Abstract

With the steady progress of China’s opening-up policy, how to avoid the financial risks brought by opening-up is a valuable research topic at present while promoting economic development. As an innovative business model connecting the real economy and the virtual economy, the Internet of Things (IoT) finance provides standardized technical support for the expansion of trade and finance. In financial data analysis, deep learning (DL) has become an important means to predict financial market movements, process text information and improve trading strategies. Analysis is conducted on the influence of trade and financial opening on the volatility of real exchange rate. Through the empirical test of panel data of 45 major countries in the world, the pooled ordinary least square (OLS) method and instrumental variable method are used to evaluate the influence of trade and financial opening of sample countries on the volatility of real exchange rate. The main conclusions are that trade openness is negatively correlated with the volatility of real exchange rate, and financial openness is positively correlated with the volatility of real exchange rate. A certain reference is provided for reducing the fluctuation of real exchange rate in the process of opening to the world.

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