Predictive Modeling Of Chinese MNC Currency Risk Based On ARCH-Factor Analysis-GRNN Combined Techniques Illustrated By The Example Of Geli Electronics And Zhongxing Telecom Equipment

As long as currencies have not been unified across the globe and the foreign exchange market has not been perfectly efficient, currency risk management is an eternal topic for multinational corporations. With the increasing turbulence of RMB exchange rate, whether or not effectively managing foreign exchange risk becomes a crucial attributor to Chinese MNC’s profit. Sadly, it’s not uncommon to see news reports on Chinese MNC incurring heavy financial loss due to incompetence to manage exchange risk. The foundation of exchange risk management is for decision makers to realize when and to what extent the company is exposed to exchange risk and how the risk is distributed across different currencies and operating activities. Only then can the decision makers choose appropriate risk control tools. Therefore, the purpose of this paper is to improve Chinese MNC’s precision in exchange risk forecasting by adopting a holistic perspective and using combined techniques.The content of this paper mainly includes:Firstly, induce three major factors influencing corporate exchange risk through summarizing published papers, and then do thorough analysis on the three factors. The three factors are exchange rate fluctuation, corporate exchange risk exposure and corporate exchange risk resistance. Secondly, construct a measurement structure of corporate exchange risk. The structure is made clear, condense and systematic with the help from ARCH model and factor analysis to extract crucial information from data of the case. Thirdly, use specific Chinese MNC Geli Electronics in household electronic appliance industry as a case to build exchange risk forecasting model based on GRNN technique and the measurement structure constructed in prior section. This paper gives the forecasting precision of the ARCH-Factor Analysis-GRNN model and makes comparison between precision of ARCH-Factor Analysis-GRNN model and that of classical VaR model to see if the precision is significantly improved by ARCH-Factor Analysis-GRNN model. Finally, choose another representative Chinese MNC Zhongxing Telecommunication Equipment Corporation as a testing case to check the adaptability of the ARCH-Factor Analysis-GRNN model.The conclusion is the ARCH-Factor Analysis-GRNN combined model based on exchange risk measurement structure proposed in this paper can significantly improve the forecasting precision of Chinese MNC’s exchange risk. The innovation of this paper is:Firstly, construct a more customized and systematic measurement structure of exchange risk for Chinese MNC through summarizing published papers and using linear techniques ARCH model and factor analysis. Secondly, apply GRNN technique to corporate exchange risk forecasting and significantly improve the forecasting precision compared with traditional exchange risk forecasting technique because the advantages of both linear and non-linear techniques have been taken in the proposed model. Finally, make objective judgment on the merits and limitations of the proposed model by testing it in two typical MNC cases and comparing it with VaR forecasting model.