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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 during the 1980s and 1990s when I received my basic education—every question had a standard answer, and it was generally not too difficult to score high by answering according to the teachings of past sages or imagining how they would respond. This was even more true in traditional China, where the process of education primarily involved memorizing and reciting classics (which generally came from "sages") and the classic interpretations of those classics (which typically came from "wise men"). Both the classics and their interpretations represented varying degrees of privilege. 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 grave offense.

Such traditional societal and cultural psychology often leads to two misconceptions: first, an excessive diminishment of one's cognitive abilities; whenever people hear terms like "research report," "model," or "strategy," many may not be frightened on the spot but will feel a sense of distance, a so-called "respectful avoidance." Second, there is an excessive deification of the cognitive abilities of "sages"; we always expect an ultimate solution to be revealed by a prophet who understands the secrets of how things work, and we follow their lead, step by step, ultimately reaching the shores of happiness.

In fact, from exposure to familiarity, 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 "research reports," doing whatever the goddess says, forgetting that you are an equal and independent entity.

Now is the era of "people"; we must get used to looking at each other as equals; any cooperative relationship implies utilizing the strengths of the partner while also accepting their weaknesses.

Let me give an example. In the fable "Waiting for the Rabbit," the farmer's "model" is: the rabbit will crash into the stump (this actually happened); the conclusion of the "research report" is: waiting by the stump means there will be meat to eat. However, the "model" of the fable's author, Han Feizi, is: the probability of the rabbit 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 made in these two research reports are easy to determine. In actual investment processes, the situation can be a bit more complex, but it is not overly complicated; 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 essentially an investment fable.

Now, please set aside your mental burdens; if you feel that research reports are not so difficult to approach, we can continue discussing what research reports really are.

What Are Research Reports?#

Definitions are always a bit annoying, but to enter the world of research reports, we still need to spend three minutes to briefly discuss.

Unless otherwise specified, the "research reports" referred to in this book are research reports published by securities companies to provide investment consulting services. We usually call them "sell-side research reports," which is in relation to investors (the buy-side). Simply put, these reports indicate which industries and companies are favored and what strategies are available, serving as references for investors' investment activities.

There is a paradox here. You must be wondering: if an analyst is optimistic about a certain stock, why not just buy it themselves instead of kindly informing investors?

The answer to this question could fill 10,000 words, so let’s illustrate it with a few analogies. First, why did Zhuge Liang not lead his own army but instead follow 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 information so quickly and accurately, yet they do not directly trade stocks? The first example emphasizes resources. The second emphasizes division of labor. The third emphasizes specialization or comparative advantage. I can assure you that the above explanations are extremely imprecise, but fortunately, we do not need to focus on such uninteresting questions; you just need to understand the analyst as a "strategist," "enforcer," or "reporter." Few can dominate an entire industry; the investment consulting business has already been sufficient to support six to seven thousand people, allowing this industry to exist relatively independently.

Of course, there are indeed many analysts who have become fund managers and achieved success; there are also many who have failed. As the research giant 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 akin to Zhuge Liang being less capable of crying than 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 recommendations for specific analysts; there will be a dedicated chapter discussing which analysts to recommend.

