Look at the daily chart of Bitcoin market on Huobi.com. Recently, many attempts to attack 19,000 yuan have failed, and the high points have been lower each time. The strength of the bulls' upward attack has become worse and worse. Finally, it fell below the 5-day line yesterday and began short-term adjustments. Look at the hourly chart of Bitcoin prices on Huobi.com.
In 2025, against the background of intensified global geopolitical fluctuations, rising financial uncertainty, and the strengthening of national strategic resource positioning, China's gold industry will usher in a historically high boom cycle, bid farewell to the traditional operating model dominated by cyclical fluctuations in gold prices, and enter a new development stage of bullish gold prices, demand differentiation, policy regulation, and leading concentration. The latest data from iiMedia Research, the world's leading third-party data mining and analysis organization for the new economic industry, released the "2025 China Gold Industry Market Status and Benchmark Enterprise Operation Data Analysis Report" shows that China's gold investment demand will surge in 2025, with net inflows of gold ETFs exceeding 180 tons throughout the year, a year-on-year increase of 127%; sales of investment products such as physical gold bars and gold coins increased by 63% year-on-year, and gold jewelry consumption showed the characteristics of "volume reduction and price increase". The capital market presents a significant stratification pattern, with core indicators such as market value, revenue, profit, and capital flow continuing to cluster towards the top. Among them, Zijin Mining’s cumulative net profit attributable to the parent company in the first three quarters reached 37.864 billion yuan, which is particularly outstanding.
iiMedia Consulting analysts believe that the current operating performance of upstream mining companies and downstream retail companies in China's gold industry is clearly differentiated, and companies with resource reserves, global layout and full industry chain operation capabilities are occupying an absolute advantage. At the same time, multiple favorable factors such as the implementation of the new taxation policy and the continued promotion of high-quality development policies have accelerated the elimination of inefficient entities in the Chinese gold market, forcing the optimization and upgrading of the industrial structure and steadily moving towards strategic, intensive, high-end, and financialization.
In 2025, against the backdrop of escalating global geopolitical volatility, rising financial uncertainty, and the strengthened positioning of gold as a national strategic resource, China's gold industry ushered in a historic high-boom cycle, bidding farewell to the traditional operating mode dominated by cyclical fluctuations in gold prices and entering a new development phase characterized by a long-term bull market in gold prices, differentiated demand, standardized policies, and concentrated leading enterprises. Data from the latest Analysis Report on the Market Situation of China's Gold Industry in 2025 and Data on the Operations of Leading Enterprises released by iiMedia Research, a world-leading third-party data mining and analysis institution in the new economic industry, shows that China's gold investment demand surged in 2025: the annual net inflow of gold ETFs exceeded 180 tons, a year-on-year increase of 127%; the sales volume of investment-oriented products such as physical gold bars and gold coins rose by 63% year-on-year, while gold jewelry consumption showed the characteristic of "decreased volume but increased price". The capital market presented a distinct stratification pattern, with core indicators such as market value, operating income, profits, and capital flow continuing to gather towards leading enterprises. Among them, Zijin Mining's cumulative net profit attributable to parent company in the first three quarters reached as high as 37.864 billion yuan, delivering an especially outstanding performance.
Analysts from iiMedia Research believe that in the current China's gold industry, there is a clear differentiation in the operating performance between upstream mining enterprises and downstream retail enterprises, and enterprises with resource reserves, global layout and full industrial chain operation capabilities are seizing an absolute advantage. At the same time, multiple positive factors such as the implementation of new tax policies and the continuous advancement of high-quality development policies have accelerated the clearance of inefficient entities in China's gold market, forced the optimization and upgrading of the industrial structure, and promoted its steady progress towards strategization, intensification, high-endization and financialization.
gold industry definition
Golden type classification
Top 10 companies in gold industry revenue
Monitoring data shows that the top three companies in the gold industry revenue are: Zijin Mining (254.200 billion yuan), Shandong Gold (83.783 billion yuan), and Hengbang Co., Ltd. (76.444 billion yuan). iiMedia Consulting analysts believe that the revenue distribution of leading companies is concentrated, with the top three accounting for more than 60%, indicating a high degree of market concentration. Zijin Mining and Shandong Gold mainly focus on gold, copper and other metal products, while Hengbang Co., Ltd. has more diversified business, which reflects its leading position in the gold industry. The revenue structure of the industry is relatively healthy and the competition pattern is relatively stable. The scale of revenue is closely related to the size and development stage of the enterprise. Most of the leading enterprises are large enterprises in the mature stage.
