Silver Macro + Industrial Model白银宏观 + 工业模型
Silver = high-beta gold + an industrial kicker. Combine gold's monetary legs with copper-led growth, gold/silver-ratio mean-reversion and a positioning guard — this beats the trend swap and buy-&-hold on Sharpe and drawdown.白银 = 高贝塔黄金 + 工业属性。将黄金的货币腿与铜主导的增长、金银比均值回归及持仓护栏结合——在夏普与回撤上跑赢趋势开关与买入持有。
As of截至 Jul 16, 2026 · Silver白银 · current income当前票息 ~2.49%
⚗ Experimental — display-only (Phase-0)实验性 — 仅展示（Phase-0）
A drawdown / Sharpe engine — not a yield-maximizer回撤 / 夏普引擎 — 并非收益最大化工具
Recommended allocation right now当前建议仓位
Silver白银33%
T-bills短期国债67%
Silver白银
T-bills短期国债 (cash carry现金套息)
Last change上次调整: 2026-06-25 — 66% → 33%
Current income blends the risk-asset yield (when invested) with the cash-leg yield (when de-risked).当前票息为风险资产收益（在场时）与现金腿收益（降险时）的加权。
Monetary + growth headwind货币 + 增长逆风 score评分 (0–100)
65
Stress — de-risk压力 — 降险
Higher = more risk-off. The score sets the risk-asset weight via graded bands (below), with a 5-day debounce to cut whipsaw.分数越高越偏避险。该分数通过分级区间（见下）设定风险资产权重，并有 5 日缓冲以抑制频繁换仓。
What is driving the score分数由什么驱动
Each leg adds points to the 0–100 score (renormalised weighted mean). The bar is the current score, split by contribution.各分项为 0–100 分数贡献分值（归一化加权平均）。下方进度条为当前分数，按贡献拆分。
Filled width = the score out of 100. Empty = headroom (calm).填充宽度 = 满分100中的得分。空白 = 余量（平静）。
| Signal leg信号分项 | Intensity强度 | Weight权重 | Pub lag发布滞后 | Points贡献分 |
|---|
| Trend (TSMOM)趋势（时间序列动量） |
67/100 |
1.0 |
0d |
13.1 |
| Real yields rising实际收益率上行 |
79/100 |
0.8 |
1d |
12.3 |
| Broad dollar rising广义美元走强 |
70/100 |
0.7 |
2d |
9.6 |
| Inflation expectations falling通胀预期下行 |
86/100 |
0.4 |
1d |
6.7 |
| Copper downtrend (weak growth)铜下行趋势（增长走弱） |
0/100 |
0.7 |
1d |
0.0 |
| Gold/silver ratio low (silver rich)金银比偏低（白银偏贵） |
88/100 |
0.5 |
1d |
8.6 |
| Speculators over-long投机过度做多 |
58/100 |
0.5 |
7d |
5.7 |
| Realized-volatility guard已实现波动率护栏 |
88/100 |
0.5 |
1d |
8.7 |
| Composite score综合分数 | | | | 65 |
The strategy in action · benchmark with the model on top策略实战 · 基准叠加模型
Green = fully invested, amber = trimmed, clear = defensive. ▲/▼ mark every allocation change. The strategy equity (blue) is rescaled onto the benchmark axis so you can read protection vs participation directly.绿色 = 满仓，琥珀 = 减仓，空白 = 防守。▲/▼ 标注每次仓位变动。策略净值（蓝）已缩放至基准轴，可直接对比保护与参与度。
Growth of $1 (log) — vs buy & hold1美元增长（对数）— 对比买入持有
Underwater (drawdown) — vs buy & hold水下回撤 — 对比买入持有
Honest framing: this does NOT reliably beat buy-and-hold on CAGR — sitting in the cash leg through stress gives up some carry. The edge is the higher Sharpe and the much shallower max drawdown: it times the LEFT TAIL that destroys the yield (the recession/credit/rate shock), not the yield itself.诚实说明：本策略在年化收益上并不稳定跑赢买入持有 —— 压力期退守现金腿会让出部分套息。优势在于更高的夏普与明显更浅的最大回撤：它择时的是吞噬收益的左尾（衰退/信用/利率冲击），而非收益本身。
Backtest scorecard · 25.9 years vs buy & hold回测记分卡 · 25.9 年对比买入持有
CAGR
7.99%
buy & hold买入持有 9.82%
Sharpe
0.5
buy & hold买入持有 0.45
Max drawdown最大回撤
-54.6%
buy & hold买入持有 -75.8%
Time invested在场时间
94.8%
1.81x turnover/yr换手/年
Sortino
0.56
buy & hold买入持有 0.56
Income yield now当前票息
2.49%
blended risk-asset + cash风险资产 + 现金加权
Deflated Sharpe贬值夏普
0.8424
multiple-testing haircut多重检验折减 · n=8
The rule-book · risk band → weight规则手册 · 风险区间 → 权重
| Risk band风险区间 | Score分数 | Silver白银 weight权重 | T-bills短期国债 |
|---|
| Calm — fully invested平静 — 满仓 |
< 25 |
100% |
0% |
| Watch — trim关注 — 减仓 |
25–50 |
66% |
34% |
| Stress — de-risk压力 — 降险 ◀ |
50–75 |
33% |
67% |
| Defensive — all cash防守 — 全现金 |
≥ 75 |
0% |
100% |
A new band must hold 5 trading days before it takes effect (hysteresis kills whipsaw). Bands and leg weights are pre-registered, not tuned per result.新区间须连续保持 5 个交易日才生效（滞后机制抑制频繁换仓）。区间与分项权重为预先登记，非按结果调参。
Independent bear episodes · the true sample size独立熊市事件 · 真实样本量
| Peak峰值 | Trough谷底 | Buy & hold drawdown买入持有回撤 |
|---|
| 2004-04-06 | 2004-05-11 | -32.8% |
| 2006-05-11 | 2006-06-13 | -35.4% |
| 2008-03-05 | 2008-10-28 | -57.5% |
| 2011-04-29 | 2020-03-18 | -75.8% |
| 2026-01-26 | 2026-07-16 | -51.7% (ongoing进行中) |
A handful of independent ≥20% bears govern a get-out / get-back-in switch — effective-N, not the day count, bounds confidence. Full leave-one-crisis-out validation is a fast-follow.少数几次独立的 ≥20% 熊市决定一次离场/再入场切换 — 决定置信度的是有效样本量，而非天数。完整的留一危机验证为后续跟进。
Commodity, display-only / experimental. Benchmark = Silver (SI=F) continuous front-month total-return close (2000→); the de-risked sleeve earns the T-bill yield. Monetary (real yields/USD/breakevens) + industrial (copper trend, gold/silver ratio) + positioning + vol. Its edge over the trend swap is the whole point of modelling silver specifically. Macro legs activate once their FRED series begin (real yields/breakevens 2003, broad USD 2006). Full Phase-0 is a fast-follow.商品，仅展示 / 实验性。基准 = 白银 (SI=F)连续近月总回报收盘价（2000→）；降险时空仓腿赚取短期国债收益。货币（实际收益率/美元/通胀预期）+ 工业（铜趋势、金银比）+ 持仓 + 波动。其相对趋势开关的优势正是为白银专门建模的意义。 宏观腿在其 FRED 序列开始后才激活（实际收益率/通胀预期 2003 年、广义美元 2006 年）。完整 Phase-0 为后续跟进。