Strategy #0000000062 · Global macro and cross-asset signals
Fundamental macro momentum and cross-asset exposure
Estimate macro-state trend directions, then map them through asset sensitivities into a capped illustrative exposure.
Macro momentum maps trends in state variables—such as growth, trade, monetary policy or risk appetite—through each asset’s sensitivities into cross-asset exposures. Implementation requires point-in-time data vintages, release calendars, mixed frequencies and time-varying asset sensitivities.
Release delays, revisions and estimated sensitivities affect the signal; the score is conditional exposure, not a macro forecast.
Three ways in
Understand the story. Then inspect the risk.
Start with a familiar situation, check the payoff, then test how the numbers change.
The idea · in two minutes
What direction and exposure result when growth, trade, policy and risk trends meet asset sensitivities?
Kai tracks standardised trends in four macro states and records an asset’s directional sensitivity to each variable.
The simulator sums trend times sensitivity and caps exposure using a scale parameter; the future asset return remains a separate user assumption.
A real signal must not backfill history with revised data. It also needs policy-turning points, release timing, costs, FX and cross-asset correlations.
- Composite macro score assumptionChange four standardised macro trends, asset sensitivities, exposure scale and assumed return to inspect the composite score and position scenario.
- Capped exposure scenarioManual assumptions only; no macro series, point-in-time vintages or estimated asset sensitivities are loaded, and this is not a forecast or backtest.
- Assumed return after costsIllustrative expiry outcome.
Illustrative research examples only. They are not live signals or a recommendation.
The mechanics · payoff and exposure
Score_i=\sum_j Trend_j\,Sensitivity_{ij},\quad w_i=\operatorname{clip}(Score_i/s,-1,1),\quad R_i^{scenario}=w_iR_i^{assumed}-Cost|w_i|
Trend_j is a standardised macro-state trend; Sensitivity_ij is asset i’s directional sensitivity; s scales exposure.
Greeks: the directional intuition
- 即時數據版本
- Measures sensitivity to implied volatility.
- 敏感度不穩
- Measures sensitivity to implied volatility.
- 共同尾部風險
- Measures sensitivity to implied volatility.
Score_i=\sum_j Trend_j\,Sensitivity_{ij},\quad w_i=\operatorname{clip}(Score_i/s,-1,1),\quad R_i^{scenario}=w_iR_i^{assumed}-Cost|w_i|
Practical context · published observations
Fundamental macro momentum and cross-asset exposure: read the record with its caveats.
The chart uses the published figures or explicitly labelled study inputs below. A historical index or model replay is not the same as an investor’s realised account return.
純手動假設；不載入宏觀時間序列、即時資料版本或資產估計值，也不構成預測或回測。 Source ↗ · Methodology ↗
Change assumptions and inspect the scenario
Inputs illustrate the strategy mechanics; they are not live quotes, forecasts or investment advice.
Variants · same family, different risk levers
Related methods still carry different exposures and failure modes.
Compare the input, position and assumptions that can fail.
| Related strategy | Relationship | What changes | New cost or risk |
|---|---|---|---|
| Economic-momentum currencies | Cross-country macro spread | Trades currencies on relative economic momentum. | Revisions, rate differentials and hedge cost. |
| Business-cycle currency exposure | Output gap | Maps cycle differences into currency positions. | Cycle turning points and estimation error. |
| State-conditioned commodity momentum | Macro regime filter | Scales commodity trend with stress or policy uncertainty. | Regime definition may be overfit. |
Manual assumptions only; no macro series, point-in-time vintages or estimated asset sensitivities are loaded, and this is not a forecast or backtest.
Read beyond the summary
References
Primary sources and research used to describe the strategy and its limits.