Top 10 profit companies in the gold industry
Monitoring data shows that the top three profit companies in the gold industry are: Zijin Mining (55.646 billion yuan), Shandong Gold (7.568 billion yuan), and CICC Gold (5.636 billion yuan). iiMedia Consulting analysts believe that the profit distribution of leading companies shows that Zijin Mining has an absolute advantage. The core reason is that in the first three quarters of 2025, the average price of London gold has risen sharply, and companies have acquired new gold mines. The overall profit concentration of the industry is high, and the profit level and quality are high. Overall, the industry's profit model mainly relies on gold mining and sales, and leading companies have significant scale effects.
Gold industry funds flow into TOP10 companies
Monitoring data shows that the top three companies with capital inflows into the gold industry are: Zijin Mining, China Gold, and Western Gold. iiMedia Consulting analysts believe that the capital inflow structure of leading companies shows that the top three companies have significant net inflows of very large orders, indicating a clear preference for large funds, while Zijin Mining has a larger net inflow of small orders, which may be related to the market's attraction to small and medium-sized funds. The concentration of funds within the industry is high, with the top three accounting for 96.37% of the capital flow scale of the TOP10, indicating that market hot spots are concentrated in leading companies. There are significant differences in capital preferences of different sizes. Super large orders are more inclined to leading companies, while large orders show net outflows in some companies, which may be related to the market's cautious attitude towards the short-term performance of these companies. The internal logic of capital flows may be related to gold price fluctuations, corporate fundamentals, and the market's long-term expectations for the gold industry.
Top 10 companies with proportion of gold industry R&D investment
Monitoring data shows that the top three companies in the gold industry in terms of R&D investment in revenue are: Chao Acer (1.16%), CICC Gold (0.97%), and Shanjin International (0.85%). iiMedia Consulting analysts believe that companies with high proportions of R&D investment, such as Chao Acer and CICC Gold, reflect their emphasis on technological innovation, especially in terms of investment intensity in product design, process upgrades and other aspects. The overall technological innovation investment intensity of the industry is relatively low, lower than the average level of high-tech and manufacturing industries, which may affect the long-term competitiveness of the industry to a certain extent. The rationality of R&D investment needs to be analyzed based on the company's scale and development stage. Large companies such as CICC Gold and Chifeng Gold have relatively high R&D investment, which is consistent with their company size and industry status, and helps improve innovation capabilities and market competitiveness.
Top 10 companies with debt ratio in the gold industry
Monitoring data shows that the top three companies in the gold industry with debt ratios are: Yuyuan Holdings (68.91%), Cuihua Jewelry (68.78%), and Western Gold (68.49%). iiMedia Consulting analysts believe that companies with high debt ratios are generally concentrated in the field of gold mining and processing, which is consistent with the characteristics of capital-intensive industries. The gold industry has a large demand for funds, and the high debt ratio reflects the needs of corporate expansion and operations to a certain extent. The overall debt level and financial leverage level of the industry are relatively high, but risks need to be comprehensively assessed based on cash flow and profitability.
Top 10 companies with the highest price-to-book ratio in the gold industry
Monitoring data shows that Zhaojin Gold (41.38 times), Xiaocheng Technology (20.86 times), and Sichuan Gold (17.83 times) rank among the top three in terms of price-to-book ratio. iiMedia Consulting analysts believe that companies with high price-to-book ratios usually have high asset scarcity or brand value, such as Zhaojin Gold’s dual layout in real estate and mining, Xiaocheng Technology’s diversified development in solar power generation and gold mining business, and Sichuan Gold’s focus on gold mining. These companies have high asset quality, good growth potential, and stable returns on net assets, so the market gives them higher valuations. At the same time, the high price-to-book ratio also reflects the market's recognition and expectations of the future development potential of these companies.
Top 10 companies with gross profit margin in the gold industry
Monitoring data shows that Xiaocheng Technology (65.07%), Sichuan Gold (64.11%), and Huayu Mining (51.02%) rank among the top three in terms of gross profit margin. iiMedia Consulting analysts believe that the gross profit margin of leading companies is significantly higher than the industry average, showing strong profitability and competitive advantages. Especially in the resource-based industry of gold, high gross profit margin often means strong resource control and excellent cost control capabilities. The overall industry profitability is relatively high, and the gross profit margins of the top 10 companies are mostly above 20%, reflecting the high value-added nature of the gold industry. High gross profit margins are closely related to corporate moats. Resource endowment, technological advantages and brand influence are the keys for companies to maintain high gross profit margins.
