Core Insights - The report focuses on cross-asset timing strategies for interest rates, systematically backtesting various assets (including stock indices, commodities, and bonds) to identify performance under different market conditions [1]. Group 1: Cross-Asset Rotation Effects - The "stock-bond seesaw" effect arises from shifts in risk appetite, where strong economic expectations lead to capital flowing into equity markets, putting pressure on bond prices and raising yields [2][14]. - The relationship between commodities and bonds is closely tied to inflation expectations, with rising commodity prices typically leading to higher inflation and interest rates, which suppress bond valuations [2][14]. Group 2: Timing Strategies in Commodity and Equity Markets - In equity markets, strategies focused on volatility structures yield higher excess returns compared to trend-based moving average strategies, particularly in high-volatility environments [3]. - For commodities, timing strategies exhibit high odds and low win rates, aligning with the trend-driven nature of commodity trading. Multi-signal strategies outperform in various market conditions due to their adaptability [3][51]. Group 3: Cross-Asset Timing Strategies - The report employs a "cross-validation signal triggering method" for each asset, enhancing the robustness of cross-asset timing strategies. The "look at stocks, trade bonds" and "look at commodities, trade bonds" approaches aim to mitigate drawdowns while maintaining excess returns [4][86]. Group 4: Future Optimization Outlook - A dynamic weighting mechanism is proposed to adjust the importance of different market signals based on macroeconomic conditions, enhancing the adaptability of strategies over time [5]. - The report suggests exploring pair trading strategies in the foreign exchange market to provide additional support for cross-asset trading logic [5].