Cthulhu's Teapot: Quantitative analysis of China A-shares thematic speculation in the past 5 years
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Many critics argue that China's onshore market has not experienced substantial financial returns compared to US equity market, particularly when examining major indices such as the Shanghai Composite Index over the past decade. One might hope that these indices accurately represent the investment return potential of the onshore A-share market. However, the China A-share market is characterized by high volatility and driven by thematic speculation, making it less favorable for a traditional buy-and-hold strategy.
Nonetheless, amidst the market's intricacies, there exist opportunities to capture its main trends and identify optimal entry points. Selecting the right trend can lead to triple-digit returns in under a year. Conversely, missing out on the dominant themes of the current year may result in significant declines in returns.
To navigate this unique landscape effectively, it is crucial to understand the distinctive nature of the A-share market and, more importantly, how to discern the prevailing main trend in any given year.
In this post, we present a translation of exceptional research conducted by Mr. Bob Chen. The article delves into top-notch sectors that have yielded substantial gains over the past five years from a quantitative analysis perspective. Furthermore, it offers invaluable insights into understanding the market's underlying logic and how to identify the next exponential growth opportunity.
About the author: Bob Chen is a venture capitalist and a former macro-economist based in China. Decoding China's financial market and macroeconomic trends with AI-driven technology is one of Bob’s many interests.
Cthulhu's Teapot: Quantitative analysis of A-shares thematic speculation in the past 5 years
Imagine the A-share market as a water kettle, one that is continuously shaken and distorted by the invisible force of Cthulhu. The flow of water in this market is intricately tied to the kettle's shape, market sentiment, and the force's magnitude. However, at a certain moment, there will always be a prevailing direction in the market where the water is most abundant. This phenomenon is known as the crazy theme rotation of A-shares, leaving many investors desperately seeking ways to chase this direction.
The market expectations even become self-reinforcing, leading to herd behavior among public funds, starting from exuberant market sentiments and escalating into madness, ultimately culminating within this chaotic state.
The A-share market exhibits high volatility, significant cyclicality, and is driven by thematic speculation. This makes it less favorable for a buy-and-hold strategy. However, it does offer good liquidity, even for smaller, lower-market-cap stocks. With themes rotating frequently, there are numerous structural opportunities to explore. The challenge lies in capturing the market's main trends and timing the right entry points.
Over the years, with the index remaining stagnant or even weakening, missing out on the current year's main themes or sectors can lead to significant declines in returns. On the other hand, if one manages to grasp and ride the market's waves, substantial excess returns can be achieved. This is why "value investing" in A-shares has been heavily criticized lately, as the market structure is not favorable towards value-oriented approaches. While others are riding the waves, those who are diving might find themselves stuck at the bottom for years.
How to grasp the rotation of themes?
The emergence of main market themes is often the result of multiple factors coming together. Firstly, a solid market foundation is essential, as seen in recent cases with CPO modules (Baiguan: CPO refers to Co-packaged Optics, which is a packaging technology used in the field of data communications and networking.) This theme was supported by ample supply and demand, positive market prospects, and significant orders, leading to its rapid and substantial growth, even surpassing AIGC in both speed and height. On the other hand, AIGC's rise was largely driven by emotions and speculations.
When GPT first gained popularity, my initial reaction was that most related domestic stocks would suffer significant declines. This was due to GPT's focus on application-layer companies, with the high entry barrier of large models leaving mid-to-small-sized companies lagging behind, precisely the kind of companies prevalent in the A-share market.
However, the market quickly proved me wrong. When investing in A-shares, investors undergo a learning process often accompanied by irrational passion and imagination, which benefited the AIGC concept. Since it couldn't be falsified in the short term, everyone joined in on the hype. Furthermore, this further aligns with China's national strategy to promote data resources ("数据要素"), such as China-specific large models, which bolstered the fundamentals and further fueled the uptrend.
Yet, from a global industrial chain perspective, the highest-quality tickers in both hardware and software are in the US stock market. The ceiling for speculation in the A-share market became evident. As more and more tickers jumped on the AIGC bandwagon, the index tracking the AIGC theme became increasingly cluttered, and the high valuation of AIGC-themed equities became increasingly doubtful. Consequently, the theme index fell back, culminating in a few dramatic, iconic events: share disposals due to divorce and Wang Huiwen's departure due to depression.
Baiguan’s note:
Both events led to the price collapse of the AIGC-related stocks.
The stock price of Kunlun Wanwei (300418.SH) experienced a significant drop and hit the limit-down after an announcement of a planned reduction in shareholding by major shareholder Li Qiong. Li Qiong, who is the ex-wife of the company's founder, intends to reduce her stake by not more than 3% of the company's shares. Despite claiming to support the company's business, some investors view this move as a disguise for divesting shares. Similar cases of significant shareholding changes due to divorces have been observed in other A-share listed companies this year.
Former Meituan co-founder Wang Huiwen has stepped down from important positions due to "personal health reasons." After retiring from Meituan, Wang Huiwen founded an AI company called "Beyond Light Years" that quickly gained significant funding and attention. However, his recent announcement of "personal health issues" has raised speculations about its impact on the company.
Eventually, everyone woke up from their dreams.
Regarding hardware, China's comparative advantage was highly evident, as it perfectly aligned with China's policies and the preferences of Chinese investors, who were actively seeking tangible, calculable advantages. This alignment became particularly evident when major players like Nvidia, Microsoft, and Google increased their orders for CPO modules. The presence of clear-cut business relationships with global leaders and the predictability of stable hardware shipments played significant roles in propelling the CPO theme to rise.
