商品指数系列报告（四）：物价趋势跟踪商品指数多因子择时策略

Report Industry Investment Rating - Not provided Core Viewpoints of the Report - The report systematically reviews the cycle characteristics and causes of the commodity bull market, indicating that the core driving force for the excellent performance of commodities during the economic prosperity phase comes from the expansion of real - economy demand and rising inflation [3]. - The commodity index timing strategy 2.0 has limitations such as high noise in trading signals during deflation and insufficient capture of phased rebound markets. The newly developed multi - factor timing strategy significantly improves sensitivity to rebound markets and capture efficiency, with optimized signal quality and better overall timing results [3]. Summary by Relevant Catalogs "Commodity Bull Market" Cycle Review and Cause Analysis - "Commodity Bull Market" Cause Analysis: During economic growth, the demand of major commodity - consuming industries like manufacturing, construction, and transportation increases, directly promoting the expansion of the commodity market and causing price increases. Commodities are effective anti - inflation investment tools during economic prosperity due to their high correlation with inflation [6]. - Commodity Market Performance in the Economic Cycle: Using the macro - economic prosperity index year - on - year data and CPI year - on - year data as indicators for economic growth and inflation growth, it is confirmed that the commodity market has the best returns during the prosperity phase [7]. Limitation Analysis and Timing Factor Formulation Method - Review of Commodity Index Strategy 1.0 and 2.0: Strategy 1.0's inflation index based on PMI ex - factory prices leads official PPI data by about 10 days but lags behind the commodity futures index by about a month. Strategy 2.0 optimizes Strategy 1.0, and the monthly average of the commodity futures index is highly consistent with the inflation index, providing a leading signal for inflation paths and leading official PPI data by about 40 days in PPI trend information acquisition [10][11]. - Limitations of Commodity Index Strategy 2.0: In the deflation phase, the trading signals generated by the strategy are noisy, and the ability to capture phased rebound markets is limited, resulting in missed profit opportunities [14]. - Formulation Method of Commodity Index Multi - factor Timing Strategy Factors: - Commodity Futures Index Trend Timing Factor: Use the commodity index itself as the price - level factor and combine it with economic index timing [15]. - Supply Timing Factor: Use the PMI new order index and PMI production index to represent the supply and demand sides, and combine them with PPI trend prediction [18]. - Demand Timing Factor: Similar to the supply timing factor, it combines relevant indicators and PPI trend prediction [20]. - Supply - Demand Composite Timing Factor: Based on the weights in the manufacturing PMI index, sum the weighted new order index and production index and normalize them with a total weight of 55% [21]. - Predicted Supply Timing Factor: Select 14 high - frequency supply - side indicators to fit the PMI production index, with monthly rolling fitting and historical back - testing starting from July 2021 [23]. - Predicted Demand Timing Factor: Select 16 high - frequency demand - side indicators to fit the PMI new order index, with monthly rolling fitting and historical back - testing starting from July 2021 [25]. - Predicted Supply - Demand Composite Timing Factor: Weight and sum the predicted supply and demand timing factors and then normalize them with a total weight of 55% [27]. Commodity Index Multi - factor Timing Strategy Net Value Back - testing - Combine the 7 timing factors introduced above with the timing factor in the previous report to construct 8 equal - weighted scoring factors. When the total score of the 8 factors exceeds 4 points, a long signal for the commodity index is triggered. The multi - factor timing strategy shows obvious timing effects on the commodity index, and its timing effect is more sensitive than that of the commodity index timing strategy 2.0, effectively tracking phased rebound markets even in a downward price cycle [29]. Summary - The research first reviews the previous research conclusions that the commodity market performs well during economic prosperity and has developed commodity index timing strategies 1.0 and 2.0. To address the limitations of Strategy 2.0, 7 new timing factors are constructed and combined with the original factor to form an 8 - factor equal - weighted scoring system. The multi - factor timing strategy significantly improves the ability to identify phased rebounds in the downward cycle, with better signal sensitivity and stability [31].