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Why Read Research Reports#

You cannot do the same thing as others and expect better results.
—— Howard Marks

In the Chinese education system, the concept and training of "research reports" were relatively rare, at least in the 1980s and 1990s when I received my basic education—every question had a standard answer, and as long as you answered according to the teachings of the sages, or imagined how they would respond, getting high scores was not too difficult.
Traditional China was even more so; the process of education primarily involved reading and memorizing classics (which generally came from "sages") and the classic interpretations of those classics (which usually came from "wise men"). Both the classics and their interpretations were privileges to varying degrees. Imagine that an ordinary person in ancient times wrote a "research report" on the Four Books and Five Classics; they would often be seen as committing a great offense.
Such traditional social and cultural psychology often leads to two misunderstandings: one is an excessive diminishment of one's cognitive abilities; whenever people hear terms like "research report," "model," or "strategy," many, even if not frightened at the moment, will feel a sense of distance, a so-called "respectful avoidance." The second is an excessive deification of the cognitive abilities of "sages"; we always expect an ultimate solution to be eloquently revealed by a prophet who understands the secrets of how things work, and we then follow their lead, step by step, to reach the shores of happiness.
In fact, from encountering to becoming familiar, from familiarity to insight, and from insight to prophecy, this is an innate ability we all possess; being right or wrong is also our inherent right. On one hand, do not be intimidated by the name "research report"; try to approach this seemingly aloof yet fiery goddess. On the other hand, do not overly worship the "research report," doing whatever the goddess says, forgetting that you are an equal and independent subject.
Now is the era of "people"; we must get used to looking at each other as equals; and any cooperative relationship implies utilizing the strengths of the partner while also accepting their weaknesses.
Let me give an example. In the fable "Waiting by the Stump for Rabbits," the farmer's "model" is: rabbits will die by crashing into the stump (this actually happened); the conclusion of the "research report" is: waiting by the stump will yield meat. However, the "model" of the fable's author, Han Feizi, is that the probability of a rabbit dying by crashing into the stump is very low; the conclusion of the "research report" is: waiting by the stump is unlikely to yield meat, and instead, one might "be laughed at by the State of Song."
The choices of these two research reports are easy to decide. In actual investment processes, the situation can be a bit more complex, but not overly so; by the end of our journey, you will surely gain some insights. What I want to say is—
Although it can sometimes be a bit dry, all research reports have a logic, tell a story, and are a fable of investment.
Now, please put down your mental burdens; if you feel that research reports are not so hard to approach, we can continue discussing what research reports really are.

What is a Research Report?#

Definitions are always a tedious part, but to enter the world of research reports, we still need to spend three minutes to briefly discuss it.
Unless otherwise specified, the "research report" referred to in this book refers to the research reports published by securities companies to provide investment consulting services. We usually call it "sell-side research reports," which is relative to investors (the buy-side). In simple terms, these reports indicate which industries and companies are favored and what strategies are available, thus serving as a reference for investors' investment activities.
Here lies a paradox. You must be wondering: if an analyst is optimistic about a stock, wouldn't they just buy it themselves? Why would they kindly inform investors?
The answer to this question could fill 10,000 words; let’s simply use a few analogies to illustrate. First, why did Zhuge Liang not lead his own army but insist on following Liu Bei? Second, why did Sun Wukong not ride the cloud directly to the West but instead serve Tang Seng? Third, why do Reuters and Bloomberg provide such fast and accurate information, yet they don't directly trade stocks? The first example emphasizes resources. The second emphasizes division of labor. The third emphasizes specialties or comparative advantages. I can assure you that the above explanations are extremely imprecise; fortunately, we do not need to focus on such a dull question. You just need to understand the analyst as a "strategist," "enforcer," or "reporter"; few can dominate an entire industry, and the investment consulting business has already been sufficient to support six to seven thousand people, allowing this industry to survive relatively independently.
Of course, many analysts have indeed become fund managers and have achieved success; many have also failed. As the research community's great god Gao Shanwen said, the reason he only does research and does not invest is that he lacks the decisiveness characteristic of fund managers. This is similar to Zhuge Liang not being as good at crying as Liu Bei, Sun Wukong not being a scripture seeker, and Reuters and Bloomberg not specializing in stock trading; it is essentially the same reasoning.

What Types of Research Reports Are There?#

The research reports shown in this section do not represent a recommendation for related analysts; which analysts to recommend will be discussed in a later chapter.
If various types of research reports formed a class, we could understand the classification of research reports as follows:

Macroeconomic Research: The Homeroom Teacher, a Chinese Language Teacher.#

Generally understood, just as Chinese is the starting point for all learning,

macroeconomic research is the source of other research, because people usually view the stock market and bond market as reflections of the macroeconomic fundamentals. The homeroom teacher must care about students' grades (the operation of the macroeconomy), which leads to research reports on various economic indicators (GDP, CPI, PPI, fixed investment, industrial added value, imports and exports) and leading indicators (PMI, electricity generation, blast furnace operation, real estate sales); the homeroom teacher must care about the class atmosphere, which leads to research reports on liquidity (money supply, social financing, interest rates, exchange rates); they must care about important policy regulations from the school, which leads to relevant macro thematic reports (such as supply-side reform, Xiong'an New Area, military reform, state-owned enterprise reform, etc.); they must care about the situation in other classes, which leads to research reports on the world economy.
In short, starting from the macro perspective to look at research reports is an optional path. Especially now, excellent analysts at the forefront of the analyst team are usually able to explain logic in an accessible manner, making it suitable for readers whose foundation in economics is not solid (like myself).

Figure 1-1 A typical macroeconomic research report (Source: CITIC Construction Investment Securities, Huang Wentao)

Bond Research: Also known as fixed income research, it is the representative of the Chinese language class. As mentioned, the homeroom teacher teaches Chinese, so the status of bond research is quite special. Friends who trade stocks may not feel this, so they haven't made it the class leader, but it is actually very close to the homeroom teacher—many macro analysts are actually bond analysts, wearing two hats. The uniqueness of the bond market has two points: one is the institutional market, and the other is the funding market. In other words, the bond market reflects the basic liquidity situation of the financial market (all big money is played by large institutions). Of course, I dare to say that if you just trade stocks casually, not caring about bond research is almost fine, so I won't elaborate further.

Figure 1-2 A typical bond/fixed income research report (Source: Guosen Securities, Dong Dezhi)

Strategy Research: The Class Monitor.#

Non-professionals often get stuck on the two words "strategy," which simply means: what you should buy and what you should not buy. The relationship between strategy research and macro research is also quite close—the class monitor is essentially the homeroom teacher—there is quite a bit of overlap in some areas; the relationship between strategy research and industry research is also close—the class monitor is an important channel for connecting classmates. Therefore, strategy is both a carrier for macro "implementation" and a pathway for industry research to "enter the hall." From another perspective, strategy is also squeezed by macro and industry, caught in a sandwich: if macro is bearish, strategy theoretically does not look good (but in practice, there are instances where macro and strategy diverge within the same institution), and if industry research is optimistic about a certain industry, and strategy ignores it, then when that industry rises sharply, strategy will also lose face. In previous years, strategy research was once considered quite awkward because its territory was too much encroached upon by macro and industry. However, in the past two years, strategy research seems to be welcoming a happy moment again.
Thus, strategy is a comprehensive summary of an institution; each year, the annual and quarterly strategies of various brokerages receive widespread attention. The well-known stock combinations, industry recommendations, and thematic recommendations are mostly aggregated in the strategy section. When reading research reports, starting with macro, then strategy, and finally industry, or starting with the mutual verification of strategy and macro before moving to industry, is the ideal entry path.
To add, strategy may also involve some themes, which could be concepts, industries, new stocks, quantitative analysis, or even sentiment (such as the "sell in May" curse), etc., all of which can become strategies. Therefore, those who dominate this field are often seasoned veterans; most of the stock comments you are familiar with come from here.