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 speaking, just as Chinese is the starting point for all learning, macroeconomic research is the source of other research. This is because people usually view the stock market and bond market as reflections of the macroeconomic fundamentals. The homeroom teacher cares about students' grades (the operation of the macro economy), 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 cares about the class atmosphere, which leads to research reports on liquidity (money supply, social financing, interest rates, exchange rates); they care about important school policies, which leads to relevant macro thematic reports (e.g., supply-side reform, Xiong'an New Area, military reform, state-owned enterprise reform, etc.); they 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 community can usually explain logic in simple terms, making it suitable for readers with a shaky foundation in economics (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 earlier, the homeroom teacher teaches Chinese, so the position of bond research is quite special. Friends who trade stocks may not feel it, so they did not make it the class leader, but it is actually very close to the homeroom teacher—many macro analysts are actually bond analysts, taking on both roles. The uniqueness of the bond market has two points: first, it is an institutional market; second, it is a capital market. In other words, the bond market reflects the basic liquidity situation of the financial market (where large institutions play with big money). Of course, I dare to say that for ordinary stock traders, not caring about bond research is almost okay, 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," but to put it simply: it 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's assistant—there is considerable 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 serves as a carrier for macro "implementation" and a pathway for industry research to "enter the room." From another perspective, strategy is also squeezed by macro and industry; it is caught in a vice: if macro is bearish, strategy theoretically should not be bullish (but in practice, there are instances where macro and strategy diverge within the same institution), and if industry research is optimistic about a certain sector, and strategy ignores it, then if that sector surges, strategy will 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 recent years, strategy research seems to be experiencing 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 "golden stock" combinations, industry recommendations, and thematic recommendations are mostly gathered in the strategy section. When reading research reports, starting with macro, then strategy, and finally industry, or having strategy and macro mutually corroborate before delving into industry, is the ideal entry path.

To add, strategy may also involve some special topics, which could be concepts, industries, new stocks, quantitative analysis, or even sentiment (like the "sell in May" curse), etc., all of which can become strategies. Therefore, those who dominate this field are often seasoned veterans; the "stock comments" you are most familiar with mostly come from here.

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

Industry Research: The 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 research reports, I have divided 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 positions in the industry chain have good companies; what characteristics each company in a certain industry position 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. Usually, ratings indicate how much more a stock can rise relative to the market (like the CSI 300 index or other benchmark indices) within a certain period (like six months). Of course, we will discuss how to interpret 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 merely speaking in terms of quantity; company research reports indeed constitute the largest portion of brokerage research reports. Company research has the following characteristics:

1. Grounded. Stock trading is about buying companies; regardless of macro or sector, if I believe in this company, I will 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 listen to recommendations for a certain stock and then look for a few reports to read as a buying rationale. It can be said that company research reports are the closest to ordinary investors, especially the appealing "stories" within them.

2. Straightforward. Company research reports contain a large number of ratings, and even further: target prices, along with many performance forecasts (future earnings per share, net profit, return on equity for the next 1 to N years, etc.), which are very direct and blunt.

3. Wide Coverage, Quick Response. Statistics show that from 2001 to 2014, 75% of listed companies in China had analysts tracking them, with over 50% of companies being 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 will definitely be analyzed immediately.

4. Many Ineffective Products. From the perspective of research report users, this is reasonable; from the analysts' perspective, it may be a bit unfair. It is like reading political news in newspapers; many pages are similar, so there is no need to subscribe to so many political newspapers; however, each newspaper's editors and reporters are putting in effort. My suggestion is to skip most commentary-type company research reports (almost all performance commentaries and most event commentaries) and focus on in-depth research.

Moreover, in-depth company research must be viewed in conjunction with industry research for mutual corroboration. From the perspective of actual investment, in a public information environment, industry-wide opportunities are often easier to grasp than opportunities in a single company, with a relatively higher win rate; at the same time, recommendations from the same institution for industries and companies 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:
I: Can you help me see if this stock is good?
Teacher: How do you look at it?
I: You have 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?
I: …

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 large 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 texts, 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 exchange words, your real money is at stake; isn’t that too childish?

Therefore, 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.

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 does have 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 will truly learn Go; only if you spend a lot of time supervising him and accompanying him through extensive practice can he 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 lead us into the realm of 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 may be detours because you will miss the opportunity to experience the vastness of the world.

Free Channels
Knowing that everyone likes free, let’s first discuss 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 Reports" channel

First, financial websites. As shown in the picture above, this is the homepage of Sina Finance's "Research Reports" channel. I won’t copy the URL because the functionality of this database is relatively basic. Other major financial websites generally also have research report sections, but I won’t introduce them all.