Typical case studies in the industry: Zijin Mining (operations)
Zijin Mining's revenue scale continues to expand rapidly, growing from 293.403 billion yuan in 2023 to 303.640 billion yuan in 2024. In the first three quarters of 2025, it has reached 254.200 billion yuan, a year-on-year increase of 10.33%, maintaining strong growth. The company's performance shows significant seasonal and cyclical characteristics. The first quarter of each year is the low point of the year, which is mainly affected by holidays and production arrangements. Profit performance is in line with revenue and growing at a faster rate, highlighting its profitability flexibility in the upward cycle of metal prices. In terms of business, the company takes gold and copper production from mines as its core profit source, and its performance is highly tied to international metal prices. As a global mining giant, Zijin Mining fully benefits from the commodity boom cycle, but its performance is also closely linked to global macroeconomic and price fluctuations.
Typical case study in the industry: Zijin Mining (R&D investment)
Zijin Mining's R&D investment scale will show a stable and progressive development trend from 2023 to 2025. Looking at the first three quarters, it increased from 1.130 billion yuan in 2023 to 1.160 billion yuan in 2025, with an average investment of 392 million yuan in a single quarter, showing the stability of R&D investment. The intensity of R&D investment has declined, reaching 0.46% in the first three quarters of 2025, which may affect the sustainability and stability of technological innovation. Considering that Zijin Mining is in the gold industry, its R&D investment intensity is lower than that of industries with high R&D investment, but higher than that of traditional manufacturing industries, showing the rationality of the company's investment in technological innovation. In the long run, increased R&D investment will help improve the competitiveness of enterprises, but attention needs to be paid to the long-term effects of technological innovation.
Industry typical case study: Shandong Gold (capital inflow)
Shandong Gold's capital flow data shows that the main capital showed a net outflow on most trading days, especially a large outflow of nearly 800 million yuan on January 29, showing the market's strong concern and cautious investment attitude towards the company. Large order funds were mostly net inflows before January 22, and then showed net outflows. The core reasons were the correction of gold prices and the strength of the US dollar. However, the overall net inflow of mid-order funds may reflect that small and medium-sized investors are relatively optimistic about the company's development prospects and have high market attention. After January 22, investors became more cautious, and the large outflow of main funds may be related to Shandong Gold's recent operating conditions or market expectations.
Typical case study in the industry: Shandong Gold (valuation analysis)
The price-to-book ratio (PB) and dynamic price-to-earnings ratio (PE) data of Shandong Gold in the past 30 days show that both PB and PE show a fluctuating upward trend. The average PB is 6.76, with a wide range of fluctuations, from 5.48 to 9.19, showing that there are large differences in the market's assessment of the value of its assets. The average PE is 39.01, with fluctuations ranging from 31.62 to 52.97, indicating that the market's expectations for its profitability fluctuate greatly. The current PB and PE are both higher than the industry average, which may indicate that the market has higher expectations for Shandong Gold and there is a certain degree of overestimation. Combined with the characteristics of the gold industry, the market is sensitive to gold price fluctuations. The recent rise in gold prices may have pushed up the market's valuation of Shandong Gold. Overall, valuation changes reflect the market’s optimistic expectations for the prospects of the gold industry, but one needs to be wary of the risks posed by gold price fluctuations.
Industry typical case study: Lao Fengxiang (business situation)
As the leader in jewelry, Lao Fengxiang's revenue scale fell back to 56.793 billion yuan in 2024 after hitting a new high of 71.436 billion yuan in 2023. The 48.001 billion yuan in the first three quarters of 2025 was also lower than the same period last year, showing the impact of industry cycle adjustments. Its revenue is highly concentrated in the jewelry business, accounting for 84.55%, and its performance is directly related to the strength of the gold consumer market. The profit trend is highly synchronized with revenue, with a year-on-year decrease of 14.10% in 2024. Despite facing a short-term correction, its core competitiveness in channels and brands remains solid. Future performance requires close attention to the trend of gold prices and the recovery of terminal consumption.
Industry typical case study: Lao Fengxiang (asset analysis)
Lao Fengxiang's total assets showed a trend of first increasing and then decreasing from September 2024 to September 2025, with an average total assets of 25.030 billion yuan, showing that the company's assets are relatively large. The proportion of non-fixed assets is as high as 94.77%, and fixed assets only account for 5.23%. The asset structure is similar to that of the technology industry and is in line with the characteristics of light-asset enterprises. This helps enterprises quickly respond to market changes and improve the efficiency of capital use. In terms of asset growth, both fixed assets and non-fixed assets showed slight growth, and asset growth was relatively balanced. Overall, Lao Fengxiang's asset scale matches the company's operating scale, and its asset structure is reasonable, which helps the company's flexible operations and risk control.