Figure 1-3 A typical strategy report (Source: Ping An Securities, Wei Wei)

Industry Research: Subject Representatives. In fact, industry research and company research are done by the same group of people, or industry research is more focused on by team leaders, while company research is closely followed by researchers—both are done by the same group of people. However, since this is the focus of our reading of research reports, I will divide them more finely, separating industry research from company research. Generally speaking, the titles of industry research reports are of the A+B type, where A is the industry and B is the viewpoint. Industry research can be specifically divided into industry topics, data, dynamics, brief comments, and industry strategies, broadly speaking, it tells you whether the relevant industry is good or not, whether it is worth investing; which companies in the industry chain are good; what characteristics each company in a certain industry has, and which companies are better, etc.
Here, I want to emphasize: starting from the industry, research reports become more detailed, for example, ratings will appear. Typically, ratings indicate how much more a stock can rise relative to the market (such as the CSI 300 index or other benchmark indices) over a certain period (for example, within six months). Of course, we will discuss how to view these ratings later.

Figure 1-4 A typical industry research report (Source: Zhongtai Securities, Du Hui)

Company Research: Ordinary Students. Isn't this positioning a bit hurtful to company researchers? I am probably just referring to the quantity; company research reports indeed make up the largest portion of brokerage research reports. Company research has the following characteristics:
First, it is down-to-earth. Trading stocks is about buying companies; regardless of macro or sectors, if I am optimistic about this company, I will just buy it. In fact, many professional investors adhere to a "bottom-up" stock selection method. Among ordinary investors, there are indeed many cases where they buy after reading company research reports or after hearing recommendations for a particular stock, looking for a few reports to read as a reason to buy. It can be said that company research reports are the closest to ordinary investors, especially the appealing "stories" within them.
Second, it is straightforward. Company research reports contain a large number of ratings, and even further: target prices, along with many performance forecasts (earnings per share, net profit, return on equity for the next 1 to N years, etc.), which are very direct and blunt.
Third, they have broad coverage and quick responses. Statistics show that from 2001 to 2014, 75% of listed companies in China had analysts tracking them, and over 50% of companies were covered by three or more analysts (Yan Jiawei from GF Securities). Think about it, with so many people "eyeing" a company, any major or minor event is bound to be analyzed immediately.
Fourth, there are many ineffective products. From the perspective of research report users, this is reasonable; from the analyst's perspective, it may be a bit unfair. It is actually like reading political news in newspapers; many pages are the same, so there is no need to subscribe to so many political newspapers; however, every newspaper's editors and reporters are putting in effort. My suggestion is to skip most commentary-type company research reports (almost all performance reviews and most event reviews) and focus on in-depth research.
Moreover, in-depth company research must be viewed in conjunction with industry research for mutual verification. From the perspective of actual investment, in a public information environment, industry-wide opportunities are often easier to grasp than those of a single company, with a relatively higher win rate; at the same time, recommendations for industries and companies from the same institution are likely to be synchronous, which also facilitates investors in grasping specific investment targets.

Figure 1-5 A typical company research report (Source: Tianfeng Securities, Zou Runfang)

Financial Engineering Research Reports: The Top Students in Competitions.#

This is a type I often read in my spare time, mainly as a means of admiration and expanding my knowledge. I am not good at statistics and mathematics, but there are often some interesting reports in the field of financial engineering.

Figure 1-6 A financial engineering research report (Source: Minsheng Securities, Xu Yuning)

Others.#

Other research reports also include fund research, futures research, market information, morning reports, etc., which will not be introduced one by one.
In 2006, when I first entered the stock market, I had the following conversation with a teacher:
Me: Can you help me see if this stock is good?
Teacher: How do you look at it?
Me: You've been trading stocks for so many years; you must know!
Teacher: A stock is like a person. If you randomly pull someone from the street and ask me to see if they are good, how would you suggest I do that?
Me: …
Yes, new investors often face thousands of unfamiliar faces, not knowing who is more worthy of trust. At this time, there happens to be a vast and detailed database in front of you, which you can call the Baidu or Zhihu of the stock world; why not utilize it? These black-and-white words, various detailed data, various dark histories, materials, and technologies are always better than spending money to seek advice from unreliable sources or asking friends—when they just exchange a few words, your real money is already invested; isn't that too childish?
So, as investor Howard Marks said, you cannot do what everyone else does and expect better results. When many people are intimidated by research reports, you should bravely approach them and warmly embrace them.
Do not be intimidated by the name "research report"; bravely approach them!

Where Can You See Research Reports?#

Once you know where to find them, the world becomes as small as a map; if you don't know where to find them, the world feels vast.
—— Liu Cixin, "The Three-Body Problem"
It should be said that obtaining research reports still has certain thresholds, let alone classification, retrieval, and sorting. Frankly speaking, I personally believe that paying for a good research report database is reasonable, but I also admit that for most ordinary people, this kind of payment can lead to regret.
In daily life, we often have this habitual thought: I paid, so I got/enjoyed it. But learning knowledge and skills is very different from consuming products and services. For example, enrolling your three-year-old son in a Go class does not mean he can truly learn Go; only by spending a lot of time supervising him and accompanying him through extensive practice can he possibly learn Go. Moreover, for the learning process, to a large extent, "learning" does not mean much; even the significance of "interest" is often not as great as we imagine; instead, "habit" and "persistence" may be more meaningful.
To elaborate further would be to delve into success studies, so I will stop here. I want to emphasize that systematically studying research reports has its thresholds, and it is far more than just money; the journey is quite long. Of course, as a practical publication, this book will provide some shortcuts—but in the eyes of true researchers, these shortcuts are probably detours because you will miss the opportunity to feel the vastness of the world.
Free Channels
Knowing that everyone likes free, let’s first talk about the free model. In fact, the free model has significant limitations, so our discussion will not be lengthy.
Currently, the main channels for obtaining research reports (main content) for free include the following:

Figure 1-7 The research report page of Sina Finance's "Research Report" channel
First, financial websites. The above image shows the homepage of Sina Finance's "Research Report" channel. I won't copy the URL because this database's functionality is relatively basic. Other major financial websites generally also have research report sections, but I won't introduce them all.
Why?
As soon as you randomly click on a research report, you will find that the content provided by financial websites is basically limited to research report summaries. That is, a content summary at the beginning of each report, usually 1-2 pages long, presenting the main conclusions of the report. Although the conclusions of the report are indeed the essence, from an investment perspective, only looking at the conclusions provides little guidance for investment activities, even if the conclusions are correct.
We not only need to know the "what" but also the "why," so we can improve accuracy, right? However, due to copyright and regulatory requirements, most public financial websites can only help you to this extent.
No worries, there are still other free channels.

