| Abstract: |
| The commodity market contains abundant information from macro economy. Measuring the macroeconomic information fows in the fuctuations of commodity priceindexes are conducive to monitoring the market and forecasting its growing trend.In this paper, a high-order hidden Markov chain (HOHMC)is used to measurehidden macroeconomic information fows in the (hinese commodity futures index.where the time frame is from June 25, 2004 to January 31, 2023. Some interest-ing empirical results are achieved for investors and regulators as follows. First, themacroeconomic hidden information fows can be categorized into high volatility regime and low volatility regime. During a high volatility regime, the Chinese Commodity Index exhibits increased volatility and frequent jumps in behavior. Inthe panic phase of this regime, the market is relatively efcient; during its bub.ble phase, it becomes relatively inefcient. Second, different commodity marketshave heterogeneous data generation mechanisms, with industrial, metal, and energymarkets being more sensitive to exogenous shocks compared to the less sensitiveagricultural market. Third, the macroeconomic hidden information fows that driveChinese commodity market data generation mechanism serve as an explicit leadingindicator for macroeconomic variables. |
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