Core Insights - The report presents a multi-dimensional index daily frequency timing framework aimed at optimizing absolute return strategies and stock index futures performance through position timing [3] - The framework is based on a multi-dimensional factor system, including 80 analyst expectation factors, 134 capital flow factors, 43 high-frequency aggregated low-frequency features, and deep learning factors introduced after 2020 [3][12] - The backtesting results show that the long-short strategy achieves an annualized return of 46% with a Sharpe ratio of 2.37, while the long-only strategy achieves an annualized return of 23% [3][12] Factor Analysis - The basic factors include 80 analyst expectation factors and 134 capital flow factors, which are crucial for predicting future returns [12][15] - The report highlights a negative correlation between capital flow factors, particularly outflow-related factors, and the next day's returns, indicating a reversal characteristic overnight [15][16] - The report tests the performance of various analyst expectation factors, with the top-performing factors yielding annualized returns ranging from 10% to over 21% based on different thresholds [27][23] Deep Learning Integration - The deep learning factor prediction framework targets the next day's returns using both daily and minute data to capture overnight signals, employing an improved Mean Absolute Directional Loss (MADL) function for directional judgment [10][54] - The MADL function is preferred over Mean Squared Error (MSE) as it focuses on optimizing the correctness of directional predictions rather than numerical accuracy, aligning with practical trading principles [54][57] Timing and Stock Selection Strategy - The framework validates the feasibility and effectiveness of position timing, achieving a win rate of 54% for both long and short positions [12] - The strategy further integrates stock selection models to enhance the return structure, demonstrating a robust solution for quantitative investment [11][3] High-Frequency Data Utilization - The report constructs 43 high-frequency factors to capture market sentiment and risk, including intraday volatility and trading volume patterns [36][42] - The high-frequency factors are aggregated to create suitable features for daily extraction, ensuring high quality and low noise [36][37]

Geopolitical Risks - The intensifying competition between the US and China, particularly regarding Taiwan and South China Sea tensions, may trigger a phase of impulse-driven gold price increases by 2025 [1] - The global election year effect, with elections in 65 countries including the US, India, and Brazil, could lead to policy uncertainties, especially if extreme outcomes arise in the US elections, thereby elevating risk aversion [1] - The risk of uncontrolled AI governance may lead to market panic, reinforcing gold's status as a "safe haven" in the digital age [1] Central Bank Gold Purchases - Central banks globally have purchased over 1000 tons of gold for three consecutive years, with emerging market central banks (e.g., China, India, Turkey) expected to continue leading purchases in 2025 [3] - The People's Bank of China increased its gold reserves to 2298 tons by June 2025, marking eight consecutive months of accumulation, although the pace may slow due to high gold prices [3] - An increase of 100 tons in central bank gold purchases could reduce gold price volatility by 0.8% per quarter, but the "buy the expectation, sell the fact" effect should be monitored [3] Federal Reserve Monetary Policy - Key Federal Reserve meetings in 2025, particularly in March, June, September, and December, will be crucial for interest rate decisions and economic forecasts [3] - If inflation falls to the 2% target, a rate cut may occur in June, potentially driving gold prices up by 5-8% [3] - A 1% increase in the divergence of the dot plot could lead to a 1.2% increase in gold price volatility [3] Quarterly Price Forecasts - Q1 2025: Gold price expected to range between $2050-$2150, driven by US-China tensions and the US election primaries [5] - Q2 2025: Price forecasted at $2100-$2200, influenced by ongoing Russia-Ukraine conflict and Middle East tensions, with potential Fed rate cut signals [5] - Q3 2025: Anticipated price range of $2150-$2250 as global election results stabilize risk appetite and the Fed confirms a rate cut [5] - Q4 2025: Price expected between $2100-$2200 due to AI governance controversies and Fed adjustments to rate cuts [5]