Second, the personal and team WeChat public accounts of analysts.#

Currently, the behavior of disseminating research report content through WeChat public accounts has not been precisely defined by regulations; most of the content of research reports can be found on the relevant analysts' and teams' public accounts. Of course, in the usual understanding, this counts as opinions but cannot be considered investment advice.
I have compiled a list of some analysts and team public accounts that I have on hand; it should be noted that although public accounts are a free and convenient channel for obtaining research reports, there is an important issue: the classification and retrieval functions are basically unable to meet the needs. Of course, if you have determined long-term candidates to follow, then daily tracking is also feasible—it's just that determining long-term candidates is a significant problem. In any case, given the advantages of being free and convenient, let's overlook the functional issues. I have summarized some resources and made the following list:
Table 1-1 List of Analysts and Team Public Accounts

Checking so many public accounts is still quite tiring, and I haven't looked through all of them. Our discussion of free research report channels ends here. To summarize again, the advantage of free channels is that they are free, while the disadvantage is that they are not systematic and have simple functions (a byproduct of being free).
Paid Channels
First of all, I want to say that the content of paid channels' research reports is all very good. I have used several paid research report platforms or paid terminals' research report channels, such as Wind (Wande), Choice (a financial data platform under Dongfang Caifu), Chaoyang Yongxu, Maibo Huijin, and Zhiqiu, among others. Among them, "Zhiqiu" is the platform I use most frequently. I will introduce it briefly later.
The other platforms are also quite good; relatively speaking, the cheapest paid platform, Choice, is relatively poor, as it has fewer aggregated research reports and research institutions, but this terminal costs less than 1,000 yuan a year, which is just the cost of a meal for three to five friends gathering in Shanghai or Beijing; what more do you want?
Another surprise is that the research reports and research institutions aggregated by Wind, which I originally thought would be quite comprehensive, are actually not as comprehensive as I imagined, and Wind is notoriously expensive, so it is difficult for Wind to become a choice for ordinary investors.
Chaoyang Yongxu's database is good, of course, the price is also good.
However, I want to say that if you spend money, the above several channels are basically sufficient, and their functions are all good. Of course, to facilitate everyone in selecting a suitable research report platform, I will take "Zhiqiu" as an example to introduce what functions an ideal research report platform should have and what benefits it brings us in reading research reports.
First is the classification function of research reports. Table 1-2 shows a primary classification list of a platform. This content is not particularly rare because many free channels also have such classifications.

Table 1-2 Primary Classification of Research Report Platforms#

This classification still does not meet our needs; for example, if we want to find in-depth research reports on the electronics industry, just clicking on "industry research" will yield many results, and the range is very imprecise. Therefore, we need secondary classifications, as shown in Table 1-3.

Table 1-3 Secondary Classification of Research Report Platforms

Under the above requirements, if you click on "industry strategy depth," you will get various industry strategy depth reports, but it still cannot focus on the electronics industry. In other words, if we were to locate this using a coordinate system, currently, you can determine the longitude of "industry research + industry strategy depth," but you still lack a latitude; you just need to add a latitude. By adding "electronics industry" in the "industry" option, a complete coordinate is formed.

In the above image, you can see that the example platform uses conditions like industry, column, type, etc., to gradually narrow down your query range. Of course, you can continue to add other conditions, such as company (code), analyst, institution, etc., to continuously expand or narrow your range until you filter out the reports that best meet your needs.
Just from the perspective of classification, you can see the functions of a professional research report platform. Readers often wonder why Qiqilu can find so many similar research reports on the same topic; it is simply because of the right tools and familiarity.

Second, the query function of research reports.#

Querying and classifying are actually two sides of the same coin; classification determines the logic, and as long as you query according to the logic, you can find what you want (though you may not find it). This is similar to the example of needing "in-depth research reports on the electronics industry."
However, it should be noted that single-level queries often cannot meet our needs. As you delve deeper into using it, your needs often emerge unexpectedly. For example, you may initially just want to see the annual investment strategy for the electronics industry, but during the process, you suddenly find that the Apple supply chain is repeatedly mentioned. At this point, your need changes to looking at the investment strategy for the Apple supply chain. When you search for the keyword "Apple supply chain," you will indeed find quite a few results, but if you only want to see the in-depth industry strategies among them, we can only solve the problem through multi-level searches. Relevant examples are as follows:

Figure 1-9 Example of "Apple Supply Chain In-Depth Industry Strategy"

I just want to say that such multi-level search arrangements are very suitable for our wildly divergent thinking and strong thirst for knowledge.
Third, the panorama of individual stocks and analysts. I think the panoramic views of these two aspects on the example platform are the most distinctive. Let's discuss them separately:

The above image uses Kweichow Moutai as an example, clearly showing the interaction between stock price trends and analyst consensus ratings and consensus EPS. In addition, the relevant page also aggregates all research reports, announcements, news, investigations, and interactive Q&A information about Kweichow Moutai. From the perspective of quickly understanding individual stocks, I think the design and content arrangement of this approach are very effective.
Now let’s take a look at the analyst panorama:

Figure 1-11 Example of the panoramic view of Guotai Junan analyst Ju Guoxian
The above image uses Guotai Junan's non-ferrous analyst Ju Guoxian as an example. The most distinctive feature of the relevant page is that it simulates the corresponding investment portfolio through the analyst's research reports, allowing for a clear understanding of the analyst's stock recommendation ability (of course, due to the involvement of machines and algorithms, as well as human definitions, the results may not fully reflect the analyst's ability). At the same time, the relevant page also lists the analyst's research reports and the stocks they cover, as well as the situations of other analysts from the same institution and other analysts in the same industry.

Fourth, popular research reports.#

From a game theory perspective, investing is like what economist Keynes said, a process of "picking the most beautiful woman in others' eyes," or in other words, only the beautiful woman you think is beautiful will not win the beauty contest; only the beautiful woman that everyone thinks is beautiful can win the contest. So, in this case, the research report you think is good is not a good research report; the research report that everyone thinks is good is a good research report. So how do we solve the problem of "what everyone thinks is good"? The logic is also simple: the more times a report is read, the more recognized it is.
Through the example platform, you will know which research reports everyone is looking at. For reasons we all know, research reports that everyone is reading are more likely to impact the market than those that no one is reading.

Figure 1-12 Example platform's "Popular" research report section on December 15, 2017
Alright, this section basically concludes here. Through this introduction, I believe you have a general understanding of how important a fully functional research report platform is for us to conduct research and learning. If you have the opportunity to choose a research report platform in the future, I suggest you filter based on the above simple criteria.
Although good research report channels are still very limited, I believe you will not bother to conduct such systematic research; that is the job of professional investors. As mentioned earlier, I will prepare some shortcuts for you.
In the next section, we will look at those shortcuts.

Currently, "Zhiqiu" still cannot provide research report services (including paid services) to ordinary investors; it only has a version for institutional clients at the moment. In the future, when the timing is right, they may launch a 2C product, but it will not be in the current product form.