The content of this article is selected from the "iiMedia Consulting | 2025 China Gold Industry Market Status and Benchmark Enterprise Operation Data Analysis Report" released by iiMedia Research. The report has a total of 66 pages. Follow iiMedia.com for more industry reports to decode business trends and help you make accurate decisions!
Gold soared by 42 yuan/gram in a single day, and the price in gold stores exceeded 1,608 yuan! When you grit your teeth and buy a gold necklace, Wall Street is selling it secretly. Behind this national carnival, there are three deliberately concealed truths.
Today, when the international gold price stands firm at 5,279 US dollars per ounce, it is no accident that the domestic retail price of pure gold has soared to 1,600 yuan per gram. The roar of fighter jets in the Middle East is still in our ears, the oil tanker alert about Iran's blockade of the Strait of Hormuz has not yet been lifted, and funds have already poured into gold exchanges. Data shows that the single-day inflow of gold ETFs yesterday alone was equivalent to 3 million grams of physical gold, and risk aversion has heated up the entire market. What's even more subtle is the countdown to the Federal Reserve's interest rate cut - the moment U.S. bond yields fell below 4.5%, the cost of holding gold plummeted by 8%, and JPMorgan traders' desks were filled with call option orders. The purchase lists of various central banks further reveal their long-term ambitions: China has increased its gold holdings for 16 consecutive months, India and Brazil have been frantically buying up gold, and central banks around the world robbed 863 tons of gold last year, which is equivalent to emptying two mines every day.
When I walked into the mall, I discovered that the price of gold had already split in layers. The Chow Tai Fook counter has a price tag of 1,608 yuan, but the menu next door says 1,558 yuan. The difference of 50 yuan is enough for a hot pot meal. The Shuibei Wholesale Market even staged a magical reality - the bare gold price of 1,374 yuan, plus the labor cost of 35 yuan, instantly transformed it into a luxury product. The mystery behind bank gold bars: China Construction Bank sells them for 1,184 yuan per gram, while Chow Tai Fook bids 1,415 yuan for the same model. The price difference is enough to buy two mobile phones. The recycling market is in a state of ice and fire: the recycling price of 99.9% pure gold is 1,140 yuan, but the price of 18K gold is reduced to 832 yuan. The old master's hand holding the detector trembled slightly: "The number of fake gold bars doped with iridium has increased by 30% recently. "
The numbers in the golden T+D account are beating with the cruel truth. Behind the market price of 1,154 yuan/gram are retail investors and million-level leverage players who are watching the market at three o'clock in the morning. The transaction details of the Shanghai Gold Exchange show that an institution invested 2 billion in a single purchase contract, while merchants in Shuibei, Shenzhen, were packing gold jewelry overnight and sending it to Hong Kong for cash. The most ironic thing is the international and domestic price difference - the international gold price of US$5,279 should be converted into RMB 1,164 per gram, but the domestic spot price is quoted at 1,155 yuan. The loophole of upside down price of 9 yuan per gram has become a cash machine for arbitrageurs.
You are now standing in front of the jewelry counter, holding your year-end bonus in your left hand and reading the gold price chart in your right hand. The teller enthusiastically introduced that "the ancient gold craftsmanship has great potential for appreciation", but he would not tell you that the same style is only 1,375 yuan at the Shuibei Wholesale Market. When the gold price peaked during the wedding season, young people began to rent gold bracelets to take wedding photos, and the transaction volume of "gold drift bottles" on the second-hand platform soared by 300%. Those experts who claim to "buy gold to fight inflation" may have all their gold positions in their accounts.
The light of gold has never been so dazzling, nor so bewildering. When the label of 1,600 yuan is reflected in your pupils, have you ever calculated this: if the money from this gold chain is deposited in the bank for three years, the interest will be enough to buy many cups of milk tea? If the price of gold plunges 10% tomorrow, will you be a bargain hunter or a taker? Let me know your choice in the comments section - after all, in the gold game, everyone is their own prophet.
According to the Litecoin trading platform Huobi.com, as of 10:00 on July 26, Beijing time, the price of Litecoin was RMB 287.96. The opening price of Litecoin on Huobi today was 289.99 yuan. The current highest price is 292 yuan and the lowest price is 282.01 yuan, a decrease of 0.7%.
Look at the hourly chart of Litecoin market on Huobi.com. The price of Litecoin on Huobi.com has broken the shock pattern. The recent shock box of 290-310 yuan has been effectively broken. However, judging from the decline in trading volume and the intensity of the decline, the decline is not large compared with Bitcoin, showing a certain resistance to the decline. Although the willingness to fall is not strong, as the daily-level short position trend has been formed, in the short term, attention is still focused on risks. Shrinking means that the possibility of imminent changes in the market is increased.
