An Empirical Research On Financial Early Warning Of China’s Information Technology Listed Companies

With the continuous improvement and development of China’s market economy, as well as the impact of economic globalization on China’s growing, the business environment is getting more and more complex. And the competition gets more and more intense, which makes each enterprise needs to face more financial risk. If these risks have not been timely and effective controlled and evolve into a financial crisis, which will be a serious threat to the survival of enterprises. Therefore, the establishment of efficient financial early-warning model has great significance for the development of China’s economy and enterprises.This article summarized the results of previous studies. And based on this, the financial early warning model was improved and optimized from two aspects. Firstly, the model for the IT industry listed companies. The IT industry has a high-risk, high investment, high-yield characteristics, and much different with the traditional industry. To build a financial early warning model for the industry can improve the accuracy and effectiveness of early warning. Secondly, we expanded the selection of relevant indicators, added some non-financial indicators. The financial data has some shortcomings like lagging and limitation, and the financial indicators can not reflect the entire financial crisis, so the addition of non-financial indicators could offer a good complementarity. Based on these two considerations, the paper selected60listed companies of IT industry as the research sample,30ST enterprises and30normal financial enterprises. Sample data comes from the last three years annual report of ST and normal financial listed companies, among that24financial indicators and12non-financial indicators were chosen, two types of financial early warning model were built by the way of empirical research using SPSS statistical software. One of them was a simple model based on financial indicators, and the other one was a jointly built mode of financial indicators and non-financial indicators. After comparative analysis, the conclusion is confirmed that the goodness of fit financial early warning model and the accuracy of the forecast results is improved after the addition of non-financial indicators. In other words, the non-financial indicators could optimize the financial early warning model.