Shortcuts to Reading Research Reports#

A good goal will never be abandoned because it comes slowly.
—— Abraham Lincoln, "First Inaugural Address"
Research reports are more suitable for value-oriented, relatively medium to long-term investments. Please remember this sentence.
The biggest taboo in reading research reports is "greed." Here, "greed" does not refer to money; greed for money is ultimately directed, and I prefer to consider it a relatively positive orientation. What I mean by "greed" mainly refers to having unrealistic expectations about things, and in many cases, the parties involved genuinely believe so. In this situation, I even think that pretending to believe and deceiving oneself through pretending to believe, if there is some benefit, is still considered good; the most troublesome is that kind of blind and heartfelt belief, which can neither bring material returns nor provide spiritual compensation.
When we read research reports, we must avoid this kind of "greed": "greed" leads to conclusions that are super accurate, "greed" leads to buying and rising, "greed" (using research reports to prove one's imprudent) leads to correct decisions.
In other words, you must calmly accept those incorrect research reports and regard them as an important part of normal research reports—just as if you love the beautiful scenery of the Hulunbuir Grassland, you must accept that there is untreated cow dung everywhere and countless thirsty mosquitoes and flies.
"Bad" research reports account for 15% to 20%
In fact, this portion is not large, only about 15% to 20%—of course, it could cause you significant losses—so it must be avoided.
Column 1: There are not many analysts who lead you into the ditch.

Figure 1-13 A "black" analyst joke circulating on WeChat
A long-standing misunderstanding, as the core part of the joke says: clients cannot make money from your stuff.
Today, we will use the big data tools of research report platforms to see whether analysts as a whole can help clients make money.
This tool is roughly as follows:

Figure 1-14 Performance of a certain analyst's recommended portfolio on the research report platform
It will capture the stocks recommended by analysts in research reports and construct the analyst's portfolio, allowing you to compare the portfolio's returns with the benchmark. Additionally, it can automatically generate a ranking of analyst portfolio returns based on time periods:

Figure 1-15 Performance of the analyst's recommended portfolio on the research report platform
Eighty percent of analysts can outperform the benchmark
According to this data tool, Qiqilu conducted a statistical analysis, concluding that during a certain time period, about 80% of analysts' portfolio performance can outperform the benchmark represented by the CSI 1000—because the representativeness of the Shanghai Composite Index may have issues, I chose the CSI 1000 as the benchmark, hoping to reflect the overall market more accurately.

The following is the statistical situation from January 1 to June 16, 2017:

Figure 1-16 Performance of analysts' portfolios from January 1 to June 16, 2017
The above statistical data shows that 40.12% of analysts can bring absolute returns through the recommended portfolios.
Considering the extremely obvious differentiation in the market in 2017, the CSI 1000 index can better represent the overall market (the vast majority of stocks fell), so we take this benchmark as the average level—then as high as 85.47% of analysts can achieve portfolio returns that outperform the market average.
The remaining 14.53% of analysts, sorry, I have nothing to say; they underperformed the market average represented by the CSI 1000.
At this point, you might say, is the statistical time too short? This might be an issue, but I think general research report users should expect analysts' portfolios to rise quickly, so six months should be a decent statistical period. From the user's perspective, I rarely see anyone who can patiently wait for more than a year.

But it doesn't matter; statistics are not difficult after all.

So the conclusion is: among ten analysts, 4 to 5 can definitely help you make money, 8 to 8.5 can help you outperform the market benchmark, and only 1.5 to 2 will lead you into the ditch.
This still basically conforms to the 80/20 rule, or in other words—overall, the overall level of the securities analysis industry is neither higher nor lower than that of other social industries. Therefore, the derived conclusion is that as a whole, securities analysts are neither better nor worse than other social industries.
If it is the so-called "chief of new wealth with an annual salary of tens of millions," due to the issues of standards and data screening, I did not produce results, but I can almost guarantee: with performance assessments being so direct (whether they can help buyers make money), and the fierce competition in the industry, their portfolio returns must be higher than the average level; if you don't believe it, we can bet.

Four Shortcuts to Reading Research Reports#

So, how should we read research reports? I have roughly summarized the following shortcuts:

First, pay attention to "consensus expectations."#

In 2014, Fangzheng Securities' Xia Ziyan stated in a research report that the number of analysts focusing on a stock and the rate of change should be an important observation indicator. Because "the more analysts focus on a stock, the deeper the market's understanding of it... reflecting market sentiment more reasonably and accurately," conversely, "the fewer analysts covering a stock, the lower the credibility of consensus expectations."
Yan Jiawei from GF Securities also showed that from 2007 to 2014, 25% of stocks in the Chinese stock market had no analyst coverage, and 25% of stocks had fewer than three analysts covering them.
In other words, for half of these stocks, it is better to adopt an ignoring attitude. When using research reports, it is best to look at those with many analysts covering them and closely tracked stock research reports. If you look at reports on obscure companies, you are likely to share the same mindset as the analysts writing obscure reports—just to get attention, and the result is likely to be: everyone knows it without saying.
Therefore, when selecting stocks based on research reports, it is mainly suitable for those stocks with more analysts focusing on them, and on this basis, conduct "cross-sectional" comparative analysis of analysts' viewpoints. If a stock has fewer than three analysts covering it, it is generally not advisable to use research reports to assist in decision-making.
The more analysts focus on a stock, the more there is a so-called "consensus expectation"; relatively speaking, the more consistent opinions there are, the stronger the guiding significance for investment may be. Of course, under the same conditions, if a stock performs stronger over a certain period, it is more likely to be recommended, and this bullish consensus may have smaller "odds," just like in a match between the Brazilian men's football team and the Chinese men's football team, where most people will bet on Brazil winning; although the winning chance is high, the amount each person wins will be small.

Second, pay attention to "specific indicators."#

One misconception is that an upgrade in a research report recommendation/rating is a reason to buy.
In fact, this is a false proposition; very few investors buy stocks based solely on this. In contrast, more often, the situation is that they have basically decided to buy and then use the research report to enhance their confidence or as a reason to buy.
So in this process, in most cases, what you believe in is what you only see.
At this point, a more prudent approach is not only to look at consensus expectations but also to look at the "specific indicators" of those consensus expectations, such as net profit.
In 2012, Zhongtou Securities' Zhu Mi concluded: "Consensus expectation data increasingly accurately predicts the net profit figures announced by listed companies."
In 2014, GF Securities' Shi Qingsheng provided a more detailed statement, citing: "When selecting stocks in the market, referring to profit forecast indicators is more advantageous; profit forecast indicators may be more effective for non-cyclical industries; market attention and sentiment indicators are more suitable for application in overall market stock selection, and this type of indicator tends to be applied in non-cyclical industries. We can also see which indicators are not suitable for application, such as valuation indicators performing poorly in selecting stocks in the ChiNext small-cap market, etc."

Third, correct the "annual report effect."#

In 2012, Zhongtou Securities' Huang Junjie pointed out, "It is worth mentioning that strategies constructed based on consensus expectation factors may have issues during the month of annual report releases." The main problem he pointed out comes from statistical caliber; during the annual report release period, the net profit growth rate data extracted from listed companies that have released annual reports and those that have not released annual reports is one that is updated and one that is not. Of course, there are subjective issues.
The subjective issue mainly involves a tacit rule in the research report industry: during the dense disclosure period of annual reports and quarterly reports, a large number of performance reports are disclosed, which will inevitably lead to a large number of performance commentary-type research reports, and these reports must give listed companies a recommended rating (otherwise, the listed companies may blacklist the analysts), and many research institutions require analysts to provide target prices (which can only be given arbitrarily), so the research reports during this period are likely to be distorted.

