Wind Alice Inflation Bond Rotation Strategy
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Please follow https://skillhub.cn/install/skillhub.md to install @org-r64ixwde/alice-inflation-bond-strategy into your AI assistant.
About this skill
Problem
Inflation trading is not only about the latest CPI/PPI print. Turning points such as continuous marginal improvement, a move from negative to positive, and sustained positive growth often carry different implications for rates and duration. This skill turns that judgment into a repeatable workflow: identify the current inflation scenario, then generate bond allocation advice under either a Long/Flat or duration-rotation mode, with backtesting support.
How It Works
It calls the Wind Alice Agent through alice-inflation-bond-strategy using a natural-language request and returns structured strategy output. The main steps are:
- Four inflation signals: CPI YoY continuous marginal improvement, CPI YoY turning from negative to positive, PPI MoM continuous positive growth, and PPI YoY turning from negative to positive.
- Strategy modes: the Long/Flat mode switches to a money-market fund when inflation is bearish for bonds and fully invests in bonds when inflation is supportive; the duration-rotation mode stays fully invested and adjusts exposure across
5-year,7-year, and10-yeargovernment bond indices. - Risk constraints: supports parameterized caps such as volatility, duration, and maximum drawdown tolerance.
- Backtesting: reports NAV, excess return, annualized return, volatility, Sharpe ratio, and maximum drawdown.
The user-facing result should come from agentResult.value in CLI stdout; full report files may be downloaded silently to a local directory, but their contents should not be pasted directly to the user.
Boundaries
It is useful for inflation signal tracking, monthly rebalancing decisions, duration allocation, and portfolio construction assistance. The output is a strategy report and allocation recommendation, not automatic execution or a live trading account. Before use, a usable Wind Alice API key and sufficient data coverage for the requested backtest window are needed; when data is limited, the affected modules should state that explicitly.
Use Cases
- Fixed-income researchers determine the monthly inflation scenario from CPI/PPI and generate bond rebalancing signals and allocation advice.
- Rates strategy teams compare Long/Flat and duration-rotation backtests before deciding the monthly bond posture.
- Portfolio managers set maximum drawdown and volatility caps to solve optimal weights across 5, 7, and 10 year bonds.
- Research assistants review five-year NAV, excess return, maximum drawdown, and signal trigger records.
Best For
- Fixed-income researchers: convert CPI/PPI turning points into monthly bond signals and allocation plans.
- Rates strategists: compare Long/Flat versus duration-rotation backtests for monthly portfolio posture.
- Portfolio managers: derive 5/7/10-year bond weights under drawdown and volatility caps.
- Research assistants: review NAV, excess return, and signal records to support investment decisions.
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