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      影视文化产业作为“国家名片”，是彰显文化自信、建设文化强国的重要载体。行业的发展不仅与宏观环境联系密切，更与国家民族的精神内涵相关联。2020 年初新冠疫情突然爆发，对我国经济发展造成了巨大的影响，文娱产业指数呈现大幅下降的趋势，多数影视公司的经营业绩也开始下滑。此外，近些年我国影视行业也陷入了发展困局，大量外部资本的注入使行业产能过剩、严重泡沫化，加之行业内各种偷税漏税问题以及网络影视的强势发展对传统影视业的冲击，致使影视寒冬迅速在业内蔓延；同时，大量影视企业过度依赖明星效应，追求流量至上的乱象也使影视行业频频暴雷。这些不确定性的因素都会给影视企业造成严重的财务风险，对公司的稳定发展形成致命的打击，同时也严重影响整个影视文化产业的健康、持续发展，所以影视企业管理者更应加大对财务风险预警的重视程度。

      基于目前依然严峻的宏观环境，本文选择唐德影视公司作为研究对象，并结 合影视业特点对其财务风险预警问题进行重点探讨，采用熵值法和功效系数法 相结合的方式对公司进行财务风险预警研究。与传统预警方法相比，熵值法的赋权方式更加客观、操作过程简单易懂，使得研究结果更具可靠性，所以本文利用熵值法构建了财务风险预警模型。首先，分别从筹资、投资、经营、分配四个角度对唐德影视的财务风险进行识别，然后选取公司 2017 至 2021 年的财务指标作 为研究数据，利用熵值法和功效系数法构建财务风险预警模型，并以国资委发布 的《企业绩效评价标准值》为参照，对公司在生产经营活动中面临的财务风险进 行评估。计算结果表明，唐德影视近些年的财务风险预警等级处于较高的状态， 需要引起公司管理人员的高度警惕。最后，在依据财务风险预警模型的计算结果， 针对不同的风险类型提出了相应的防范和改进措施，如优化筹资结构、加速存货 变现速度等，以此来促进影视行业健康、稳定以及持续性的发展，并为其他公司 进行财务风险预警提供参考和借鉴。

     The cinema and television business serves as the country's "name card" and is crucial in fostering cultural confidence and a vibrant national identity. The growth of the industry is intimately related to both the macroenvironment and the spiritual underpinnings of the country.The abrupt outbreak of COVID-19 in the start of 2020 had a significant impact on China's economic progress. The cultural and entertainment industry index has showed a major negative trend, and most film and television firms' operating performance has begun to deteriorate.In addition, in recent years, China's film and television industry has also fallen into a development dilemma. The injection of a large amount of external capital has led to overcapacity and serious foam in the industry.Furthermore, several tax evasion issues in the sector, as well as the influence of the rapid development of online film and television on the traditional film and television industry, have caused the film and television winter to spread swiftly.At the same time, a large number of film and television companies excessively rely on the star effect, and the chaos of pursuing traffic supremacy has also caused frequent thunderstorms in the film and television industry.These unknown aspects can cause major financial risks for film and television enterprises, which can be fatal to the company's stable development and also have a negative impact on the overall health and sustainability of the film and television cultural industry. As a result, executives in the film and television industries should focus more on financial risk management.

        This article chooses Tangde Film and Television Company as the research subject based on the macroeconomic conditions, focuses on the company's financial risk early warning in relation to the characteristics of the film and television industry, and uses a combination of the entropy method and the efficiency coefficient method to conduct financial risk early warning research for the company. The entropy method is more objective in terms of weighing techniques than conventional early warning techniques, and the operation process is clear-cut and easy to follow, increasing the validity of the research findings. As a result, the entropy method is used in this study to create a financial risk early warning model. Determine the financial dangers that Tangde Film and Television is facing first from the angles of funding, investment, operation, and distribution. Then, choose the company's financial indicators from 2017 to 2021 as research data, create a financial risk early warning model using the entropy method and efficiency coefficient method, and use the SASAC's "Enterprise Performance Evaluation Standard Values" as a guide to assess the financial risks the company faces during production and operation activities. The calculations' findings indicate that Tangde Film and Television's financial risk early warning level in recent years has been at a high level, necessitating a high level of vigilance on the part of the company's management. In order to support the healthy, stable, and sustainable development of the film and television industry and to serve as a model for other businesses conducting financial risk early warning, prevention and improvement measures are finally suggested based on the calculation results of the financial risk early warning model for various risk types. These measures include accelerating the speed of inventory liquidation and optimizing the financing structure.