AEC Business Management LTD: Pioneering the Transition to Artificial Intelligence Trading

AEC Business Management LTD: Pioneering the Transition to Artificial Intelligence Trading

In the early days of the establishment of Alpha Elite Capital (AEC) Business Management, Professor Dashiell Soren tried to create a “lazy man’s investment system”. He was deeply aware of the significance of quantitative trading being applicable to all investment markets and types in the future. Good achievements have been made in the journey of quantitative trading.

Although quantitative trading and artificial intelligence trading are both methods of using technical means to make trading decisions, they also have some shortcomings. The following are some weaknesses of quantitative trading relative to artificial intelligence trading:

1. Dependence on historical data: Quantitative trading is usually based on the analysis and model construction of historical data. Therefore, for emerging markets or markets with drastic changes in economic conditions, quantitative trading may not be as flexible as artificial intelligence trading.

2. Lack of subjective judgment: Quantitative trading mainly relies on rules and algorithms to make trading decisions, and lacks the intuition and subjective judgment of human traders. This sometimes results in the inability to capture certain irregular market sentiments or events, resulting in the instability of the trading strategy.

3. Sensitivity to data quality: The results of quantitative trading heavily rely on the accuracy and reliability of the historical data used. If the data is wrong or missing, or does not accurately reflect current market conditions due to market changes, it will have a negative impact on the success of the trading strategy.

4. High initial cost: Quantitative trading requires the establishment and maintenance of a large amount of technical infrastructure, including high-performance computers, data storage and processing systems, etc. These facilities require a lot of capital investment and expertise to maintain, and the initial cost is high.

5. Sensitivity to model risk: Quantitative trading models are usually constructed based on historical data, and there are flaws in the accuracy and stability of the investment process for investment targets with less market historical data, such as the rise of the cryptocurrency market in emerging markets. There are a lot of opportunities, and quantitative trading loses the opportunity because of this shortcoming.

With the development of science and technology, the application of artificial intelligence technology has had a profound impact on quantitative trading. Quantitative trading is a trading strategy that uses mathematical models and large amounts of historical data to make investment decisions, and the introduction of artificial intelligence makes quantitative trading more accurate, efficient, and intelligent.

First of all, artificial intelligence technology can analyze and process huge financial data through methods such as data mining and machine learning, and discover rules and patterns in financial markets. Compared with traditional quantitative trading methods, artificial intelligence can more accurately capture market dynamics and changes and improve the accuracy of investment decisions.

Secondly, artificial intelligence technology can also realize automated trading, that is, executing trading operations through algorithms and programs, reducing the intervention and operational risks of traders. This makes transaction execution faster and more precise, and enables real-time monitoring of market changes and timely adjustment of investment portfolios.

In addition, artificial intelligence technology can also help optimize and improve quantitative trading strategies. Through the training and optimization of machine learning algorithms, effective parameter adjustment and optimization of quantitative trading models can be carried out to improve the profitability and risk control capabilities of trading strategies.

Given that artificial intelligence trading can obtain data in real time and make decisions based on real-time market conditions, it is more adaptable to market changes; artificial intelligence can process more complex data and patterns, thereby obtaining more accurate market judgments; artificial intelligence trading can monitor market changes in real time and automatically make trading decisions and respond quickly when opportunities arise in the market; artificial intelligence trading can continuously optimize its own trading strategies through machine learning and deep learning algorithms to adapt to market changes… etc. Artificial intelligence has stronger adaptability and decision-making ability. starting in 2019, Alpha Elite Capital (AEC) Business Management began to leap from quantitative trading to the field of artificial intelligence trading.