Impact of Xiaomi's Strategic Transformation on Valuation Logic

Xiaomi’s current P/E ratio of 20.25x, P/B ratio of 3.16x, and EV/OCF ratio of 13.94x indicate that the market still gives it a reasonable or slightly conservative traditional tech valuation [0]. However, the DCF multi-scenario model reveals: even with a relatively moderate assumption of 10.5% growth rate and 5.7% EBITDA margin, the enterprise value is only $21, far lower than the current market price of $39.22, which shows that the market has implied higher growth expectations in the valuation. The underlying logic is the explosion of new businesses such as IoT and automotive [0]. In this context, the valuation has shifted from “mobile phone sales × profit per unit” to a combination of “ARPU × growth rate of the three major platforms: mobile phone, IoT, and automotive”. Future growth drivers will rely more on ecological synergy, software services, and autonomous driving platform capabilities.

The background provided by users indicates: SU7 had 88,000 locked orders and YU7 had 240,000 locked orders in 2025, and the IoT business is expected to generate over 135 billion yuan in revenue with the self-developed progress of 3nm SoC, showing that Xiaomi has shifted from “low-price follow” to “high-end independent + ecological platform” strategy. Matching this is the company’s sustained and stable cash flow and ROE of 18.65% [0], indicating that expansion has not significantly eroded profitability. The high-frequency connections and services of the IoT ecosystem (AIoT devices, cloud services, advertising, e-commerce) and the high gross profit margin space of automobiles are redefining its growth curve, making the risk-return profile reflect a “platform-type tech company” rather than a single electronics manufacturer.

Essentially, Xiaomi still maintains the investment主线 of “tech + hardware + platform”: self-developed SoC, operating system, AIoT hardware-software integration, and smart cars. From the financial perspective, its cash flow and low-risk liability characteristics remain unchanged (excellent cash flow, low debt risk) [0]; part of the valuation increase comes from “platform-level capabilities” (including data assets brought by new product lines). Therefore, although the business boundaries have expanded, the core of being a “tech company” is still “driving user experience and long-term ARPU through continuous technological iteration”, but the dimension has expanded from “mobile phone hardware” to two platforms: “Internet of Everything + electric mobility”, enhancing the thickness of its tech growth and moat rather than changing this investment logic.

• The current DCF optimistic scenario is also lower than the market price, indicating that the market’s high growth assumptions for IoT/automotive are very important. If delivery or ecological service monetization fails to meet expectations, the risk of valuation revaluation is high [0].
• Technical indicators show that the stock price is below the 20/50/200-day moving averages, and the short-term trend tends to sideways consolidation. RSI/KDJ indicates oversold but lacks a clear trend [0], so vigilance against emotional retracement is needed.
• Strategic expansion requires a lot of upfront investment (especially in automobiles). If cost control and supply chain management are not in place, cash flow may be compressed.

Xiaomi has shifted from the mobile phone model of “catching up with Apple” to a diversified platform strategy of “IoT + large appliances + automobiles”, which has indeed reshaped its valuation logic: from single hardware profit to composite platform growth pricing. However, its core investment logic as a “tech growth enterprise” (R&D-driven, ecological linkage, long-term ARPU) has not changed, but only extended more growth dimensions. It is necessary to continuously observe the monetization of IoT services, the smoothness of automobile delivery and self-developed chips to judge whether the market will continue to pay for these future values. For further cross-cycle models, horizontal competitor comparisons, or deeper industry data, you can consider enabling the deep research mode to obtain a more comprehensive database and visual analysis.

[0] Jinling API Data