◎Reporter Wang Peng
Since the beginning of this year, the trend of A-shares has been ups and downs, showing obvious structural trends, making it more difficult to make money. However, there are still some active equity funds that have achieved good investment returns with excellent investment strategies. Take the Morgan Stanley Digital Economy Hybrid managed by Lei Zhiyong, deputy director of the Equity Investment Department of Morgan Stanley Funds, as an example. As of the end of August, the net value of the fund has increased by more than 20% this year, ranking among the top among partial stock hybrid funds.
Lei Zhiyong has rich experience in research and investment in the technology field, and is one of the few fund managers in the industry with work experience in the technology industry. He is good at comparing the prosperity of meso-level industries, selecting high-prosperity subdivisions to explore high-quality stocks, and is good at evaluating the investment value of companies from the perspective of industrial investment.
Layout high-certainty assets
Looking at the regular reports of Morgan Stanley Digital Economy Mix, we can find that the fund has been deploying the artificial intelligence computing power sector since the second quarter of last year. In the second half of last year, it further increased its position and closely tracked changes in the industry chain. The position structure has been optimized.
Lei Zhiyong said frankly that the A-share market as a whole has shown a defensive style this year, and there are two types of assets that have clearly outperformed the market, namely high dividends and artificial intelligence computing power. "These two directions seem to be two different assets, but they essentially embody the same investment idea, that is, defense. This also reflects investors' demand for certainty in the current macro environment." Lei Zhiyong said.
Many investors believe that dividend assets can outperform the market in the current and future macro environment, so they have increased their purchases of such assets. Lei Zhiyong said: "What is interested in artificial intelligence computing power assets is another type of fund, which pursues the certainty of growth. Tracking the giants of the US AI industry chain, we can find that starting from the second half of last year, the number of funds in the AI industry chain The company’s orders have increased significantly, and even supply exceeds demand, and the certainty of performance growth is very high. This is similar to high-dividend assets, so these two types of assets have been rising since last year.”
Lei Zhiyong said frankly that when reviewing the market from 2011 to 2013, the A-share market at that time also faced greater adjustment pressure, but growth-style assets related to smartphones performed better. He said that at that time, it was in the technological growth cycle of switching from feature phones to smartphones. In those years, the performance growth rate of the smartphone sector far outperformed other industries, so the overall growth rate of the sector outperformed the broader market. The same thing happened this year.
"The reason why Morgan Stanley's digital economy mixed return rate is relatively good is because we chose to deploy high-certainty assets. Since the second half of last year, we have increased our allocation position in AI computing power. At that time, our research found that optical modules The increase in orders from manufacturers is very clear, and TSMC’s order outlook also reflects that CoWoS packaging production capacity is in short supply. This information reflects the high certainty of the performance growth of the AI industry chain. Therefore, since the beginning of the year, especially since the Spring Festival holiday, the combination has been strong. Some of the stocks rose significantly, making a greater contribution to the increase in the fund's net value," Lei Zhiyong said.
In addition, the outstanding performance also benefited from the continuous optimization of the position structure. Lei Zhiyong revealed that in the process of tracking the industry, he found that in addition to developing computing power in the cloud, giants at home and abroad have also begun to evolve towards applications, especially smart terminals. In addition, giants represented by Apple have begun to deploy new products in mobile phone terminals.
"After industry comparison, we found that smart terminals and other directions are better than simple large models. Large models have performance problems. In the smart terminal industry chain, domestic companies can serve as supporting manufacturing industry chains and have order support." Lei Zhiyong said Based on the above logic, some positions on the AI terminal side were gradually added to the fund portfolio. This judgment has also been verified by the market.
