Smart Investment Advisor is an industry application that emerged with the rise of digital technologies such as artificial intelligence, big data, and blockchain. It provides customers with quantitative investment analysis and advice on financial management decisions. It first appeared in foreign countries in 2008. The financial Rubik's Cube was the first smart investment app in China and was formally launched in September 2015. Up to now, there are about 10,000 traders and a total of 450 million transactions. This million people, they became the pioneers of domestic investment advice given by robots....
The core is to solve the efficiency problem of investmentMa Yongbiao, financial advisor of Rubik's Cube, who once served as the director of operations of the Galaxy Securities Fund Research Institute, said, “I have done a statistic from the large customers and small customers I have contacted. The probability of small customers losing money is as high as 70% to 80. %, this is a very cruel reality."
Ma Yongyong pointed out that although small clients pay attention to information and pay attention to investment proposals of fund companies, he does not know when they should buy or withdraw, nor does he know how to buy products to reduce risks and stop losses in time, causing losses. “Wrong decisions are made under incomplete information, which is a common problem among small customers.â€
These problems have become pain points for small client funds. “So, what methods can be used to provide close-fitting investment consultancy services for large customers are also provided to small customers to solve the class gap in wealth management and the greatest injustice? Everyone has the right to participate in financial management.â€
In the United States, because the market has been nurturing for decades, a large and highly efficient team of human consultants has been established. However, this is not enough to meet the needs of US customers. "In contrast, the domestic market must establish such a It is almost impossible for a team to meet the needs of a wide range of client financial advisors. Therefore, we think of using the Internet and IT technologies to realize this idea."
According to Yuan Yu-Lian, CEO of Financial Rubik's Cube, the core value of investment advisors is to solve the problem of risk identification, product mix, and trading timing in the financial management process. For a human investigator, calculating these problems requires a large amount of data and follow-up surveys of customers. Their energy is limited to serving more than 20 customers per month, which is limited, so they will only choose a large rate of return. customer service. Therefore, in fact, the core issue of the wealth management market is the efficiency of investment consultants, not the level. Therefore, the emergence of intelligent investment and care, at the present stage, first of all reached a level of qualified investment and solved the problem of efficiency.
Zhou Wei, co-founder of Financial Rubik's Cube, said that traditional private banks and wealth management agencies are mainly targeting high-net-worth individuals who started investing 6 million yuan, while the main target clients of the Rubik's Cube offer asset allocation services to low-net worth individuals with less than 3 million investment. A crowd is undoubtedly a huge group in the domestic market.
How to combine finance with IT?Yuan Yulai is a doctor of computer science at Tsinghua University. He was in charge of data mining at Intel, and he is the third venturer to manage Rubik's Cube. He said that the working process of human investment consultants is a rational analysis process, whether it is analyzing the customer's goals, market and product risks, etc., so it can be reconstructed and realized by computers. When doing this, it can be divided into four areas:
·Based on analysis of user's investment behavior and characteristic data. Artificial intelligence can help us understand a user's risk tolerance, investment objectives, and other various needs based on data analysis.
· Analyze the risks of markets and assets from qualitative and quantitative aspects through data collection, collation, cleaning, and mining of financial markets and financial products, use artificial intelligence to screen different product mixes at different market stages, and optimize investment product portfolios. .
· Analyze historical data and forecast future trends, make information analysis structures and asset allocations at different time points, and make recommendations.
· Lastly, since the public fund is a long-term investment, the market will continue to change, and investors need to track and adjust users. Intelligent investment consultants rely on algorithms to track the investment of users, which is equivalent to after-sales assessment, and then judges when the market changes and the user's risk match, and when it needs to remind users to control risks, such as reducing investment proportions and other transactions.
It is understood that by cooperating with the Central University of Finance and Analysys Think Tank and other institutions, the Rubik's Cube has collected data on 500,000 financial products and more than 2,000 financial sales platforms in the country through data search instead of docking interfaces. The standard data, real-time updating the bid ranking, users can track the risk and return of the purchase of products. "After getting data from a third party, we will sort out and clean the data to ensure that the data entered is accurate."
As for the algorithms for completing these data mining and analysis, Yuan Yulai said that in addition to using big data such as classical support vector machines, decision trees, Monte Carlo simulations, etc., they adjusted the combination of parameters and algorithms according to the characteristics of the financial sector, combining the Strategy, build your own financial model and algorithm model.
As the latest report of the Boston Consulting Group pointed out, financial technology is a fusion of finance and IT technology and coordination. In terms of financial technology, according to reports, Financial Rubik's Cube and Central University of Finance and Analysys developed a set of financial products risk rating, a total of ten risk levels, updated once a month.
So here, how is the most important asset portfolio configuration completed?
In general, professional wealth management models such as professional investment institutions and high-end private banks are generally derived from Markowitz's "investment portfolio theory." The theory was proposed in 1952 and won the 1990 Nobel Prize in Economics. In recent years, especially in the smart investment industry, the “Black-Litterman model†has been selected, and the financial puzzle has also shifted from the former to the latter.
The so-called Markowitz portfolio theory refers to the portfolio effective boundary model. It uses “mean-variance†to describe these two key factors, and studies how “reasonable investors†should choose income and risk in securities investment decision-making. The problem of combination.
Therefore, the above optimized investment portfolio is drawn in a two-dimensional plane with the horizontal axis of the volatility and the vertical axis of the yield, forming a curve. There is a point on this curve, which has the lowest volatility. It is called the minimum variance point (abbreviated as MVP). The part of the curve above the minimum variance is the famous (Markovitz) portfolio effective boundary, and the corresponding portfolio is called the effective portfolio. The investment portfolio has a monotonically increasing concave curve.
If the investment scope does not include risk-free assets (the risk-free assets have zero volatility), the curve AMB is a typical effective boundary. Point A corresponds to the highest yielding securities in the investment range.
However, Zhou Wei explained that, as can be seen from the above, the unconstrained "mean-variance" optimization model has the potential to produce relatively extreme asset allocations, such as strong shorting of an asset; and the production mix is ​​expected for the input asset. The change in the value of returns is very sensitive and other issues. So, given these restrictions, two of Goldman's traders, Fischer Black and Robert Litterman, proposed the Black-Litterman asset allocation model.
The Black-Litterman model uses the Bayesian approach to combine investor's subjective view of the expected return of one or more assets with the market equilibrium vector of expected returns under prior distribution to form a new estimate of expected returns. This new profit vector based on the posterior distribution can be seen as a weighted average of investors' opinions and market equilibrium returns.
The financial Rubik's Cube stated that the “BL model†is an optimization of the Markowitz model, which overcomes the weakness of the parameter sensitivity of the Markowitz model and also adds to the expectations of the future market.
"The real technical test of smart investment has not yet arrived"Baidu CEO Robin Li said at the second quarter financial report analysis meeting that while it is not yet possible to predict how artificial intelligence + finance will develop in two to three years, it does have huge market potential. In the face of smart investment advice, the voice of the industry is also more questionable than affirmation, but it cannot be denied that this is an inevitable trend.
"Pseudo-AI," "not so smart," "difficult to land in the Chinese market" and other issues, perhaps this is in the current market, after all, emerging technologies require an iterative and perfect process. Yuan Yulai pointed out that with the growth of the smart investment market, new demands will be born. The task of smart investment at this stage is not to replace human investment, but to achieve the goal of qualified investment and efficiency. problem. After waiting for more capital to enter, the real test of intelligent investment and care technology is truly coming. At this stage, the technical field is the core stage of development.
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