Why not?
As soon as you randomly click on a research report, you will find that the content provided by financial websites is basically limited to the summary of the research report. This is essentially a content summary at the beginning of each report, usually spanning 1-2 pages, showcasing the main conclusions of the report. Although the conclusions of the reports are indeed the essence, from an investment perspective, merely looking at the conclusions provides little guidance for investment activities, even if the conclusions are correct.

We need to know not only what is true but also why it is true to improve accuracy, right? However, due to copyright and regulatory requirements, most public financial websites can only help you up to this point.

No worries, there are still other free channels.

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

Currently, the behavior of disseminating research report content through WeChat public accounts has not yet been precisely defined by regulators; 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 regarded as 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—only the determination of long-term candidates is a significant issue. 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 quite tiring, and I haven’t looked through all of them. This concludes our discussion of free research report channels. 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 (the byproduct of being free).

Paid Channels
First, I want to say that the content of paid channels' research reports is all quite good. I have used several paid research report platforms or paid terminals, 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 charges less than 1,000 yuan a year, which is about the cost of a meal for three to five friends gathering in Shanghai or Beijing; what more do you want?

Another surprise is that I originally thought Wind would aggregate a comprehensive range of research reports and research institutions, but it actually does not cover as much as I imagined, and Wind is notoriously expensive, so it is difficult for ordinary investors to choose Wind.

Chaoyang Yongxu has a good database, and 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 functionalities are all quite 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 to us in reading research reports.

First, the classification function of research reports. In Table 1-2, you can see the primary classification list of a platform. This content is not particularly surprising, as 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 a lot of results, and the scope is very imprecise. Therefore, we need secondary classifications, as shown in Table 1-3.

Table 1-3 Secondary Classification of Research Report Platforms

Still under the above needs, 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, you can currently determine the longitude of "Industry Research + Industry Strategy Depth," but you are still missing a latitude; you just need to add one more dimension. By adding "Electronics Industry" in the "Industry" option, a complete coordinate system is formed.

In the above figure, you can see that the example platform uses conditions such as 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., continuously expanding or narrowing your range until you filter out the reports that best meet your needs.

Just from the perspective of classification, you can see the functionality of a professional research report platform. Readers often wonder why Qiqilu can find so many 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 your usage, your needs often emerge unexpectedly. For example, you may initially just want to look at the annual investment strategy for the electronics industry, but during the process, you suddenly find that the Apple supply chain is repeatedly mentioned, and your need shifts to looking at the investment strategy for the Apple supply chain. When you search for the keyword "Apple supply chain," you indeed find quite a few results, but you only want to see the in-depth industry strategies among them; at this point, 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 wild and strong desire for knowledge.

Third, the panorama of individual stocks and analysts. I think the panorama of these two aspects on the example platform is the most distinctive. Let’s discuss them separately:

In the above figure, taking Kweichow Moutai as an example, you can clearly see 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 look at the analyst panorama:

Figure 1-11 Panorama example of Guotai Junan Securities analyst Ju Guoxian
In the above figure, taking Guotai Junan's non-ferrous analyst Ju Guoxian as an example, the most distinctive setting 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 capabilities). At the same time, the relevant page also lists the analyst's research reports and the stocks they cover, as well as the situation of other analysts from the same institution and other analysts from the same industry.

Fourth, popular research reports.#

From a game-theoretic perspective, investing is, as economist Keynes said, a process of "picking the beauty in others' eyes," or in other words, only the beauty that you think is beautiful will not win the beauty contest; only the beauty that everyone thinks is beautiful can win the contest. 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 it indicates that the report is recognized.

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 influence the market than those that no one is reading.

Figure 1-12 Example platform's "Popular" research report section from December 15, 2017

Well, 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 currently 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 shortcuts.