LTC Litecoin market hourly chart from Huobi.com
Industry:
Ethereum ICO Veritaseum was stolen, losing $4.5 million in funds
Over the past few months, crypto-asset ICOs have been both a blessing and a curse. This type of business model allows users to raise funds without going through official channels. Yet, at the same time, people must entrust millions of dollars to strangers. To make matters worse, ICOs may also face theft and fraud. Veritaseum is the latest ICO to be hacked. The project had $4.5 million worth of tokens stolen last night.
It’s terrible to see a crypto asset project stolen. In most cases, these types of thefts are the result of hacking. The Veritaseum ICO that just concluded recently encountered this accident. Specifically, someone successfully stole a large amount of VERI tokens. All funds were transferred to two different addresses. Currently, the cumulative value of stolen tokens is around $4.5 million, and this attack has gained a lot.
Millions of dollars stolen from Veritaseum ICO
Details about the attack are currently unknown. The hackers appear to have used some "very sophisticated attack techniques," although the team did not disclose specific details. What we do know is that the attack vector has been adjusted to ensure that similar situations don't happen again in the future. Unfortunately for the team, retrieving the funds is nearly impossible. There is no doubt that the stolen tokens will soon be cashed out on multiple exchanges.
Unfortunately, this is not the first time an Ethereum ICO has encountered this type of problem. In fact, recently, theft of funds has become the "normal" for crypto asset ICOs. Not long ago, several projects were stolen due to the MyEhterWallet vulnerability. Additionally, approximately $37 million worth of Ethereum was stolen from some projects in the past few weeks. It is clear that the technology used by these ICOs combined with centralized servers creates a large number of problems. This is the price to pay for adopting immature technology.
Fortunately, the theft had little impact on investors participating in the ICO. It appears that the stolen funds belong to Veritaseum team members, although this has not been confirmed.
Cryptoasset ICOs continue to grab media headlines, often in a negative light. Whether this situation will change anytime soon is uncertain.
The theft of Veritaseum may also be another phishing attack. 4,500 VERI have been sent to Etherdelta so far, worth approximately $500,000.
Research | Written by Wang Yugang and Lu Shiyu | Zhang Yang
In recent years, quantitative investment has attracted more and more attention, and financial practitioners and institutions have tried to lift the mystery of quantitative investment and obtain higher returns through it. At the same time, with the support of AI, quantitative investment is more efficient. However, for individuals, there are currently only a handful of AI quantitative platforms; for institutions, building an AI quantitative platform has high technical requirements.
Founded in 2016, Kuanbang Technology applies its own AI technology to quantitative investment, exports a simple and easy-to-use quantitative platform to C-side customers, and provides overall solutions to B-side customers, allowing customers to overcome technical difficulties and directly use AI quantitative tools.
Strategically, Kuanbang Technology first launched the AI quantitative application platform BigQuant for C-end users. In the process, it improved its technical capabilities, optimized its products, demonstrated its strength through the C-end platform, and cultivated brand awareness.
After that, we will provide overall solutions for the AI quantification platform for B-side financial institutions, especially securities firms. At the same time, Kuanbang Technology has commercialized BigQuant’s underlying technology platform and launched the Big AI full-stack artificial intelligence platform, which is commonly used in the financial industry.
For C-side users, the BigQuant website not only has efficient strategy writing functions, but also has a very low technical threshold.
The platform data is mainly public financial market data, and users can also define their own data sources. In terms of technology, users understand the basic principles of AI and quantification, and if they understand a little bit of code, they can write their own strategies on the platform. Through the simulated real trading function, users can easily conduct model backtesting and optimization. Moreover, through authorization, C-side customers can connect their trading strategies to the brokerage platform where they have opened an account and conduct real trading. In addition, platform users can exchange methods, share function tools, and sell their own strategies.
For B-side customers, after Kuanbang Technology has deployed the AI quantification platform, they can directly apply its writing strategies at work, conduct transactions, and pursue high returns.
Kuanbang Technology will provide overall solutions for the AI quantification platform based on the B-end customer situation. The advantage of BigQuant is that it encapsulates data processing, model building, backtesting, trading and other modules and presents them to strategy writers in a visual interface. This not only greatly reduces the technical requirements for quantitative traders, but also lowers the technical threshold for model development and maintenance.
Kuanbang Technology's overall service eliminates the need for B-end customers to set up their own AI and algorithm teams, reduces the cost of platform construction, and can be quickly applied to work.
01
Brokerages are the main source of income
Cultivate C-side users with a view to commercialization
As mentioned above, Kuanbang Technology serves C-side customers through the BigQuant website and B-side financial institutions through solutions. In addition, it opens the BigQuant platform to universities to assist in cultivating AI quantitative talents.
