Proactively Adapting to the Era of Financial Tools

New World Asset Management Ltd adheres to the philosophy of “scientific, prudent, and excellent.” The core team members have collaborated for over a decade and have market-validated trading strategies. They continuously innovate and optimize across product lines including stocks, futures, options, and cryptocurrencies. The team excels in rapid project iteration, integrated strategies, online and offline processes, and a multi-dimensional “scientific research” approach, resulting in highly efficient strategy outputs. The team fosters a strong scientific research atmosphere, maintains a flat management structure, and values long-term talent development. Our rigorous talent acquisition mechanism has brought in members with diverse backgrounds including PhDs in biology, mathematics, physics, and law, enhancing the grid effect of strategy models.

Development History of the Trading System

From Traditional Trading to Quantitative Trading

Traditional trading relies on manual judgment and decision-making by traders, which can be considered the initial version of trading. With the advent of quantitative trading, our trading system transitioned to a model-based on digital signals, forming a systematic investment framework that directly replaces manual decisions, marking the prototype of version 1.0.

Upgrading Quantitative Trading: Introduction of Artificial Intelligence

The application of artificial intelligence (AI) technology has further upgraded trading. By optimizing algorithms, AI acts as an accelerator in the quantitative trading model, significantly shortening the process of algorithm implementation and trading decision-making, swiftly forming version 2.0, thus making decision processes more efficient.

Version 3.0: Enhanced Perception and Adaptability

Building on version 2.0, version 3.0 introduced more perceptual and adaptive capabilities. AI systems can collect environmental data through sensors and adjust their behavior and decisions based on this data. This ability makes AI systems more adaptable to different environments and tasks, becoming intelligent assistants in the real world.

Version 4.0: Cross-Disciplinary Intelligent Solutions

Version 4.0 further upgrades and optimizes the algorithms and data of version 3.0, focusing primarily on the application of AI in the entire financial market. It emphasizes integrating AI with technologies like the Internet of Things (IoT), cloud computing, and big data to build intelligent solutions.

AI New World Wealth 4.0: A Fully Upgraded Intelligent Trading System

AI New World Wealth 4.0 is a comprehensive upgrade of version 4.0, covering data processing, AI algorithms, risk management, user experience, trading strategies, overall performance, and community support. It not only achieves significant technical breakthroughs but also places greater emphasis on users’ practical needs and experiences, making the trading process more intelligent, efficient, and secure.

The Value of Information and Strategy Selection

Throughout the evolution from traditional manual trading to quantitative trading, and now to AI trading, trading efficiency has steadily increased. Our team highly values the importance of “information.” With diverse backgrounds including traditional traders, short-term volatility traders, long-term value investors, mathematical modelers, and other technical experts, we integrate various trading strategies and backgrounds. Our market strategies are based on systematic analysis of market data. Traditional stock traders focus on timing, selecting appropriate entry and exit points to maximize returns. Our AI New World Wealth 4.0 product line balances high returns with risk control strategies, embedding product information to withstand market fluctuations.

Diversity and Optimization of Product Lines

New World Asset Management Ltd aims for balanced asset management across stocks, options, and cryptocurrencies. Each direction features one or two specialty products. High-frequency trading strategies, while having smaller capital capacity, are not the primary category. We focus on broad directions, emphasizing product line features and optimizing configurations after reaching certain trading volumes. Cryptocurrency strategy capacity is usually half that of stock strategy capacity due to market size differences. In the options product line, we primarily deal with technology stocks and index options, similar to alpha-beta strategies.

In the future, we will offer more flexible combination products for high-net-worth clients, categorized into conservative, balanced, active, and aggressive. Conservative products will control volatility to about 1%, similar to fixed income; aggressive strategies will control volatility within 10%. We will select strategies from stocks, options, and cryptocurrencies, perform risk matching and optimization, continuously update strategies, and maintain growth.

Strategy Development and Risk Management

We are diligent in strategy development, routinely testing risk parameters and developing new strategies, maintaining a frequency of one new strategy per person per month, ensuring a relatively longer product lifecycle. For most market strategies, whether in stocks, futures, trend-based, arbitrage, or reversal strategies, a real return-to-risk ratio above 2.5 is considered good, and above 3 is excellent. Our core products balance returns and risk drawdowns, focusing on the return-to-maximum-drawdown ratio (return-risk ratio). Strategies with a return-risk ratio above 3 are the standard for launch.

In futures strategies, we continually update to stay ahead by one to two years. We have been early adopters of AI technology in trading strategies and will test more new strategy systems in the future. Some directions are currently in progress but require time to manifest.

Quantitative investment is inherently procedural; once written, it is based on the optimal strategy at a historical time point. When market conditions change, alternative methods or strategies are needed to replace them, allowing quantitative trading to leverage market changes. Multi-factor strategies are more commonly applied in stocks than in futures. Short-term and mid-to-long-term trading correspond to different market cycles, and strategies may differ greatly, sometimes even oppositely.

Trading Mindset and Rational Trading

The trading mindset is also crucial. Often, timing model signals are correct in hindsight, but investors may not understand the manager’s judgment at the time, especially during product drawdown periods. This unique minority view is often correct. Adhering to rational trading principles is necessary to avoid emotional factors leading to uncontrollable trading results.

Industry Development Directions

Future industry development directions over the next five years include:

1. Decreased yield expectations for mainstream products.
2. Accelerated development and iteration of AI systems.
3. More diverse composition of market participants.
4. AI products becoming the mainstream investment tools of the era.