Currently, "Zhiqiu" still cannot provide research report services (including paid services) to ordinary investors; for now, it only has a version for institutional clients. In the future, when the timing is right, it may launch a 2C product, but not in its current 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 clear, and I would rather 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 such situations, I even think that pretending to believe and deceiving oneself through pretending to believe, if there is any gain, can still be considered good; the most troublesome is that blind and heartfelt belief, which brings neither material returns nor spiritual compensation.

When we read research reports, we must avoid such "greed" issues: "greed" leads to super-accurate conclusions, "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 erroneous 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 an abundance of 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 may cause you to suffer significant losses—so it must be avoided.

Column 1: There Aren't Many Analysts Who Lead You Astray

Figure 1-13 A joke about "black" analysts circulating on WeChat

A long-standing misunderstanding, as the core part of the joke says: clients can't 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 like this:

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 their 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

80% of Analysts Can Beat the Benchmark
According to this data tool, Qiqilu conducted some statistics, and the conclusion is that within a certain time frame, about 80% of analysts' portfolio performances 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 market's overall situation more accurately.

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

The above statistical data shows that 40.12% of analysts can bring absolute returns through the portfolios they recommend.

Considering the extremely obvious differentiation in the market in 2017, the CSI 1000 index can better represent the market as a whole (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 could be an issue, but I think that general users of research reports 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 over a year.

But it doesn’t matter; statistics are generally not difficult.

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 astray.

This still basically conforms to the 80/20 rule, or in other words—overall, the securities analysis industry does not have a higher overall standard than other social industries, nor does it have a lower one. Therefore, the conclusion derived is that as a whole, securities analysts do not have a better overall standard than other social industries, nor do they have a worse one.

If it is said that the "chief analyst of New Wealth with an annual salary of tens of millions" is involved, due to the standards and data screening issues, I have not produced results, but I can almost guarantee: given the direct performance assessment (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 its change rate 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 focusing on it, the lower the credibility of the 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 generally better to adopt an attitude of neglect. When using research reports, it is best to look at reports for stocks with many analysts covering them and closely track them. If you look at reports for obscure companies, you are likely to share the same mindset as the analysts writing those obscure reports—merely to attract attention, and the result is likely to be mutual understanding.

Therefore, when selecting stocks based on research reports, it is mainly suitable for those stocks with a larger number of analysts focusing on them, and based on this, conduct "cross-sectional" comparative analysis of analysts' viewpoints. If a stock has fewer than three analysts focusing on it, it is generally not advisable to use research reports to assist in decision-making.

The more analysts focusing on a stock, the more there is what is called "consensus expectations." 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 bullishness under consensus expectations may have "lower odds," just like in a match between the Brazilian men's football team and the Chinese men's football team, where the majority will bet on Brazil winning; although the winning odds are high, the money each person wins will be small.

Second, pay attention to "specific indicators."#

A misconception is that an upgrade in research report recommendations/ratings 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 boost their confidence or as a reason for buying.

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; and 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 in the selection of stocks in the ChiNext."

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 are one updated and one not updated. Of course, there are subjective issues.

The subjective issue mainly involves a tacit rule in the research report field: during the intensive disclosure period of annual reports and quarterly reports, a large number of performance reports are disclosed, which inevitably leads to a large number of performance commentary-type research reports, and these reports must give listed companies recommended ratings (otherwise, the listed companies may blacklist the analysts), and many research institutions require analysts to provide target prices (which can only be given casually), so the research reports during this period may 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%, because the indicators in financial reports have lagging characteristics and do not fully consider the current or future situation of the company.

PB-ROE is a combined indicator for measuring company value. It combines Price-to-Book Ratio (PB) and Return on Equity (ROE) to help investors more comprehensively assess whether a company is worth investing in. Specifically, the PB-ROE concept focuses on the net asset return obtained based on 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 evaluate how the market prices a stock relative to the company's book value; typically, a lower price-to-book ratio indicates that a stock may be undervalued, while a higher price-to-book ratio suggests that a 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 typically 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 on equity generated by the company's shareholder 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 suggest 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 targets that value investors may favor.
• Low ROE and high PB: Typically indicates that the company's market value may be overvalued, or the company has weak profitability, which may not be an ideal investment target.

