System Dynamics Modeling to Forecast Economic and Financial Market Indicators Using Interrelationship of Shocks Among Global Financial Markets

Objective: In today’s interconnected global economy, changes in one market can have ripple effects across related markets, making it essential for economic and financial policymakers and experts to accurately predict these mutual impacts. Various methods have been developed to forecast the impact and mutual impressions of financial markets. In this study, a generic framework is proposed for forecasting economic and financial market indicators using the interrelationship of shocks among global financial markets and a system dynamic approach. Methods: To demonstrate the stages of the proposed generic framework and system dynamics modeling, as an example, the study forecasts the Iranian economic and the Tehran Stock Exchange indicators using their interactions with eleven major global financial markets, including London, Tokyo, Shanghai, Frankfurt, Paris, Milan, SIX Swiss, Istanbul, Korea, Bombay Stock Exchanges, and Dubai Financial Market. The New York Stock Exchange index return is used as a stimulant or driver for the other stock exchanges in the model.Results: The results indicate that the proposed forecasting model successfully predicted the Iranian economic and the Tehran Stock Exchange indicators. Furthermore, the study finds that while Iranian exports are sensitive to global financial markets, the sensitivity of imports and production returns to global financial markets is low. Conclusions: The proposed generic framework and system dynamics modeling can provide valuable insights for predicting different economies using their interactions with the global economy and finances.