Launching Z-Score: AI-Powered Crypto Investments

Today, ZIGDAO introduces the highly anticipated AI-driven Z-Score, poised to revolutionize digital assets investing forever. This is a sea change for investors in the digital assets sphere as we lay the foundation for a future where AI leads to optimized decision-making & trading performance assessment, leaving no space for uncertainty or conjecture.

The latest innovation is powered by the team of Quant Traders and ML tech experts who delve deep into an extensive dataset of over 22 million trades from the past 5 years. The Z-Score uses intricate weighting and multifaceted factors, such as profitability, risk, and consistency, to score Traders and identify the best ones for the Investors. Not only that, but the powerful algo will be available to the Z-Prime traders to enhance their experience further and optimize returns for their communities.

With Z-Score, the focus extends far beyond profits. The AI evaluates a range of factors, all with one mission:

To ensure that only the finest traders are accessible to our investors.

Let’s delve into each category and the unique role it plays in the process of assessing performance and ranking traders:

• Risk: Engaging in trading without effective risk management is typically an unfavorable approach. Z-Score takes into consideration a range of risk metrics, including ‘Max Drawdown’ and ‘Sharpe ratio,’ among others, in order to gauge the trader’s risk profile, which is then prominently displayed on their service card. At ZIGDAO, we place a profound emphasis on risk management, and it is a pivotal component in every trader’s Z-Score assessment. The focus is not just on profits but also on the quality of those profits by taking into account the risk that is taken in achieving them.
• Profits & Benchmarking: Is the trader outperforming the market, or would the investor have fared better by holding a diversified portfolio of leading tokens? This is another key consideration in the Trader’s Z-Score and is a novel attempt to introduce benchmarking in the digital assets sphere in line with traditional markets.
• Days in Profit: Another significant metric, ‘Days in Profit,’ allows Z-Score to gauge how often the trader achieves profitability. This metric holds great importance in assessing the trader’s consistency and filters out noise from market volatility that is a result of systematic factors and not the trader’s skill.
• Assets: The Z-Score factors in the varying scale of total assets under management by the Trader, assigning weightage accordingly. It recognizes the distinction between making a 50% return on $1,000 and achieving the same return while managing $1 Million, assigning weights accordingly.
• Timely Redemptions: Ensuring prompt redemptions for investors is our primary focus at, and the Z-Score takes this into consideration when assessing traders. Traders with elongated redemption periods will see their Z-Score negatively impacted.
• Responsible Leverage: Engaging in high-leverage trading poses risks and has a negative impact on the trader’s Z-Score — a lower leverage level results in a higher Z-Score.
• Asset Growth: The trader’s capacity to consistently attract new assets under management on the marketplace plays a crucial part in determining their Z-Score. Consistently growing AUMs reflect greater trust in the trader and are analogous with all the other metrics defined above.

*Computations in the shared graphic is not up to date

Observing the Z-Score in action: The AI scrutinizes a trader’s performance by analyzing 14 sub-categories pertaining to profitability, service management, and risk management, resulting in the assignment of a performance-based Z-Score.

*Computations in the shared graphic is not up to date

In the depicted graphic, a comprehensive analysis is conducted, delving into computations segregated by distinct categories: i) Profits, ii) Service Management, iii) Risk Management, and iv) Balanced metrics (risk-to-reward ratio). On the far right, the AI assesses whether the Trader meets the predefined criteria.

Z-score — A Growth Catalyst to ZIGDAO & $ZIG

While the Z-Score enables AI-powered investments, it also fulfills a crucial role in promoting the sustainable growth of the ZIGDAO protocol, which directly reflects on $ZIG. Leveraging AI technology, ZIGDAO connects Investors with top-tier traders, translating into increased yields and ongoing revenue growth. Under the new ZIG BuyBack & Burn program, the protocol utilizes the earnings to buyback & burn $ZIG, solidifying its status as a truly deflationary token.