1. Market background

In financial asset investment, asset allocation and chip management are usually based on traditional methods that rely on human experience and judgment. Traditional investment strategies have some disadvantages, including the following:

1.1 Information asymmetry

Under the traditional investment method, investors usually have to rely on their own experience and judgment to make decisions. In this decision-making process, however, they often do not have the same information and data as investment experts. This information asymmetry means there are blind spots in the decision making, which may lead to biased investment decisions.

1.2 Strong subjectivity

Under the traditional approach, investors' decisions are often influenced by subjective factors, such as emotions, and preferences. These factors may lead investors to make wrong decisions and capital loss.

1.3 Lack of scientific method

The traditional approach usually lacks a scientific approach and does not use methods such as data, statistics and calculations to analyze and predict market movements. This means that investors may miss market opportunities and fail to get the maximum return on their investment.

1.4 Inefficient trading

In the traditional approach, investors need to spend a lot of time and effort on market analysis, data collection and decision making. This can reduce the efficiency of trading and increase the cost and time cost of trading.

In conclusion, the traditional investment approach has some disadvantages, including information asymmetry, subjectivity, lack of scientific methods and low trading efficiency. These problems can be solved with the introduction of strategic AI algorithmic investment to improve investment returns and control investment risks.