Therefore, the "annual report effect" must be corrected; the correction method is simply not to look at performance commentary-type research reports during this time, and it is better to look at in-depth reports after May each year.#

Fourth, research reports may be more suitable for value investing.#

According to Huabao's Zhang Qing's research report, using the PB-ROE (Price-to-Book Ratio - Return on Equity) stock selection model, this classic value investing method, adopting financial indicators published in financial reports yields low returns, with an annualized return of only 8%. This is because the indicators in financial reports have a lagging nature and do not fully consider the current or future situation of the company.

PB-ROE (Price-to-Book Ratio - Return on Equity) is a combined indicator for measuring company value. It combines Price-to-Book Ratio (PB) and Return on Equity (ROE), helping investors more comprehensively assess whether a company is worth investing in. Specifically, the PB-ROE concept focuses on the net asset return obtained on the basis of the price-to-book ratio.

1. Price-to-Book Ratio (PB)#

The price-to-book ratio is the ratio between a company's market value and its book net assets, calculated as:

[
PB = \frac{\text{Market Value}}{\text{Net Assets}} = \frac{\text{Stock Price} \times \text{Total Shares}}{\text{Net Assets}}
]

The price-to-book ratio can be used to assess how the market prices a stock relative to the company's book value; generally, a lower price-to-book ratio indicates that the stock may be undervalued, while a higher price-to-book ratio suggests that the stock may be overvalued.

2. Return on Equity (ROE)#

Return on equity is the ratio of a company's net profit to shareholder equity (i.e., net assets), calculated as:

[
ROE = \frac{\text{Net Profit}}{\text{Shareholder Equity}} \times 100%
]

ROE measures a company's ability to generate profit from shareholder investments. A higher ROE usually indicates that the company is more efficient in utilizing capital.

3. PB-ROE Combined Analysis#

PB-ROE combines these two indicators to provide a more comprehensive perspective on whether a company's stock price is reasonable. The basic idea is:

• The lower the PB and the higher the ROE, the better the return generated by the company's equity, while the market value is relatively low, which may indicate that the company is undervalued.
• If the PB is high and the ROE is low, it may indicate that the market has overly high expectations for the company's future growth, while the company has not effectively utilized its capital to generate corresponding returns.

4. Application of PB-ROE#

Investors can use the combination of PB and ROE to better assess companies. For example:

• High ROE and low PB: Typically considered undervalued and high-return stocks, which are likely targets for value investors.
• Low ROE and high PB: Typically indicates that the company's market value may be overvalued, or the company's profitability is weak, which may not be an ideal investment target.

5. Practical Application#

When analyzing stocks, investors can use PB-ROE to identify companies with low stock prices but high profitability, or high stock prices but poor profitability. This analysis method helps identify opportunities and risks in the market.

In summary, PB-ROE is a combined indicator of Price-to-Book Ratio and Return on Equity, providing more information about a company's stock pricing and profitability.

However, if the PB and ROE indicators predicted by analysts are used for screening, the test results show that returns significantly improve, with annualized returns increasing to over 20%, achieving a winning rate of 90.91% compared to the annual performance of the Wind (Wande) All-A index (note: generally used to depict overall market performance).
Therefore, his conclusion is that analysts' consensus expectations significantly enhance the stock selection performance of the PB-ROE model, improving the applicability of value investing in the Chinese market, and over the long term, it can achieve stable excess returns.

Figure 1-18 Historical returns of value investment indicator stock selection model (Source: Huabao Securities)
Finally, to summarize this section in five sentences: 1. "Bad" research reports do not account for a high proportion and can be avoided. 2. For a stock, the more analysts focus on it, the more suitable it is to guide investment through comparing research reports. 3. For individual stocks, looking at specific forecast indicators is more useful than looking at conclusions. 4. To correct the "annual report effect," one can look at in-depth reports after May each year, ignoring all performance commentary-type research reports. 5. Research reports may be more suitable for guiding relatively long-term, value-oriented investment activities.
Some friends may say, I want to find speculative stocks through research reports. I can only answer that this path is difficult. Indeed, during the surge of some speculative stocks, there are always research reports involved, but the motives and logic of these reports are difficult to discern, making them elusive; thus, they are not very operable; at the same time, the process of speculative stocks "becoming speculative" often does not create value but merely transfers wealth between different people's accounts, a game that may not be suitable for the vast majority of ordinary investors. Tang Bohu has a poem that tells you how to make money, what money to earn; although it may seem a bit pedantic, it is not without wisdom:
Expressing Ambitions
Not refining elixirs, not sitting in meditation, not for merchants, not farming.
Writing in leisure to sell the green mountains, not letting the world create sinful money.
The main content of this article is from the June 20, 2017 article "Pah! Chinese Analysts Are Not the Chinese Men's Football Team!" from "Toxic Tongue Research Reports."
The main content of the "shortcuts" comes from the October 17, 2017 article "5 Secrets to End Your Mutual Harm with Analysts" from "Toxic Tongue Research Reports."

Good News: Research Reports Are Becoming More Useful
The bad news is that time flies. The good news is that you are the pilot.
—— Sean Ellis, "Supermarket Night Shift"
The foreplay has been long enough—after this section, we will officially enter the phase of reading research reports.
I know that people want to get straight to the point. In life, we often overlook the beauty of foreplay. Foreplay is not a routine before entering the theme; it has high aesthetic and experiential value in itself. It is a bit like Peking Opera; have you seen Peking Opera live?
In fact, the stories in Peking Opera cannot compare with American blockbusters, but it gradually adjusts your state to be slow and simple, and then the limited dramatic conflict produces an extremely shocking stage effect. I think similarly: when we approach something, it is best to first appreciate the external beauty of this thing and then move from the surface to the core; if we think it lacks even external beauty, then we should quickly terminate the process of getting closer to save the cost of reading opportunities.
This is why I have been rambling for a chapter without showing you half a penny's worth of research report.
Back to the point. Since 2016, the guiding significance of research reports for investment has gradually become prominent; in simple terms, the value of research reports is increasing.
At the end of 2017, I sorted out the annual strategy research reports of that year and found that the prediction accuracy was very high. It is worth noting that these annual strategies were basically published in November 2016, which shows that research reports are becoming more useful.
In my impression, in previous years, the media and ordinary investors were keen to dig up the annual strategies at the end of the year to whip them. However, looking back at the annual strategies of 2017 at the end of 2017, you will find them to be very accurate.
Let’s give a thumbs up to the following analysts: Dai Kang, then an analyst at Huatai Securities (now at GF Securities), Xun Yugen from Haitong Securities, Zhang Huaen from Guotai Junan, Chen Yalong from Northeast Securities (now at Huatai Securities), and Tu Jun from Shanghai Securities; they all accurately anticipated the annual investment theme of "profit recovery" and "profit improvement."
Table 1-4 Summary of Accurate Analyst Views on the 2017 Annual Strategy

Qiqilu is also glad that in November 2017, "profit improvement" (in purple text in Figure 1-14) was identified as a key clue, and the process of transporting viewpoints was relatively shrewd.
Let’s give a thumbs up to Qin Peijing from CITIC Securities; he basically accurately predicted the expected return ranking of major asset classes from high to low: cyclical goods, stocks, gold, US dollars, real estate, and bonds.
Table 1-5 Qin Peijing's Major Asset Ranking Viewpoint

