Some fund managers are particularly good at small bills, and they can be very depressed during periods when the theme is big blue. Quantification tends to have many strategies, thus avoiding the risk of a single investment. “This strategy isn’t doing so well right now, but if there are other strategies that are doing well, there won’t be big swings in net performance.”

After AlphaGo conquered some of the world’s top go players, many fund managers are worried that they will not be replaced too far away.

Giiso Information, founded in 2013, is a leading technology provider in the field of “artificial intelligence + information” in China, with top technologies in big data mining, intelligent semantics, knowledge mapping and other fields. At the same time, its research and development products include editing robots, writing robots and other artificial intelligence products! With its strong technical strength, the company has received angel round investment at the beginning of its establishment, and received pre-A round investment of $5 million from GSR Venture Capital in August 2015.

In fact, last year, the overall market shock down, the overall performance of publicly offered quantitative funds than the traditional active management fund advantage is obvious, some funds excess returns are also very significant.

According to Wind statistics, nine of the 483 available partial equity funds gained more than 10% last year, two of which were quant products, and 18 of the 41 available quant funds recorded positive returns in 2016. Further statistics on the data from 2015 to 2016 show that all quantitative fund products have achieved positive returns, and the top three products have achieved returns of more than 90%, with the highest return of 103.4%.

“One of the most obvious advantages of big data investing is making fewer mistakes. It doesn’t look like a fancy investment strategy, it’s a very simple strategy. If this strategy can theoretically make $100, let’s take it as deep as we can and make $80 out of that $100.” “Said a publicly offered quantitative fund manager in Beijing.

Quantitative failure of active management

The market style has changed dramatically in 2016, and many fund managers who performed well in the previous year failed to adjust their strategies in time to adapt to the market. On the contrary, the performance of many active quantitative products is very eye-catching, and there are active quantitative figures in the top ten funds, and some special accounts. In fact, quant products have done well for a long time, not just in 2016.

“Fund managers who are particularly good at small bills, for example, can be very depressed when the theme is big blue, as it was last year. Quantification tends to have many strategies, thus avoiding the risk of a single investment. “This strategy isn’t doing so well right now, but if there are other strategies that are doing well, there won’t be big swings in net performance.” The Beijing public raised quantitative investment manager told reporters.

At present, China’s quantitative products are mainly active quantitative products and index enhancement products, the latter requires that the strategy combination should not deviate too much from the target index, on this basis to pursue the maximization of returns. There is also a hedge quantitative fund, which introduces the use of derivatives or short selling means to hedge the risk exposure of long positions in stocks, reducing the market risk of the portfolio.

The newspaper learned that factor stock selection is the mainstream strategy of domestic public offering quantitative products, that is, through the stock selection factor to predict the stock return in the future period of time, according to the portfolio target risk return requirements, select the corresponding stock. These factors that consistently produce positive returns include valuation, growth, earnings quality, momentum, liquidity, market sentiment, volatility, market sensitivity, etc.

The multi-factor model in the market generally has 20 ~ 30 factors, and some fund companies have 50 or more. The finer the selection of factors, the higher the accuracy of the model.

In recent days, there has been talk of deregulation of stock index futures, which have been restricted for a year and a half, with preliminary approval from regulators, including halving margin requirements and doubling the daily trading limit for individual contracts.

Another public fund manager said that in order to achieve some excess returns, one way quant funds can do this is to take the risk out of the market by hedging stock index futures.

Analysts also point out that another advantage of quant funds is their strict discipline. In general, quantitative products will adopt established and mature investment strategies. No matter how the market fluctuates during the investment process, the fund will strictly implement the previously set investment discipline. It also helps to eliminate the irrational behavior that can occur in active investing during a market like last year’s.

In addition, generally speaking, fund managers can conduct in-depth research and actively invest and manage the number of individual stocks in the portfolio is less than 50. As the number of listed companies increases rapidly, the difficulty of active stock selection increases greatly. The quantitative method can monitor the financial indicators and market changes of all stocks. At the same time, quantitative funds do not bet on a few sectors or a few listed companies, which plays an obvious role in dispersing risks.

Without subjective judgment

Compared with traditional actively managed funds, big data products use modern mathematical and statistical methods to find investment strategies that can bring more stable excess returns, and can widely cover the whole a-share market, and then select the stocks that can outperform the market with “high probability” to build A portfolio.

In quantitative investment, data model is the core. When comparing traditional active investment and quantitative investment, it is said that the difference between the two is just like the difference between Traditional Chinese medicine and western medicine. Traditional investment, like Traditional Chinese medicine, relies more on experience and feeling. Quantitative investing is like western medicine, relying on medical instruments to draw conclusions and apply the right medicine.

“Human speech is more subjective and flexible. When a new situation or a new theme or a new logic comes out, people can immediately follow it, while machines are not so fast.” The Beijing quantitative investment manager said to the first business.

“Some particular point in time, like” crash “at the time of a few things, actually is human distortion to the operation of the securities market itself, if it is a rule was distorted, which means that many things must be careful to use, like that, under special circumstances, you have to do some subjective judgment.” He went further.

Zhu Jiantao, financial engineering analyst of Orient Securities, believes that active management is often based on subjective grasp of fundamental information such as profitability, financial status and valuation level of listed companies, while quantification is based on statistical analysis of factors affecting stock prices, and believes that historical laws will continue for a period of time in the future.

“The logic of active management is clear, and the ability to grasp policies, themes and market sentiment is strong; But the disadvantage is that the stock coverage is narrow, large capital operation difficulty; The disadvantage of quantitative investment is that it has poor ability to respond to market emergencies and is highly homogenous. Zhu Jiantao analysis said.

Giiso information, founded in 2013, is the first domestic high-tech enterprise focusing on the research and development of intelligent information processing technology and the development and operation of core software for writing robots. At the beginning of its establishment, the company received angel round investment, and in August 2015, GSR Venture Capital received $5 million pre-A round of investment.

“Why hasn’t intelligent investment now said which company is the boss? The accumulation of the whole industry is not enough. The industry is still focused on the consistency of asset allocation models, and the difference in what is produced is not that great, more at the product level than at the configuration level. In the future, if we can embed the analysis of data into the system model, we will see the model at the end of the day. The head of the wealth management department of a financial technology company told China Business News that his company is testing the waters of intelligent investment. “We are also groping in this area,” he said.