The C-side has accumulated tens of thousands of strategy developers, 1/3 of which are professional investors. Users who develop strategies on the platform can be subscribed by other users for a fee, and some users can earn over RMB 10,000 per month in strategy subscription fees from the platform. Strategies developed by investors through the platform are used by many quantitative asset managers to release private equity products and for real trading.
B-side financial institutions are Kuanbang Technology’s current main source of income, especially securities firms. Brokerages are the most active party in investment activities in the financial market. They hope to use new methods to increase investment returns, but their own technical capabilities are limited.
On the one hand, Kuanbang Technology has solved the problem of building an AI quantification system for securities companies, enabling the system to go online quickly and reducing personnel barriers and costs for operation and maintenance. On the other hand, compared with traditional trading methods, AI quantitative trading returns have significantly improved.
Based on the above two benefits, brokerages are willing to pay for BigQuant. The charge for the overall solution is divided into two parts, the project deployment fee and the subsequent annual maintenance fee. At present, Kuanbang Technology has served dozens of securities firms and private equity institutions, including leading companies such as CITIC Securities.
Recently, AiAnalysis conducted an exclusive interview with Liang Ju, founder and CEO of Kuanbang Technology, and now shares the exciting content as follows.
02
China’s quantitative trading market is still in its early stages
AI application potential is huge
AiAnalysis: What can we learn from in the foreign quantitative trading industry?
Liang Ju: Relatively speaking, the foreign quantitative industry is much more mature and has many types of transactions. If high-frequency trading is included, about 80% of the trading orders in the market are issued by machines, and the machines are algorithm-driven in the background. Some larger funds, such as Renaissance and Two Sigma, are using machine learning and other methods to make machines better able to trade.
The domestic quantitative industry is in its early stages. First of all, the market share of companies that conduct transactions through quantitative trading is still very low; secondly, tradable targets are not abundant, and market effectiveness is relatively low; in addition, compared with traditional trading methods, the performance accumulation of quantitative trading is not enough, and it needs to accumulate for a period of time for the market to see the effect.
At the same time, in the face of changes in the domestic market, securities firms are looking for new trading methods. The advantages of AI quantitative trading are reflected in two aspects: on the one hand, AI is a greater productivity; on the other hand, the performance advantages of quantitative trading will gradually emerge. Quantification has many natural advantages, such as not being affected by human emotions. Therefore, the application of AI and quantification is likely to grow significantly in the next few years.
iAnalysis: How is the application of AI quantitative trading in the Chinese market different from that in the United States?
Liang Ju: We found that China is a very large market. Applying our algorithm to A-shares, it is easy to achieve an annualized return of 50%. However, in the US stock market, it is very difficult to achieve 10%-20% because market information is very transparent and other companies are very competitive.
There is a lot of information asymmetry in China's A-share market, and some good results can be achieved by using volume and price. And the machine digs deeper, getting better results. At this stage, those using AI will gain first-mover advantages.
AiAnalysis: Is there any competition with other domestic quantitative trading platforms?
Liang Ju: The entire investment activity covers many aspects. Broadly speaking, it covers investment strategy (which financial products to do), investment strategy (how to do investment transactions), and transaction execution from top to bottom. Companies that provide quantitative services will do a certain part of the business in a targeted manner based on their own capabilities and understanding of the market. So it may be a competitive relationship or a cooperative relationship.
Traditional quantification focuses on the execution level, where people write strategies. Artificial intelligence, on the other hand, is more strategic and involves machine-written strategies. On our platform, you don’t need to give instructions to the machine. You only need to set goals for the machine. For example, screen out the stocks with the highest price increases in the next five days, and then the machine will find the stocks through the machine learning model. People can combine their own abilities to screen and further optimize.
Quantification is low-dimensional, while AI is high-dimensional. We provide a platform with both quantification and AI functions.
03
Provide customers with overall solutions, extending downward from industries with high data concentration
Love Analysis: Is AI an improvement on traditional strategies, or is it using a completely new strategy?
Liang Ju: Including these two aspects. On the one hand, it is optimization, which allows the machine to learn the parameters of the original strategy; on the other hand, AI may find a better path with less resistance, thereby obtaining better results.
Love Analysis: What is the difference between BigQuant and traditional AI technology?
Liang Ju: We mainly treat machine learning as a service, and do not require customers to do data processing, build machine learning frameworks, and build algorithm models themselves.
CITIC Securities used to take 40 minutes to access data, but we helped them optimize it to the second level. They don’t know how to build a machine learning framework, but our platform is transparent to them and can handle large amounts of data.
AiAnalysis: Is it connected to the securities firm’s trading system?