Multi-dimensional selected stocks
When talking about how to screen individual stocks, Lei Zhiyong said that the company's position in the industry chain will be judged based on the evaluation of industry chain giants, its upstream and downstream supply chains, and competitors. In addition, executives and business backbones of listed companies will be interviewed to collect feedback from employees to understand the company's operating efficiency, cost control, order production, etc., and to judge the business development trend. Finally, study the key financial indicators such as accounts receivable and gross profit margin in the financial statements, conduct multi-dimensional comparisons, and select companies with better quality.
"After understanding the above information, when it comes to investment, as a fund manager, I will judge whether the current price is appropriate. We hope to buy the best company at the right price." Lei Zhiyong said.
However, in Lei Zhiyong’s view, selling points are more difficult to grasp than buying points. "The first situation is how to avoid selling prematurely. If the industry trend has not ended or is accelerating, even if the stock price reaches my target price, I will choose to sell in batches and reduce my position by one-third or more in stages. A quarter." Lei Zhiyong said.
If the judgment is wrong and the stock is not sold in time, resulting in huge floating losses, Lei Zhiyong will make different choices according to different situations. He said that if investment losses are due to a systematic decline in the market, and there are no problems with the fundamentals of individual stocks, or even the prosperity is improving, he will tend to continue to hold them. If conditions permit, we will even consider adding positions; if there is a problem with the company's fundamentals, we will sell decisively.
Talking about how to view the retracement of the portfolio's net value, Lei Zhiyong said frankly that the retracement of the net value is an unavoidable accompanying phenomenon in the capital market. No stock or index can only rise but not fall. He will focus more on judging stocks. In terms of fundamentals and industry prosperity.
"Only the fundamentals of the selected stocks can stand the test. After the retracement, the stock prices of these stocks will rise again or even reach new highs. This may be a more ideal way to deal with the retracement." Lei Zhiyong said.
AI development is far from reaching its peak
After experiencing a significant rise for a long period of time, how does the valuation of the AI industry chain match its performance? In this regard, Lei Zhiyong said that at the current point in time, this issue should be viewed from two dimensions. First of all, the AI industry chain is still in an upward boom cycle. Historically, the valuation PE of the new energy industry in the current year and the second year of this stage can reach 30 times to 40 times or even higher. The current market generally expects that optical modules and PCBs will correspond to 2025. The annual PE valuation is less than 20 times. Secondly, from a historical perspective, during the innovation cycle of TMT switching from 3G to 4G when the economy was booming, its price-to-earnings ratio was as high as 35 times or even 40 times in the second year. Therefore, whether it is compared horizontally with other industries or vertically with the individual stock industry chain, the current valuation and performance matching of the AI sector are relatively reasonable.
Compared with overseas markets, Lei Zhiyong believes that domestic fields such as humanoid robots, cloud computing, and chips already have certain competitive advantages and development potential. First, China has a large number of engineers and solid basic education, and engineers are very cost-effective. Second, the country has rich application scenarios and massive data accumulation, as well as a policy environment that encourages and supports innovation. These will help domestic enterprises occupy a favorable position in the innovation and development of emerging industries, and ultimately achieve overtaking in corners. .
Looking forward to the market outlook, Lei Zhiyong said that compared with other industries, orders and demand for AI industry products are still attractive, and the industry trend is still in an upward boom cycle. Judging from the tracking of the industry chain, the demand for cloud AI computing power is still in a good trend, and end-side products such as smartphones have begun to add AI functions. AI is expected to drive new growth for companies related to the end-side industry chain after the cloud. He is optimistic that AI will drive demand for cloud computing power and terminal consumer products. Morgan Stanley Digital Economy Mix will focus on the above directions and select companies with matching quality and valuation for allocation.
Looking to the future, Lei Zhiyong is optimistic about the AI industry chain. He believes that the vision of artificial intelligence is general artificial intelligence. Although there have been some adjustments in the artificial intelligence sector recently, judging from industry trends, the development of AI is far from reaching its peak. With the expansion of computing power and the continued evolution of large models, companies in the AI industry chain are expected to maintain rapid growth momentum.