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Beijing investigates the first case of pyramid selling using blockchain and virtual currency, a technology company was fined and confiscated over 930,000 yuan

According to a report from the Beijing Daily client, the Market Supervision Administration of Haidian District, Beijing, investigated and handled the city's first illegal case of assisting pyramid schemes using blockchain and virtual currency technology, resulting in a technology company being fined and confiscated a total of over 930,000 yuan.The technology company involved is an outsourcing service provider for a certain public blockchain, offering support such as operations, market services, publicity and promotion, exchange docking, and maintenance. This public blockchain launched the "Atomic Plan" and "Hathaway Plan," which are centered around recruiting people for rebates, using the number of recruited individuals as the basis for rebates, and requiring participants to invest funds to obtain membership qualifications. Despite being aware of the pyramid scheme applications associated with this public blockchain, the involved company continued to provide technical operations, external publicity, and maintenance of virtual currency trading channels, facilitating the flow of funds and the spread of activities related to the pyramid scheme.Ultimately, the pyramid scheme activities of this public blockchain were investigated by public security authorities, the organizers were criminally detained, and the involved technology company was administratively punished with a total fine and confiscation of over 930,000 yuan for providing facilitative conditions.

Goldman Sachs: Global technology stocks had a net sell-off of 20 billion USD in two weeks

According to Goldman Sachs data, in the past two weeks, global technology stocks have experienced a net sell-off of approximately $20 billion, with the intensity of the sell-off reaching an extreme level of -3.3 standard deviations. The sell-off scale in the TMT sector is close to the $23 billion seen in July of this year. Meanwhile, the volatility spread between the Nasdaq 100 Index and the S&P 500 Index has risen to the 98th percentile of the past five years, indicating a significant increase in market demand for hedging against technology stocks.According to JPMorgan, the scale of debt financing for AI infrastructure has exceeded $500 billion this year, with the financing costs for large-scale cloud service providers rising by about 120 basis points compared to before. As Google, Microsoft, and Amazon release their earnings reports this week, the market will focus on whether AI capital expenditures can be converted into actual revenue, as well as the sustainability of financing for subsequent investment expansions.JPMorgan believes that the financing relationship between Nvidia and GPU operators may become a channel for credit risk transmission. If operator financing tightens, pressure may spread upstream along the supply chain. The bank maintains a constructive view on the fundamentals of the technology sector, believing that a buying window may appear in early November, but it is still necessary to observe signals such as further market position clearing, corporate earnings realization, and credit spread narrowing.

first_img Yushu Technology reminds of unusual stock price fluctuations, with a rolling price-to-earnings ratio of 465.22 times

The humanoid robot company Yushu Technology (688836.SH) announced that the cumulative price deviation of the company's stock closing price has exceeded 30% over three consecutive trading days, which falls under the category of abnormal stock trading fluctuations. As of October 26, 2026, the company's rolling price-to-earnings ratio is 465.22 times, significantly higher than the average rolling price-to-earnings ratio of 38.54 times in the general equipment manufacturing industry.The announcement pointed out that the humanoid robot industry is still in the early stages of commercialization, with uncertainties in technology maturity, cultivation of downstream market demand, and supporting capabilities in the industrial chain. The transition of physical AI technology from laboratory demonstrations to large-scale implementation in real-world scenarios still faces challenges such as perception accuracy, motion control stability, data accumulation, and hardware-software collaboration. The maturity of the technological path and business model still requires time for validation. If the industry's large-scale commercialization progress does not meet expectations, the company's future revenue expansion and performance release may be adversely affected, posing investment risks of valuation regression.
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