In November 2016, I summarized the 2017 annual strategy in four sentences: corporate profit improvement, global infrastructure construction, capital moving away from real estate, and overweighting equities to solve difficulties. Looking back now, except for the phrase "global infrastructure construction," the other sentences are accurate predictions. At that time, analysts overestimated the fiscal expansion of Trump, but the recovery of external demand in 2017 was indeed an undeniable fact.
Thus, from the annual strategy—this is the most challenging task for analysts—the accuracy is so high, which shows that research reports are becoming more useful.
After the "mad cow" and stock market crash in 2015, our market is undergoing profound changes, and these changes are making research reports increasingly useful. Senior reporter Li Dongliang from "Securities China" has a precise analysis of this:
"Everyone is inevitably swept into the torrent of the times, and analysts are no exception.
"In the past year, three major events have occurred in brokerage research: the star research institute's director Gao Li took office as the chairman of Fangzheng Securities, internet celebrity macro analyst Ren Zeping took a position at Evergrande with an annual salary of 15 million, and New Wealth platinum analyst Liu Yuanrui is about to become the president of Changjiang Securities.
"Analysts were once labeled as stock-picking 'fortune tellers'; why have they suddenly appeared in succession as chairmen or presidents of securities companies, or been poached by non-financial enterprises at unexpectedly high salaries?
"Let’s start with the capital market! This year (2017, author’s note), the A-share market created history; the Shanghai Stock Exchange 50 Index, representing blue-chip stocks, has risen by 25%, while the CSI 1000 Index, representing all market stocks, has fallen by 18%. Companies like Ping An Insurance and Kweichow Moutai have transaction amounts reaching tens of billions, while over 1,000 small-cap stocks have daily transaction volumes below 20 million.
"This means that this year, institutions not only made a fortune but also enjoyed superior liquidity. Meanwhile, retail investors who are keen on small and poor stocks have suffered tremendously this year and often encounter liquidity crises. There are many reasons behind this:
"First, China is determined to promote opening up, and it is reasonable for the capital market's valuation system to align with mature markets abroad.
"Second, to stabilize the index, and more importantly, before the A-shares are officially included in the MSCI Emerging Markets Index next year, blue-chip stocks in A-shares need reasonable pricing, and related funds have significantly increased their buying of blue-chip stocks over the past two years.
"Third, after a stock market crash triggered by a liquidity crisis, institutional funds have begun to pay unprecedented attention to liquidity, and buying blue-chip stocks meets this demand.
"Fourth, China's economy has shifted from high-speed growth to medium-high-speed growth, coupled with the continuous promotion of strong capacity reduction policies, the days of the real economy flourishing are over, and businesses in various industries are beginning to concentrate on leading companies, enhancing the profitability of blue-chip stocks.
"The direct effect is that the Chinese capital market has never been so close to the institutional era.

The capital market is cruelly clearing out retail investors who like speculation from the market, welcoming the arrival of the institutional era with the two rewards of profitability and liquidity."#

The bolded sentence above is what I want to say.
Speculating in stocks has never been easy. If in the previous decade we had to face stock manipulators and wolves (such as the limit-up death squad), in the next decade we will have to face institutions. Therefore, we must adopt an institutional mindset.
What is an institutional mindset? Institutions mostly prefer value investing, and various subjective and objective reasons determine this. Therefore, compared to stock manipulators and wolves, institutions are much gentler—they earn money primarily from the growth of corporate value rather than directly taking money from retail investors.
In this sense, if your thinking aligns more closely with that of institutions, you are likely to become a companion of institutions; if your thinking diverges from that of institutions, you may become their opponent.
In this institutional era, how should you choose? If you do not have the strength to harvest institutions, then becoming a companion of institutions is undoubtedly the optimal choice.
Research reports are one of the main sources of institutional investment information, so my conclusion is also very clear:

In the institutional era, ordinary investors must become companions of institutions and learn to read research reports like institutions.#

Now, let’s start reading research reports together!
The content here comes from the December 5, 2017 article "The Great Trend of the World, Division Must Unite, Union Must Divide, Division Must Unite Again, and Union Must Divide Again..." from "Toxic Tongue Research Reports."
With the author's permission, parts of the article "Three Major Events in Brokerage Research" from "Securities China" on December 27, 2017, have been quoted.

The First Glance at Research Reports#

Let’s start with strategy reports.
Life is an unending game of strategy, which means achieving desired results through choosing the right strategies.
—— John von Neumann
In the first chapter, we mentioned that macro research is the homeroom teacher, strategy research is the class monitor, industry research is the subject representatives, and company research is the students.
Where should we start to understand a class? Originally, I wanted to first talk to the homeroom teacher, but then I thought the homeroom teacher might not be the best choice; you understand the reason; it might be better to first talk to the class monitor—you agree, right? The class monitor has both a political side and a down-to-earth side.
Let’s start with an observation of an annual strategy. In November 2016, I made the following observations on the annual strategies released by brokerages for 2017.

Figure 2-1 Hypothetical Shanghai Composite Index running chart based on the 2017 annual strategies

The above image is a simulated Shanghai Composite Index trend chart for 2017 based on the overall impressions of nine annual strategies, seeking the greatest common divisor. I deliberately removed the coordinates, mainly to observe the shape. Of course, it also contains some of my personal views.
In the background of the gray line, each difference is 100 points; if calculated this way, the starting point of the Shanghai Composite Index in 2017 was around 3100 points, and it closed at around 3300 points, which should say that this chart's point estimate is basically accurate.
This chart looks like the head of an elephant, right?
Of course, the actual running shape of the Shanghai Composite Index in 2017 is as follows:

Figure 2-2 Actual running candlestick chart of the Shanghai Composite Index in 2017
We can see that the overall shape is not much different, but the elephant's trunk is longer, and the annual high point appeared in the fourth quarter instead of the second quarter.
Overall, if viewed from the perspective of annual investment, referring to the 2017 strategy reports would not pose too many problems: among the nine annual strategies, almost all were bullish on 2017, with only significant divergence in the second quarter.
Among the nine reports, eight clearly expressed optimism or raised the valuation center for A-shares in 2017. These eight bullish reports came from Wang Zhen of CICC, Qin Peijing of CITIC Securities, Wang Sheng of Shenwan Hongyuan, Zhang Huaen of Guotai Junan, Zhang Xiaochun of Guolian Securities, Dai Kang of Huatai Securities, Xun Yugen of Haitong Securities, and Chen Yalong of Northeast Securities.
Only one report—though it cannot be said to be bearish—should be considered conditionally bullish, focusing on whether the midstream industry continues to replenish inventory from the upstream industry, the so-called "midstream determines the outcome." I personally prefer this kind of report that provides conditions over one that simply draws conclusions; the author is Tu Jun from Shanghai Securities.
Four annual reports predicted the main range of the Shanghai Composite Index, with two reports estimating the upper limit at 3800 points, from Wang Zhen of CICC and Chen Yalong of Northeast Securities; the other two estimated it at 3500 points, from Zhang Huaen of Guotai Junan and Tu Jun of Shanghai Securities. Regarding the lower limit, three individuals—Chen, Zhang, and Tu—estimated it at 2800 points, while Wang Zhen estimated it at 2900 points.
Regarding quarterly highs, three reports made predictions, with some sharp divergences: Wang Zhen predicted a second-quarter high of 3600 points, while Qin Peijing of CITIC Securities also believed the second quarter would be better; however, Zhang Huaen thought the second quarter would face the most pressure, with the fourth quarter (after the 19th National Congress) being the best time to attack.
Regarding style trends, two reports made clear predictions with generally consistent conclusions: Wang Sheng of Shenwan Hongyuan believed that value would prevail in the first half, while Zhang Xiaochun of Guolian Securities believed that cyclicals would come first, followed by growth.
Qiqilu wants to remind everyone that for annual strategies, the conclusions can be looked at, as everyone is willing to mentally outline the market's tone in advance; as for the specific shape—whether it is an elephant's head or an old duck's head, as long as you guess, you may be wrong—so we say that comparing predictions is more important.
More important than conclusions is the logic, that is, the analysts tell you why they are bullish. In other words, you need to familiarize yourself with the basic clues of strategy analysts' thinking because analysts as a whole have considerable influence in the market, and they are constantly roadshowing; thus, what they think and say will eventually become what the market thinks and says.
It may not necessarily be accurate, but from the perspective of behavioral finance, this is similar to the five-day moving average; the more people believe it, the more significance it generates.
Thus, the following table uses the same viewpoint represented in the same color; you can see which color appears more frequently and is concentrated, representing which viewpoints occupy a larger proportion in the analysts' thinking.
Table 2-1 Tagged 2017 Annual Strategies