Liang Ju: When we help securities companies with privatization deployment, we will directly extend it to the trading side. Whether it is for the internal needs of securities firms or the needs of their customers, the transaction interface needs to be opened. The docking of the transaction interface is very simple, but compliance must be ensured.
AiAnalysis: Are there any technical or financial barriers to users?
Liang Ju: In fact, we have lowered the ability requirements for users very low, and we will further lower them in the future. Our platform now still requires users to have a certain understanding of AI and quantification. People who understand the rules of market operation will choose better features and let the machine learn them, and the results will be better.
AiAnalysis: Can strategy developers see how their models are optimized?
Liang Ju: AI technology itself is a black box, but we try to open up the AI algorithm part so that strategy developers know how the results come from. So we are also doing investor education and training.
iAnalysis: What securities products can BigQuant be applied to?
Liang Ju: You can do US stocks, A-shares, Hong Kong stocks, and futures. To us, these transactions are actually data. Some foreign exchange institutions are also cooperating with us, and there are even digital currencies. For different securities products, the same AI platform is used, but the trading algorithms are different.
AiAnalysis: In addition to quantification, in what fields do you plan to implement Big AI in the future?
Liang Ju: In the early days, we visited many companies, including securities firms, banks, and insurance companies. Among them, securities companies have many scenarios that can be implemented, and quantification is the most direct. At the same time, quantification can also assist traditional investment, such as screening stocks for investors, and then letting people do further processing.
Other implementation scenarios include intelligent customer service. The original intelligent customer service only needed to add a corpus and knowledge base, but now machine learning can make intelligent customer service do a better job.
The choice of implementation scenario is to start from industries with a high degree of data concentration or a high degree of acceptance of AI, and then expand to areas with a lower degree of data concentration or a relatively low degree of acceptance. During this process, we will also continue to polish the products.
04
Breaking down AI quantitative talent barriers for securities firms
iAnalysis: Which types of financial institutions are the main customers?
Liang Ju: We mostly serve companies with weak IT in the financial field. Brokerages want to do AI quantification, but the IT and development departments themselves lack capabilities and need to rely on mature outside technologies.
AiAnalysis: What are the benefits of Kuanbang’s overall solution to securities companies?
Liang Ju: On the one hand, excellent AI technical personnel are scarce, and it is difficult for brokerage firms to build their own teams and build platforms. The threshold of our platform is very low, which reduces the dependence on talents. AI quantified knowledge can be deposited in enterprises.
On the other hand, when it comes to big data, machines can do better than people. Humans can only see part of the world and achieve local optimization, but machines can see more and achieve global optimization. For example, the results obtained by a human based on 3 stocks may be different from the results obtained by a machine based on 3,000 stocks.
iAnalysis: How long does it take for a brokerage’s privatization deployment process?
Liang Ju: It can be deployed in a week or two, and then it has to be connected to the customer's system. The whole process takes about a few months because the customer's internal system is relatively complex.
He further explained that firstly, the change fee rules lacked fair consideration. If a passenger misses the train on the day and changes his ticket before 24:00 on the day of departure, he can only change the train to the next day or later, and he will have to pay a handling fee of up to 40%, which is much higher than the 20% standard for refunds in the same period. This billing method does not fully take into account the objective needs of passengers who "still need to travel after missing the train". Passengers who miss the train due to operational errors or traffic delays often have to bear additional costs beyond their expectations. At the same time, the 15% handling fee for ticket changes less than 24 hours before driving is too burdensome for small tickets and lacks an upper limit protection mechanism.
Second, the rebooking operation lacks a withdrawal mechanism. Once the current change operation is confirmed, it will take effect immediately and cannot be withdrawn. If passengers cannot restore the original ticket status due to operational errors, system delays, or misoperation by others, they can only choose to refund the ticket and bear additional fees. This "correction means loss" design leaves no room for passengers to make corrections and significantly increases the cost of travel without subjective intention.
Third, service connection and information prompts are obviously insufficient. At present, the railway department's "free refund within 30 minutes" policy to benefit the people has not yet been extended to the ticket change process. The official platform operation page lacks clear risk warning and fee preview functions, making it difficult for passengers to predict the actual handling fee amount before confirming the change. In addition, the rules for changing tickets on third-party ticket purchasing platforms are different from the official ones. The rules are opaque and inconsistent, which can easily lead to misunderstandings and disputes.