5. Practical Application#

When analyzing stocks, investors can use PB-ROE to identify companies with low prices but high profitability, or high prices but poor profitability. This analytical 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 an annualized return rate increasing to over 20%, achieving a victory rate of 90.91% compared to the annual performance of the Wind (Wande) All-A index (the author notes: 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 the value investment indicator stock selection model (Source: Huabao Securities)

Finally, to summarize this section in five sentences: 1. The proportion of "bad" research reports is not high and can be avoided. 2. For a stock, the more analysts focusing 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," it is advisable to 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 explosive rise 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; this kind of game 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 is somewhat pedantic, it is not without wisdom:
Expressing Ambition
Not refining elixirs, not sitting in meditation, not for merchants, not farming.
Leisurely writing 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 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 Research Reports."

Good news: Research reports are becoming increasingly 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. It is a bit like Peking Opera; have you seen Peking Opera live?
In fact, the stories of 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 delve deeper; if we believe it has no external beauty, then we should quickly halt the process of approaching it to save the cost of reading opportunities.

This is why I have rambled on for a chapter without showing you half a penny's worth of research reports.
To get back on track, since 2016, the guiding significance of research reports for investment has gradually become prominent; simply put, the value of research reports is increasing.

At the end of 2017, I sorted out the annual strategy research reports for that year and found that the accuracy of predictions was very high. It is worth noting that these annual strategies were basically released in November 2016, which shows that research reports are becoming increasingly 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 very accurate.

I want to 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 themes of "profit recovery" and "profit improvement."

Table 1-4 Summary of Accurate Analyst Views on 2017 Annual Strategies

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 astute.

I want to give a thumbs up to Qin Peijing from CITIC Securities, who accurately anticipated the ranking of expected returns for 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 Viewpoints

In November 2016, I summarized the annual strategies for 2017 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 accurately predicted the situation. At that time, analysts overestimated the fiscal expansion of Trump, but the recovery of external demand in 2017 was indeed an undeniable fact.

Therefore, looking at the annual strategies—the most challenging task for analysts—the accuracy is quite high, indicating that research reports are becoming increasingly useful.

After the "mad cow" and stock market crash of 2015, our market is undergoing profound changes, and these changes are making research reports increasingly useful. Senior reporter Li Dongliang from "Securities China" provides a precise analysis of this:

"Everyone is inevitably swept up in the tide of the times, and analysts are no exception.

"In the past year, three major events have occurred in brokerage research: the star research institute director Gao Li took over as chairman of Fangzheng Securities, the internet celebrity macro analyst Ren Zeping joined Evergrande with an annual salary of 15 million, and New Wealth's platinum analyst Liu Yuanrui is about to become president of Changjiang Securities.

"Analysts were once labeled as stock-picking 'fortune tellers'; why have they suddenly appeared 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, with the Shanghai Stock Exchange 50 Index, representing blue-chip stocks, rising by 25%, while the CSI 1000 Index, representing all market stocks, fell by 18%. Companies like Ping An Insurance and Kweichow Moutai had transaction amounts reaching tens of billions, while over 1,000 small-cap stocks had daily transaction volumes below 20 million.

"This means that this year, institutions not only made a fortune but also enjoyed superior liquidity. In contrast, retail investors who were keen on small and poor stocks suffered significant losses this year and often faced liquidity crises. The reasons behind this are many:

"First, China is resolutely advancing its opening-up, and it is reasonable for the capital market valuation system to align with mature foreign markets.

"Second, to stabilize the index, and more importantly, to ensure that the A-shares are reasonably priced before they are officially included in the MSCI Emerging Markets Index next year, relevant 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 implementation of strong de-capacity policies, the days of the real economy thriving are over, and businesses in various industries are beginning to concentrate on leading companies, enhancing the profitability of blue-chip stocks.