Let me summarize:

1. The purple "profit improvement" ("profit recovery," "financial indicator improvement") appeared five times in nine reports, accounting for 55.56%. This means that over half of the strategy analysts believe that A-share profits are expected to improve in 2017, thereby boosting risk appetite and creating opportunities for overweighting stocks. This is a micro fundamental factor.
2. The yellow "expansive fiscal policy" ("fiscal expansion," "active fiscal policy") appeared four times in nine reports, accounting for 44.44%. This indicates that nearly half of the strategy analysts are optimistic about the global expansionary fiscal policy backdrop, which will certainly boost overall demand, raise nominal growth rates, and directly benefit infrastructure. This is a macro fundamental factor.
3. The red "asset allocation" appeared five times in nine reports, accounting for 55.56%. This indicates that over half of the strategy analysts believe that institutions will overweight A-shares, thus improving A-share valuations. This is a liquidity factor.
4. The green "real estate" appeared three times in nine reports, accounting for 33.33%. This indicates that one-third of strategy analysts believe that funds from the real estate market are expected to shift to the stock market, which is related to point 3 and is also a liquidity factor.
   At that time, I summarized these viewpoints into four sentences: corporate profit improvement, global infrastructure construction, capital moving away from real estate, and overweighting equities to solve difficulties. This is the logic of strategy analysts regarding 2017.
   Looking back, the logic of the annual strategy was very correct: the biggest logic for A-share investment in 2017 was actually "profit improvement." We saw that many solid-performing stocks (the "beautiful 50" stocks most sought after in the market in 2017) performed brilliantly in 2017, while some long-ignored stocks (the most representative being cyclical stocks) also returned to prominence due to profit improvement. The actual operation of liquidity also confirmed the analysts' logic, with value investing becoming the dominant force, leading to excellent performance for stocks that institutional investors overweighted, and indeed, the overall market's risk appetite increased to some extent.
   Except for the prediction of "global infrastructure construction," which was slightly inaccurate (mainly because the pace of the U.S. fiscal expansion was less than expected), the other predictions were basically accurate. Although there was no "big infrastructure construction" globally, total global demand did indeed see a significant increase, and in 2017, Chinese enterprises' exports were unexpectedly good.
   Finally, I will summarize from a methodological perspective, which will be elaborated in detail in the following sections.
5. Start learning to read research reports from strategy reports.
6. Comparative research. Do not just look at one research report, but look at multiple reports on the same topic, such as the nine annual strategy reports mentioned above.
7. Seek commonalities. This is the tagging statistics I did, which can also be referred to as consensus expectations. I do not particularly advocate using the least common multiple method but rather the greatest common divisor method. In other words, if these smart minds all agree on a mistake, you have no way to avoid it. Please note that I am not saying to follow the majority; rather, I am saying to believe in high-probability events, or to trust the consensus opinions among the most outstanding minds—in fact, in November 2016, these analysts' consensus opinions were not even the majority opinion.
8. Reading volume. The above small study has a total reading volume of about 50,000 to 60,000 words. There is no way around it; I read every word to form a feeling; this effort cannot be spared, and it is not actually hard. The total number of words you read in junk articles on WeChat every day is definitely not less than 50,000 to 60,000 words.
9. Dehydration. This means having a certain summarization ability. Annual strategies are relatively lengthy, and you can take a moment to jot down notes (I also take notes during the reading process) and try to condense the story told by each research report (which is the main logic and central idea) into a more concise form. If you cannot condense an annual strategy to around 200 words, either the analyst did not write well, or your reading comprehension ability is relatively poor.
   Well, I will use a chart to illustrate how I dehydrate the annual strategies:

Table 2-2 Content after Dehydration of the 2017 Annual Strategies

The above is our first lesson in reading research reports, discussing five small methods for reading strategy reports. Next, we will delve deeper into how to read strategy reports.
The content here comes from the November 29, 2016 article "Nine Major Brokerages Paint the Picture for Next Year’s Stock Market: Bearish? Bullish? It’s an Elephant!" from "Toxic Tongue Research Reports," with some modifications.