In order to optimize the EMU rebooking service and protect the legitimate rights and interests of passengers, Lei Maoduan put forward three suggestions. The first is to optimize the billing rules for rebooking fees. The handling fee for rebooking for the next day and subsequent trains after missing a train will be reduced from 40% to 20%, consistent with the refund standards, taking into account railway operating costs and passenger affordability. The 15% handling fee for ticket changes less than 24 hours before driving is stipulated, and a cap of 50 yuan is added to avoid excessively high handling fees for small tickets. At the same time, for special groups such as the elderly, students, and disabled people, relying on the 12306 real-name authentication system, free rebooking opportunities are provided twice a year; any rebooking losses caused by system failures or prompt errors shall be fully refunded after verification.
The second is to establish a withdrawal mechanism for rebooking errors to provide room for error correction. Set up a 30-minute free withdrawal window after ticket changes, allowing passengers to promptly restore their original ticket status after an operation error. The conditions for withdrawal are limited to more than 4 hours before driving time, failure to print out the reimbursement voucher, and failure to check in luggage. After withdrawal, the original seat information will be restored and the number of changes will not be used. For emergency rebooking errors that are less than 4 hours before driving, a manual review channel is opened. If it is verified that it is a non-subjective and malicious operation, the rebooking can be revoked and only a 10 yuan cost will be charged. Special groups are exempted.
The third is to improve the service guarantee system and improve operation friendliness. The official platform operation interface has been optimized, and key information such as fee details and withdrawal time limit are clearly marked on the rebooking page. Secondary pop-up window confirmation and real-time fee preview functions have been added to guide passengers to standardize operations. Promote the unified change of rules between the railway department and mainstream third-party platforms to ensure synchronized and transparent policies. Establish a rapid handling mechanism for rebooking disputes and promise to respond to passenger complaints within 72 hours and provide feedback on the handling results within 15 working days. The 12306 system was simultaneously upgraded to realize the real-time effect of the withdrawal operation, and an online portal for "Rescheduling Error Appeal" was added to support passengers in uploading certification materials for manual review, improving service convenience.
Lei Maoduan pointed out that optimizing the EMU rebooking service can not only effectively solve the practical pain point of "easy to change but difficult to correct errors" for passengers, and highlight the public welfare attribute of railway passenger transportation, it can also promote the transformation of railway services from "management-oriented" to "demand-oriented", reduce rights disputes from the source, and enhance people's sense of travel gain.
The world is changing faster and faster, but women are becoming more determined.
On March 6, a female travel report released by Qunar Travel showed that in the past year (March 2025-March 2026), the number of women choosing to stay in hotels alone increased significantly by 63% year-on-year, and the number of women traveling alone by plane also increased by 34%. Compared with men, women fly more economically and live more comfortably. The average hotel price paid by women is 20% higher than that of men.
Women on a solo trip don’t need complicated preparations to set off. They only need an air ticket of their own and a hotel room that only they can stay in.
In the past year, the most popular cities for hotel stays and flight destinations were still large cities with both business and travel attributes such as Beijing, Shanghai, Guangzhou and Shenzhen. It is worth mentioning that the number of women choosing to stay in hotels alone increased significantly by 63% year-on-year.
Judging from the increase in hotel check-in cities, in the past year, women on solo trips have turned their attention to niche cities around them. Data shows that in Chongzuo, Weifang, Handan, Puyang, Ziyang, Lishui, Haikou, Putian, Linfen, and Jiuquan, the number of women staying in hotels alone has nearly doubled.
Among the increases in female solo trip routes in 2026, short-distance routes will lead the country. Data shows that in the past year, the fastest growing route was Chengdu-Lijiang. In just one weekend, with a one-way flight of 1.5 hours and a round-trip ticket as low as 600 yuan, the "Chengdu Girl" flew to the romantic Lijiang, driving a nearly 50% year-on-year increase in route ticket volume. The Nanjing-Guangzhou route followed closely, with an increase of more than 40%, becoming a popular choice for cross-city roaming.
In terms of outbound travel, in the past year, the number of women traveling alone by air has also increased by 34% year-on-year. The most popular flight routes are still from first-tier cities to neighboring countries such as Thailand and South Korea, as well as China, Hong Kong and Macao. The TOP10 includes Shanghai-Seoul, Beijing-Seoul, Shanghai-Jeju Island, Hangzhou-Seoul, Qingdao-Seoul, Beijing-Hong Kong, China, Guangzhou-Seoul, Shanghai-Bangkok, Shanghai-Hong Kong, China, and Guangzhou-Bangkok. In terms of growth rate, Yantai-Seoul increased by 1.6 times, Guangzhou-Chiang Mai and Hangzhou-Seoul increased by 1.3 times, Shanghai-Busan increased by 1.2 times, and Tianjin-Seoul increased by 1.2 times.
Jiupai News Reporter Li Yang Li Kai
Editor Wan Xuan Fu Shan
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