"The direct effect of this is that the Chinese capital market has never been so close to the institutional era.

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

The bolded sentence above is what I want to convey.

Speculating in stocks has never been easy. If in the previous decade we had to face market makers and wolves (like 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 lean towards value investing, and various subjective and objective reasons determine this. Therefore, compared to market makers 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 thoughts align more closely with those of institutions, you are likely to become a companion of institutions; if your thoughts diverge from those 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 should become companions of institutions and learn to read research reports like institutions do.#

Now, let’s begin reading research reports together!
This content is derived from the December 5, 2017 article "The World’s Trends, Division Must Unite, Unity Must Divide, Division Must Unite Again, Unity Must Divide Again..." from "Toxic Research Reports."
With the author's permission, portions of the December 27, 2017 article "Three Major Events in Brokerage Research: From Gao Li to Ren Zeping and Liu Yuanrui, the Overlooked Changes" have been quoted.

The First Glance at Research Reports#

Let’s start with strategy reports.
Life is an endless game of strategy, and strategy means achieving desired results through appropriate choices.
—— 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 talk to the homeroom teacher first, but then I thought the homeroom teacher might not be the best choice; you understand the reason; it might be better to talk to the class monitor first—don’t you think? The class monitor has both a political side and a grounded 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 A hypothetical chart of the Shanghai Composite Index based on the 2017 annual strategies

The above chart is a simulated chart of the Shanghai Composite Index 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 includes some of my personal views.

In the background of the gray line, each segment differs by 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 suggests 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 K-line 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, with the highest point of the year appearing in the fourth quarter rather than the second quarter.

Overall, if viewed from the perspective of annual investment, referencing the strategy research reports for 2017 should not pose too many issues: among the nine annual strategies, almost all were bullish for 2017, with only significant disagreements in the second quarter.

Among the nine reports, eight explicitly expressed optimism or raised the valuation center for A-shares in 2017. These eight bullish reports came from Wang Zhen of CMB Securities, 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 victory." I personally prefer reports that provide conditions over those that simply conclude; the author is Tu Jun from Shanghai Securities.

Four reports predicted the main range of the Shanghai Composite Index, with two reports estimating the upper limit at 3800 points, from Wang Zhen of CMB Securities 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—predicted 2800 points, while Wang Zhen predicted 2900 points.

Regarding quarterly peaks, three reports made predictions, with some sharp disagreements: Wang Zhen predicted a peak of 3600 points in the second quarter, while Qin Peijing of CITIC Securities also believed the second quarter would be favorable; however, Zhang Huaen thought the second quarter would face the most pressure, with the best offensive opportunity coming in the fourth quarter (after the 19th National Congress).

Regarding style operations, two reports made clear predictions, and the conclusions were generally consistent: Wang Sheng of Shenwan Hongyuan believed in value in the first half and growth in the second half; Zhang Xiaochun of Guolian Securities believed in cyclical first and growth later.

Qiqilu wants to remind everyone that for annual strategies, the conclusions can be looked at, as everyone is willing to mentally sketch the market's tone in advance; as for the specific shape—whether it is an elephant's head or an old duck's head, if 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 discourse power in the market, constantly roadshowing, so 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 like a five-day moving average; the more people believe it, the more significance it generates.

Thus, we have the following table, where the same viewpoints are represented in the same color; you can see which colors appear more frequently and are concentrated, representing which viewpoints occupy a larger proportion in the analysts' thoughts.

Table 2-1 Tagged 2017 Annual Strategies

Let me summarize:

1. The purple "profit improvement" (including "profit recovery" and "financial indicator improvement") appeared five times in the 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 promoting an increase in risk appetite and creating opportunities for overweighting stocks. This is a micro fundamental factor.
2. The yellow "expansive fiscal policy" (including "fiscal expansion" and "active fiscal policy") appeared four times in the nine reports, accounting for 44.44%. This indicates that nearly half of the strategy analysts are optimistic about the backdrop of global expansionary fiscal policies, which will certainly boost overall demand, increase nominal growth rates, and directly benefit infrastructure. This is a macro fundamental factor.
3. The red "asset allocation" appeared five times in the nine reports, accounting for 55.56%. This indicates that over half of the strategy analysts believe that institutions will overweight A-shares, thereby improving A-share valuations. This is a liquidity factor.
4. The green "real estate" appeared three times in the 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 three and is also a liquidity factor.