In the end, the CPO theme outperformed the AIGC index with higher gains and faster growth of return. It continued to surge even after AIGC entered a sideways trend.
Historically, multiple themes have exhibited similar characteristics. Themes supported by market fundamentals, being quantifiable, favoring industrial chain hardware advantages, and possessing strong certainty, tend to have more substantial uptrends in terms of duration and magnitude. Examples include lithium mining, liquor, and rare earths. Hence, A-shares can be described as having structural trends supported by market fundamentals.
Given this market structure, the objective becomes quite simple: we must analyze the annual “beauty contest” results and pinpoint the most remarkable upward cycles each year. These cycles should demonstrate sustained uptrends, minimal pullbacks, and a consistent pattern of reaching new highs.
However, the challenge lies in the A-share themes' steep upward slopes, which can lead to missing out on substantial returns if one fails to catch the early stages. For individual investors, substantial information asymmetry makes it difficult to timely capture the left-hand side of the trend [Baiguan: left-hand trading refers to investing in an asset while the price is still falling]. Institutions, on the other hand, may face high costs in building positions due to their significant capital size and concerns about the theme's sustainability after entry. Speculative investors, although agile and capable of influencing momentum, face a multitude of theme choices, and amid rotations, they may become sacrificial to the secondary themes.
Therefore, reviewing the magnitude and duration of historical uptrends of past themes can be helpful in understanding the main trend. Firstly, it helps to determine whether the current high level can still accommodate enough space for further returns. Secondly, it shows how much time is left for positioning and whether there is room for a calm exit.
Thus, we can attempt to quantitatively capture past champions of themes. As always, the assistance of GPT comes in handy.
Our goal is to capture the upward cycles of various themes and determine their magnitude and duration. To do this, we need a simple algorithm to identify continuous upward cycles for each theme while filtering out periods of oscillation or decline.
The challenge lies in defining what "continuous" means. It requires a significant upward movement that distinguishes it from fluctuations and oscillations. Sometimes, certain indices appear to be consistently rising, but in reality, they consist of multiple consecutive waves with relatively flat areas in between. We want to avoid considering the entire upward movement as a single "rise period" and instead divide it into a moderate number of upward cycles that are both meaningful and actionable for investors. This means cycles that have sufficient value in terms of magnitude and duration.
To address this, I employ a method that uses retracements to identify the beginning and end of upward cycles. By controlling the size of the given retracement, we can adjust the threshold for whether to include a cycle in our analysis. Once we identify a significant retracement that signals the complete end of an upward cycle, we can trace back to find the starting low point and final high point, and consider the interval in between as the "rise period."
Let's start by examining the results.
For the AIGC index, Wind's data starts in 2019. It looks like this on the candlestick chart.
I used the algorithm to search for upward cycles and measured the price movement from the lowest to the highest point using the height of the histogram (Y-axis: maximum gain) and the number of days using the width (X-axis: upward days). The results are presented below:
This result is quite intuitive, as we can observe that the index had previous upward cycles, but the most significant one is the last one. Let’s mark the corresponding time period on the candlestick chart (in blue shade):
The algorithm effectively captured the upward cycles, but the only drawback is that the period covering the year 2021 is a bit too long. Adjusting the retracement threshold could further split the cycle and remove the initial volatile phase. However, doing so might fragment the cycles too much, increasing trading frequency. Hence, we will maintain the 20% threshold, which is often considered a stop-loss level for many investors with a medium-to-high-risk appetite.
Don’t worry; we will eventually remove smaller fluctuations from the analysis in a larger dataset.
To account for cases where occasional retracements exceeded the threshold but quickly resumed upward movement and reached new highs, we merged upward cycles that were less than one month apart into a single cycle.
Next, I collected data for the popular indices provided by Wind, specifically, the thematic indices they compiled based on market themes, totaling 260 indices. The data spans from 2019 until the present (data before 2019 is incomplete). From this dataset, I filtered out indices with limited investment significance.
By selecting the top 30 upward cycles based on the percentage gain from the start date to the present, we compiled a "skyline" of the best-performing A-share thematic indices. To enhance clarity, I made some minor adjustments to the code, making the longer duration more visually transparent. As a result, indices that experienced rapid short-term gains are now prominently displayed at the forefront. It's worth noting that the same index might have more than one upward cycle making it to the top 30 list.
Even before examining the specific names of the thematic indices corresponding to the stock codes, we can already observe a prominent characteristic: the stock market's downturn in 2022 resulted in a “desperate valley”, with no index gains making it into the top 30.
Since 2023, the CPO concept (8841258) has stood out as the sole surviving theme to explode in the stock market after a year of suppressed performance. Strictly speaking, this theme is still unfolding and has not completely concluded, so it still has the possibility of catching up with its predecessors. In comparison, the highest gain of the AIGC concept is less than 120%, and it cannot even enter the top 30.
For these top-notch themes, upward cycles with gains exceeding 300% are also quite rare, with only four indices achieving this feat.
So, how long do these top-notch upward cycles generally last? Among the top 30, two-thirds of them lasted for over a year. In other words, to capture the entire gain from the bottom to the peak, most thematic cycles span over one year. As seen from the chart below, the 400-day mark serves as a watershed. For A-share investors, this is already a considerable period, which suggests that buying and holding might not be a bad strategy if one chooses the right direction. What can be guaranteed is that this theme can sustain an upward trend for over a year, with retracements not exceeding 20%, and even if they do, new highs can be achieved within one month.
Let's list the top 50 upward cycles, including the start date, duration, and percentage gain:
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