黄金：资产配置中的长期压舱石

Quantitative Models and Construction Methods - Model Name: Huatai Three-Cycle Model Model Construction Idea: The model analyzes the price movement of COMEX gold settlement prices using three classic economic cycles: Kitchin, Juglar, and Kuznets cycles. It identifies the dominant cycle components influencing gold price trends[17] Model Construction Process: 1. The model decomposes the year-on-year sequence of COMEX gold settlement prices into three cycle components: Kitchin, Juglar, and Kuznets cycles 2. The amplitude of the extracted cycle components is ranked as Kuznets > Juglar > Kitchin 3. The current positions of the Kuznets and Juglar cycles are analyzed to predict future gold price trends[17][19] Model Evaluation: The model highlights that gold prices are more influenced by longer-term cycles (Kuznets and Juglar) compared to shorter-term cycles (Kitchin), providing insights into the strong cyclical positioning of gold in the current market[17] Model Backtesting Results - Huatai Three-Cycle Model: The model indicates that the Kuznets cycle is near its peak, and the Juglar cycle is in an upward phase, suggesting that gold prices are likely to remain strong in the near term[17][19] Quantitative Factors and Construction Methods - Factor Name: Gold as a Portfolio Stabilizer Factor Construction Idea: Gold is evaluated as a low-correlation asset with high long-term returns, making it a potential stabilizer in diversified investment portfolios[3][21] Factor Construction Process: 1. Historical performance of gold is compared with other major asset classes (e.g., equities, bonds, commodities) over different time horizons (1 year, 5 years, 10 years, 20 years) 2. Risk-return metrics such as Sharpe ratio, Calmar ratio, and maximum drawdown are calculated for gold and other assets 3. Correlation analysis is conducted to assess gold's relationship with other asset classes[21][23][24] Factor Evaluation: Gold demonstrates high returns, low volatility, and low correlation with other assets, making it a valuable addition to investment portfolios for risk diversification and return enhancement[21][23] - Factor Name: Gold in Asset Allocation Portfolios Factor Construction Idea: The impact of adding gold to a traditional stock-bond portfolio is analyzed to evaluate its contribution to portfolio performance[3][24] Factor Construction Process: 1. A baseline portfolio is constructed with 60% bonds (ChinaBond New Comprehensive Wealth Index) and 40% stocks (CSI A500 Index) 2. Two new portfolios are created by reallocating 10% of the baseline portfolio to gold (AU9999 spot gold): - Portfolio A: 50% bonds, 40% stocks, 10% gold - Portfolio B: 60% bonds, 30% stocks, 10% gold 3. Monthly rebalancing is applied, and backtesting is conducted over the period from January 3, 2005, to February 19, 2025 4. Risk-return metrics (e.g., annualized return, Sharpe ratio, maximum drawdown) are calculated for all portfolios[24][26] Factor Evaluation: Adding gold improves portfolio Sharpe ratios and reduces volatility, demonstrating its role as a stabilizing asset in diversified portfolios[26] Factor Backtesting Results - Gold as a Portfolio Stabilizer: - Sharpe Ratio: 0.59 (AU9999 spot gold), 0.57 (London spot gold), 0.56 (COMEX gold futures) - Maximum Drawdown: -44.88% (AU9999 spot gold), -44.62% (London spot gold), -44.52% (COMEX gold futures) - Annualized Return: 9.07% (AU9999 spot gold), 9.76% (London spot gold), 9.74% (COMEX gold futures)[23] - Gold in Asset Allocation Portfolios: - Portfolio A: Annualized Return 7.17%, Sharpe Ratio 0.72, Maximum Drawdown -35.47% - Portfolio B: Annualized Return 6.69%, Sharpe Ratio 0.88, Maximum Drawdown -26.86% - Baseline Portfolio: Annualized Return 6.63%, Sharpe Ratio 0.68, Maximum Drawdown -33.36%[26]