At that time, I summarized these viewpoints in 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 indeed "profit improvement." We saw that many solid-performing stocks (the "beautiful 50" stocks most sought after in the 2017 market) had bright performances in 2017, while some stocks that had been ignored for many years (the most representative being cyclical stocks) also re-entered the spotlight 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 of stocks that institutional investors overweighted, and the overall market's risk appetite indeed increased to a certain extent.

Except for the prediction of "global infrastructure construction," which was slightly inaccurate (mainly because the progress of the US's expansive fiscal policy was not as 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, China's exports were unexpectedly good.

Finally, I will summarize from a methodological perspective, which will be elaborated in detail in the following sections.

1. Start learning to read research reports from strategy reports.
2. Comparative research. Do not just look at one research report; instead, look at multiple reports on the same topic, such as the nine annual strategy reports mentioned above.
3. Seek commonalities. This is the tagging statistics I did, which can also be referred to as consensus expectations. I do not strongly advocate 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 out. 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 of the most outstanding minds—actually, in November 2016, these analysts' consensus opinions could hardly be considered the majority opinion.
4. Reading volume. The small study above has a total reading volume of 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 work. The total word count of the garbage articles you read on WeChat every day is definitely not less than 50,000 to 60,000 words.
5. Dehydration. This means having a certain summarization ability. Annual strategies are relatively long, and you can take a moment to jot down notes (I also take notes while reading) and try to condense the story told by each research report (which is the main logic and central idea) into something more concise. If you cannot condense an annual strategy to around 200 words, either the analyst has not written well, or your reading comprehension ability is lacking.

Well, I will use a diagram to illustrate how I dehydrated the annual strategies:

Table 2-2 Dehydrated content of the 2017 annual strategies

This can be considered our first lesson in reading research reports, where we discussed five small methods for reading strategy reports. Next, we will delve deeper into how to read strategy reports.

This content is derived 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 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 focused 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 a display of the most serious thinking results of a brokerage's strategy team.

Annual strategies are essentially an annual story, and this story is usually complete, with a beginning, development, and 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." If you hope that the annual strategy is entirely correct, that is greed; if you hope it will be correct immediately, that is also greed. In the process of reading annual strategies, many things that are later disproven 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 need not expend energy searching for such god-like teams.

At the beginning of 2017, I conducted a comprehensive overview of the annual strategies in the "Toxic Research Reports" column. Looking back a year later, as a report transporter, as long as you pay a little attention, you can accurately predict the main storyline of stock investment in 2017—of course, the term "accurate" belongs to the major institutional analysts.

It is worth noting that this annual strategy overview also includes some macro reports, but most of the selected reports are from the strategy sections of macro reports, so we will treat them as strategy reports for now. 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 2017 Assets Be Allocated?
Dear friends, may you have a prosperous start to the year! 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 should be left behind," how should assets be allocated in 2017?

Qiqilu systematically sorted through the asset allocation reports of the top ten chief analysts in the macro and strategy categories from the New Wealth selection in 2016. Among them, eight chief analysts expressed their views on asset allocation for 2017: Jiang Chao from Haitong Securities, Wang Han from Industrial Bank, Ren Zeping from Fangzheng Securities, Li Huiyong from Shenwan Hongyuan, Xie Yaxuan from CMB Securities, 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 adding conditions. Jiang Chao from Haitong Securities (last year's New Wealth macro champion) believes that there are opportunities in high-dividend stocks 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 all regard stocks as the preferred asset category for 2017.

