In order to explore the impact of the Internet of Things technology on economic market fluctuations and the analysis effect of the Internet of Things technology on economic market fluctuations, this paper uses the Internet of Things algorithm to improve the economic fluctuation model. Moreover, this paper uses the Internet of Things algorithm to locate economic transactions and performs data processing to optimize the intelligent network system to improve the operating effect of the economic system. In addition, this paper improves the sensor node algorithm and proposes to use the weighted value of network node density to balance the positioning problem caused by the unbalanced distribution of network nodes in the detection area. Finally, this paper analyzes the market economy volatility model through the Internet of Things technology, combined with simulation experiments to explore the application of the Internet of Things technology in the economic market volatility model. Through experimental research, it can be known that economic market fluctuation models based on Internet of Things technology can play an important role in market economic analysis.

Under the macro background of severe deterioration of air quality, rapid development of science and technology and support of national policies, new energy vehicles have great potential for development, but the characteristics of large investment and unstable income in the early stage have made new energy automobile enterprises face high financial risks. This paper uses case analysis method, BYD Co., Ltd. as the research object, and builds a financial early warning model based on binomial logistic regression to warn BYD financial risks. It aims to provide effective advice for BYD and the new energy auto industry to control financial risks. The paper concludes that the BYD energy vehicle business has a promising future, but also faces serious financial risks. BYD should take timely measures to reduce financial risks and improve financial conditions.