equips traders with accurate insights into potential price fluctuations, helps them make informed investment decisions, and provides guidance on how to interpret charts and market information. It simplifies the complex world of cryptocurrency into easily digestible information.

GNY is now looking to improve on the already impressive 97% accuracy rate of the 7-day bitcoin forecast published daily in the GNY Range Report. The goal is to see if collective user forecasts can further refine the data set that supports their machine learning model.

The research found that 41% of traders would prefer long-term options when considering AI tools, while 19% would opt for short-term options. Approximately 38% are equally interested in both. A significant 39% would find AI-powered daily summaries of crypto market activity extremely useful, and 51% would find them quite useful.

Cosmas Wong, CEO of GNY, commented, "Our Long Short-Term Memory (LSTM) model, Fabian, is already achieving remarkable accuracy in its daily 7-day volatility forecasts. The mission now is to enhance this model, with our users taking the lead, and turn the experience into a gamified process."

"We are eagerly anticipating the end of the crypto winter. Our machine learning tools suggest that momentum is returning to the market. Having reliable, data-driven tools to navigate the upcoming market swings will be essential for any crypto trader."

How to use the report:

The GNY Range Report is an advanced machine learning tool tailored to predict the volatility of the top 12 cryptocurrencies. By utilizing various data points and advanced algorithms, the platform provides traders with accurate insights into potential price fluctuations, enabling them to make more informed trading decisions.

Unlike traditional market analysis tools, the GNY Range Report acts as a centralized hub, collecting and consolidating all relevant information in one place. This ensures that traders have access to the most important data without feeling overwhelmed.

With its user-friendly interface and intuitive design, the GNY Range Report appeals 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 of all skill levels.

*GNY commissioned independent research firm Pureprofile to survey 100 cryptocurrency traders who trade at least $5,000 per month. The survey was conducted in July 2023 with respondents from the UK, US, Germany, Brazil, Hong Kong, Singapore, UAE and South Africa.market."


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