In contrast, real estate assets are relatively viewed with skepticism; among the seven analysts who clearly expressed a low allocation to real estate assets, six explicitly expressed a bearish outlook 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 earlier, 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.

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 allocations after the second quarter; from the perspective of diversifying risks and betting on value, he is optimistic about gold, but advises buying puts rather than calls; additionally, he is also optimistic about real estate in first-tier cities, with the general ranking of asset categories being stocks > bonds > gold > first-tier city real estate. Li Huiyong believes that a major assumption is that China and the US will guide global recovery, and in this case, asset allocation will shift towards more aggressive assets and equity assets.

The most pessimistic analyst among the eight chief analysts is Wang Han from Industrial Bank (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 not optimistic about other major asset categories such as 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, the downward trend in residents' risk appetite means that other risk assets will not perform well.

Although they are both bullish on the stock market, the sentiments of the chief analysts differ greatly. The more optimistic ones are Xun Yugen and Xie Yaxuan, who both believe that 2017 will see improvements in corporate profitability, 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 calculated scores based on bullish points (4 points for the highest, decreasing in value) and bearish points (-3 points for the lowest, increasing in value). The details are as follows:

Table 2-3 Scoring of Major Asset Allocations by Eight Chief Analysts

Thus, the overall ranking of major asset allocations for 2017, based on the combined viewpoints of the eight chief analysts, should be: stocks > bonds/cash > commodities > gold. Real estate should be under-allocated.

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 need to be clear about what we want when reading strategy reports. The new wealth macro champion Guo Lei believes that the two main values of macro research are allocation and timing. I wholeheartedly agree with this judgment; strategy research reports are no different. 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 to allocate investment ratios 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 the 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 methods have been applied; I compared the annual views of eight leading strategy/macroeconomic analysts; the reading volume is around 50,000 words, and it took just one morning; as for dehydration, the central ideas summarized are direct and concise, making them easy to understand. These three methods will not be repeated.

3. I also attempted to use a new analytical method, assigning scores to each asset class based on analysts' opinions (see Table 2-3, ranging from +4 points to -3 points), with 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 was that for ordinary investors, as long as they find two asset classes—one that the mainstream opinion is concentrated on being bullish and the other that the mainstream opinion is concentrated on being bearish—they can overweight the former and avoid the latter.

From the results, the effect is still good. The stocks in the portfolio scored 25 points indeed performed well in 2017 (of course, they were also structurally good), while the real estate that scored -13 points was indeed not suitable for investment in 2017. Of course, this result would also help you avoid bonds and cash that scored 5 points, as bonds were indeed a pit in 2017; it would also lead you to miss out on commodities that scored 3 points, as commodities performed well in 2017, especially in the first half. In comparison, the avoided and missed opportunities may not be significant; as long as you bought stocks in 2017 and avoided real estate, the returns would be relatively standard.

4. Of course, the issue mentioned in point 3 has significant problems, namely that scores can only reflect totals and not structures. For example, although stocks scored as high as 25 points, if you bought small-cap stocks in 2017, your results could 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 bullish on stocks, Fangzheng, Ren Zeping, and Xun Yugen discuss valuation logic (opportunities arising from price declines or valuations not being expensive), in other words, they want you to discern which stocks are not highly valued, which clearly are not small-cap stocks; Wang Sheng from Shenwan discusses mean reversion (which is essentially the well-known and ancient Eastern logic: division must unite, unity must divide), which is a two-sided coin to valuation logic, meaning you need to discern which stocks have deviated significantly and in what direction; Xu Biao from Anxin discusses improvements in ROE (Return on Equity), which is essentially about the improvement of corporate operational performance, and this indeed is an important logic for the structural bull market in 2017, which often occurs in leading companies; while Shenwan's Li Huiyong and CMB's Xie Yaxuan discuss global recovery, which is a significant macro fundamental change and indeed constitutes an important backdrop for economic operations in