This story tells us…
Narration moves the story from point A to point B until it concludes at point Z.
—— Stephen King, "On Writing"
If the first glance at research reports is on strategy reports, then the first glance at strategy reports should indeed be on annual strategies. Annual strategies may not reveal a short-term turning point for you, so in terms of practicality, they may even be less useful than a weekly strategy report. However, because annual strategies passively avoid much noise, they become the most serious reflections of a brokerage's strategy team's thinking outcomes.
Annual strategies are essentially an annual story; this story is usually complete, with a beginning, a development, and a conclusion. It will tell us how to navigate through the year.
When reading the annual story, it is still important to emphasize "not being greedy"; you hope that the annual strategy is entirely correct, which is greed; you hope it will be correct immediately, which is also greed. In the process of reading annual strategies, many things that are later proven wrong may be more valuable because, in long-term investments, thought processes may be more important than short-term market fluctuations; at the same time, no strategy team can accurately predict every short-term fluctuation, so you do not need to focus your energy on finding such a godly team.
At the beginning of 2017, I conducted a comprehensive overview of the annual strategies in the "Toxic Tongue Research Reports" column, and looking back a year later, as a report transporter, as long as one pays a little attention, one can accurately predict the main storyline of stock investment in 2017—of course, "accuracy" belongs to the major institutional analysts.
To clarify, this annual strategy overview also includes some macro reports, but most of the ones I selected are from the strategy sections of macro reports, so let’s consider them as strategy reports. This also illustrates some intersections between macro reports and strategy reports, which we will discuss later.
Column 2: Eight Chief Analysts, Seven Favorable Stocks! How Should Assets Be Allocated in 2017?
Dear toxic friends, may you have a prosperous start to your work! Let me see your rolled-up sleeves!
"The sky won't drop pies," how should assets be arranged in 2017?
"On the road to a moderately prosperous society, no one can be left behind," how should assets be allocated in 2017?
Qiqilu systematically sorted out the asset allocation reports of the ten chief analysts who ranked in the macro and strategy categories in the New Wealth selection in 2016, among which eight chief analysts expressed their views on asset allocation for 2017: Jiang Chao from Haitong Securities, Wang Han from Industrial Securities, Ren Zeping from Fangzheng Securities, Li Huiyong from Shenwan Hongyuan, Xie Yaxuan from CICC, Xun Yugen from Haitong Securities, Xu Biao from Anxin Securities, and Wang Sheng from Shenwan Hongyuan.
Notably, among the eight chief analysts, seven explicitly expressed optimism about the performance of stock assets in 2017.
Most Optimistic About Stocks, Most Pessimistic About Real Estate
Among the eight chief analysts, seven clearly stated that they are optimistic about the performance of stock assets in 2017 (see Table 2-3), with three of them adding conditions. Jiang Chao from Haitong Securities (last year's New Wealth macro champion) believes that high-dividend stocks present opportunities from a medium to long-term perspective; Li Huiyong from Shenwan Hongyuan (New Wealth macro fourth place) believes that infrastructure commodity stocks have opportunities; Xu Biao from Anxin Securities (New Wealth strategy runner-up) believes that stock market opportunities will emerge later in 2017, and the expectation of ROE (return on equity) bottoming out may bring about a wave of ROE bull market.
Among the seven analysts who are optimistic about stock asset performance, Ren Zeping from Fangzheng Securities (New Wealth macro third place), Li Huiyong from Shenwan Hongyuan, Xun Yugen from Haitong Securities (New Wealth strategy champion), and Wang Sheng from Shenwan Hongyuan are the four chief analysts who prioritize stocks as the first choice in asset allocation for 2017.
In contrast, real estate assets are relatively the most pessimistic; among the seven analysts who clearly expressed views on underweighting assets, six explicitly expressed bearish views on real estate assets, with four listing real estate as the least favored asset category. Ren Zeping's view has undergone some adjustments compared to previous periods, as he believes that the investment and speculative attributes of real estate have been denied by policies, and he expects the adjustment to continue until the end of 2017.
The Most Optimistic and Most Pessimistic Predictions
Among the eight chief analysts, the most optimistic is Li Huiyong, who, in addition to being most optimistic about infrastructure commodity stocks, is also optimistic about bonds, gold, and even real estate. His specific suggestion is to increase bond allocation after the second quarter; from the perspective of diversifying risks and betting on value, he is optimistic about gold but suggests buying puts instead of calls; additionally, he also considers real estate in first-tier cities as an asset he is optimistic about, with the general ranking of asset categories being stocks > bonds > gold > first-tier city real estate. Li Huiyong believes that a significant assumption is that China and the U.S. will guide global recovery; in this case, asset allocation will shift towards more aggressive assets and equity assets.
The most pessimistic analyst among the eight is Wang Han from Industrial Securities (New Wealth macro runner-up), who, in addition to being optimistic about the performance of interest rate bonds in the medium to long term, is bearish on all other major asset classes, including credit bonds, stocks, and real estate. His reasoning is that the monetary policy in 2017 is neutral to tight, limiting the imagination for asset performance; in addition, residents' risk appetite is declining, and other risk assets will not perform well except for low-risk, stable-return interest rate bonds.
Although they are both optimistic about the stock market, the mindset of the chief analysts is vastly different. The more optimistic ones are Xun Yugen and Xie Yaxuan, who both believe that 2017 will see improvements in corporate profitability levels, while Xie Yaxuan is also optimistic that the economic fundamentals will improve in 2017, which will benefit the stock market.
Jiang Chao believes that with the start of monetary tightening, stagflation is entering its mid-to-late stages, and cash will gradually replace commodities as the preferred allocation. Once economic inflation falls again, a recession will follow, and both the bond and stock markets will see new opportunities.
Major Asset Scoring Rankings
To more intuitively reflect the ranking of major asset allocations in the minds of the eight chief analysts, we used a scoring system where bullish opinions add points (4 points for the highest, decreasing in value) and bearish opinions deduct points (−3 points for the lowest, increasing in value), and we calculated the total scores for each major asset class based on the eight chief analysts' opinions, as detailed below:
Table 2-3 Total Asset Scores of Eight Chief Analysts

Thus, based on the aggregated opinions of the eight chief analysts, the order of major asset allocations in 2017 should be: stocks > bonds/cash > commodities > gold. Real estate should be underweighted.
Table 2-4 Asset Allocation Views of Eight Chief Analysts in 2017

After reading the above column, I wonder if you have gained some insights. I have summarized some of my thoughts:

1. First, we must be clear about what we want in the process of reading strategy reports. The newly crowned New Wealth macro champion Guo Lei said that he believes the two main values of macro research are allocation and timing. I completely agree with this judgment; strategy research is the same. Therefore, when we look at macro and strategy reports, especially annual reports, we must keep this in mind: focus on solving allocation and timing issues, that is, how you should allocate investment proportions among stocks, bonds, real estate, gold, and commodities, and when to allocate and reallocate.
   For this reason, the issues addressed in the above column 2 article are relatively concentrated; in fact, the content of the eight annual strategies and macro reports is quite extensive, which may occasionally lead you to get lost in details. However, if we are clear about what we want, the main structure of the reports will become clear.
2. Regarding comparative research, extensive reading, and dehydration, all three strategies have been applied; I compared the annual views of eight leading strategy/macroeconomic analysts; the reading volume was around 50,000 words, which took just one morning; and in terms of dehydration, I basically summarized the central ideas directly and concisely, making them clear at a glance. These three strategies will not be repeated.
3. I also tried using a new analysis method, which is to assign scores to each asset class based on analysts' opinions (see Table 2-3, ranging from +4 to -3 points), with the scores depending on the analysts' rankings of bullish and bearish assets. In fact, this method is also a manifestation of the "seeking consensus" mentioned earlier; my idea at that time was: for ordinary investors, as long as they find two asset classes—those that mainstream opinions are concentrated on being bullish and those that mainstream opinions are concentrated on being bearish—overweight the former and avoid the latter.
   From the results, the effect was quite good. The stocks with a score of 25 points were indeed among the best-performing assets in 2017 (of course, they were also structurally good), while the real estate with a score of -13 points was indeed not suitable for investment in 2017. Of course, this result would also help you avoid the bonds and cash with a score of 5 points, as bonds were indeed a pit for investment in 2017; it would also lead you to miss the commodities with a score of 3 points, which performed very well in 2017, especially in the first half. In contrast, the avoided and missed opportunities may not be important; as long as you bought stocks in 2017 and did not touch real estate, the returns would still be decent.
4. Of course, the issue mentioned in point 3 has significant problems, namely that scores can only reflect the total amount, not the structure. Just like stocks, although they scored as high as 25 points, if you bought small-cap stocks in 2017, your results might still be very disappointing. How to address this issue?
   This requires us to discern the logic of analysts (of course, this also belongs to hindsight). Please look at the far-right column in Table 2-4; among the analysts who are optimistic about stocks, Wang Zhen, Ren Zeping, and Xun Yugen all discussed valuation logic (opportunities arising from