招标股份股价回调，业绩亏损与市场情绪成主因

Company Overview - The recent stock price of Zhaobiao Co., Ltd. (301136.SZ) has experienced a pullback against a backdrop of favorable policies, primarily due to performance losses, market sentiment, and technical factors [1] - As of February 13, 2026, the stock price closed at 18.32 yuan, with a 7-day decline of 8.26% and a volatility of 16.37% [2] - The company’s earnings forecast released on January 30 indicates an expected net profit loss of 6.3 million to 12.6 million yuan for 2025, attributed to a decrease in business volume and extended accounts receivable collection periods, leading to provisions for bad debts and goodwill impairment [3] Industry Policy - On February 11, the National Development and Reform Commission and eight other departments issued guidelines to accelerate the application of artificial intelligence in the bidding and tendering sector, which activated the bidding concept sector on that day [4] - Despite the positive policy direction, there are concerns regarding the effectiveness of policy implementation and the company's profitability, leading some investors to reduce their holdings at higher prices [4] Market Dynamics - Internal data shows that after reaching a high of 20.60 yuan on February 11, the stock approached the upper Bollinger Band, indicating short-term overbought pressure [5] - The KDJ indicator's J line fell from 41.97 to 34.81, and the MACD histogram narrowed, suggesting a weakening buying momentum [5] - During the same period, the A-share artificial intelligence sector saw a 7-day increase of 3.34%, but with increased volatility, leading to profit-taking in some AI concept stocks, which affected market sentiment [6] Future Outlook - Despite the short-term pullback, the AI policy for bidding and tendering clearly requires full coverage in key scenarios across certain provinces by the end of 2026, which may create a demand for technological upgrades in the company's bidding services [7] - Additionally, the "AI+" initiative focusing on investment and data optimization by state-owned enterprises may indirectly benefit the bidding industry chain [7]