After the sharp decline in the stock market in 2022, the scale of many equity actively managed funds has retreated, but the management scale of equity ETFs has achieved a contrarian growth, and ETFs have been widely accepted by individual and institutional investors as a tool for investing in the stock market.
On the other hand, with the expansion of ETF funds, the number of industry and thematic ETFs has increased significantly in the past three years, and investors can choose from the subdivision direction.
However, the increase in the number of funds has also brought some troubles to investors, due to the differences in the preparation institutions, compilation methods, and product terms of the corresponding index, resulting in very different investment results, such as both called dividend ETFs, what is the difference between Shenzhen Securities Dividend and China Securities Dividend? The same artificial intelligence ETF, why is there so much difference in performance this year?
How many sector and thematic ETFs are there?
According to incomplete statistics, the number of hot industries and thematic ETFs such as new energy, TMT, health, and consumption reached 342, of which the number of ETFs in TMT, health and Hong Kong stocks was relatively the largest, all exceeding 60, and the number of ETFs in several other sectors also exceeded 20.
Why do sub-sectors have so different returns in the same sector, and what should I pay special attention to when choosing an ETF?
In the new energy sector, the theme of carbon neutrality fell relatively little, due to the small weight of power equipment, and the utility and non-ferrous metal industries contributed certain positive returns.
In the TMT sector, influenced by the concept of AI, AI topics such as computers, communications, artificial intelligence, and entertainment media generally outperform other directions such as chips and electronics. Since the beginning of this year, Hong Kong technology stocks have generally underperformed A-shares, and it is necessary to pay attention to whether the constituent stocks include Hong Kong stocks such as Tencent, Meituan, and Kuaishou.
In the consumption sector, topics such as online consumption and online consumption significantly outperform other consumer themes because of the higher weight of media and computers, which are all themes that benefit from AI.
In the big health sector, the Chinese Medicine Index stood out, with the CSI Chinese Medicine Index selecting the stocks of listed companies involved in the production and sales of Chinese medicines as constituent stocks, such as Pian Zixi and Tongrentang, while innovative drugs, vaccines, medical treatment and other themes generally declined.
In the Hong Kong stock sector, the Hang Seng Technology Index is quite different from the Hang Seng Internet, which includes not only Internet companies, but also new energy, chip, pharmaceutical and other technology companies.
In the central SOE sector, the theme of win-win and innovation of central enterprises performed relatively well, but the emphasis was different, and the high-interest coupons of traditional industries such as PetroChina, Sinopec, China Mobile, and China Telecom contributed significantly to the increase, while the innovation of central enterprises included many technology stocks such as iFLYTEK and SMIC.
In the dividend sector, SZSE dividends screen constituent stocks by the absolute amount of dividends, so the trend is closer to large-cap stock indexes such as CSI 300 and SSE 50.
In the financial real estate sector, the fintech theme can achieve a yield of close to 20%, and also benefits from the AI concept, and individual stocks such as flush, Inspur Information, and Wealth Trends have risen by more than 50%.
Specifically, what are the ETFs with similar abbreviations but with a large difference in net value trends?
For individual investors, the increase in the number of ETFs has brought convenience to investment, but to a certain extent, it has also increased the difficulty of selection, and many ETFs with similar names seem to have the same investment direction, but because of the differences in the compilation institutions, compilation methods, and product terms of the corresponding index, the investment results are also far from the same.
For example, they are all dividend ETFs, and the trend difference between CSI Dividend ETF (515080) and SZSE Dividend ETF (159905) is large, because there are certain differences between the compilation methods of CSI Dividend Index and SZSE Dividend Index.
The CSI Dividend Index focuses on the dividend rate of listed companies, which is more in line with investors' cognition of the high dividend strategy of dividends, while the Shenzhen Dividend Index considers the absolute dividend amount of listed companies, so the stock market value of the constituent stocks of the SZSE Dividend Index is generally large, and the trend is close to that of large-cap stock indexes such as the SSE 50 and CSI 300 Index.
The AI sector is one of the main lines of trading this year, but the AI ETF (159819) significantly outperformed the AI 50 ETF (517800).
The reason is that the artificial intelligence ETF tracks the CSI artificial intelligence thematic index, and the constituent stocks are all A-shares, while the artificial intelligence 50 ETF tracks the CSI Shanghai-Hong Kong-Shenzhen artificial intelligence 50 index, and some of the components are Hong Kong stocks, such as Tencent, Meituan, etc., which drags down the overall performance of the sector.
The author of this article: Huabao Securities Wang Kaichang, source: Huabao Securities Private Wealth, original title: "Industry Theme ETF: 300 Products, To Choose Carefully", with deletions
Wang Kaichang SAC practice certificate number: S0890623050004
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