Model Research on the Accuracy of Enterprise Value Prediction Based on Machine Learning Algorithm Optimization

This paper aims to study the improvement of enterprise value prediction accuracy based on machine learning algorithm optimization, and proposes a model of enterprise value prediction combined with Monte Carlo simulation. First, the application of machine learning algorithms in enterprise value prediction is discussed in depth, especially for data complexity and uncertainty problems, a method combined with Monte Carlo simulation is proposed to improve prediction accuracy. Secondly, an enterprise value prediction system is designed, which includes modules such as data preprocessing, feature selection, model training and optimization. This paper uses a variety of machine learning algorithms for training, and generates many random scenarios through Monte Carlo simulation to ensure that the model can cope with the uncertainty brought by market fluctuations. Through model simulation, this paper compares the prediction results of different algorithms and conducts precise data analysis in combination with actual enterprise data. Experimental results show that the optimized machine learning algorithm has high prediction accuracy under various market conditions and can effectively improve the performance of the enterprise value prediction system.