| | --- |
| | title: P2-ETF-CNN-LSTM-ALTERNATIVE-APPROACHES |
| | emoji: 🧠 |
| | colorFrom: green |
| | colorTo: blue |
| | sdk: streamlit |
| | sdk_version: "1.32.0" |
| | python_version: "3.10" |
| | app_file: app.py |
| | pinned: false |
| | --- |
| | |
| | # P2-ETF-CNN-LSTM-ALTERNATIVE-APPROACHES |
| |
|
| | Macro-driven ETF rotation using three augmented CNN-LSTM variants. |
| | Winner selected by **highest raw annualised return** on the out-of-sample test set. |
| |
|
| | --- |
| |
|
| | ## Architecture Overview |
| |
|
| | | Approach | Core Idea | Key Addition | |
| | |---|---|---| |
| | | **1 — Wavelet** | DWT decomposes each macro signal into frequency subbands before the CNN | Separates trend / cycle / noise | |
| | | **2 — Regime-Conditioned** | HMM detects macro regimes; one-hot regime label concatenated into the network | Removes non-stationarity | |
| | | **3 — Multi-Scale Parallel** | Three CNN towers (kernels 3, 7, 21 days) run in parallel before the LSTM | Captures momentum + cycle + trend simultaneously | |
| |
|
| | --- |
| |
|
| | ## ETF Universe |
| |
|
| | | Ticker | Description | |
| | |---|---| |
| | | TLT | 20+ Year Treasury Bond | |
| | | TBT | 20+ Year Treasury Short (2×) | |
| | | VNQ | Real Estate (REIT) | |
| | | SLV | Silver | |
| | | GLD | Gold | |
| | | CASH | 3m T-bill rate (from HF dataset) | |
| |
|
| | Benchmarks (chart only, not traded): **SPY**, **AGG** |
| |
|
| | --- |
| |
|
| | ## Data |
| |
|
| | All data sourced exclusively from: |
| | **`P2SAMAPA/fi-etf-macro-signal-master-data`** (HuggingFace Dataset) |
| | File: `master_data.parquet` |
| |
|
| | No external API calls (no yfinance, no FRED). |
| | The app checks daily whether the prior NYSE trading day's data is present in the dataset. |
| |
|
| | --- |
| |
|
| | ## Project Structure |
| |
|
| | ``` |
| | ├── .github/ |
| | │ └── workflows/ |
| | │ └── sync.yml # Auto-sync GitHub → HF Space on push to main |
| | │ |
| | ├── app.py # Streamlit orchestrator (UI wiring only) |
| | │ |
| | ├── data/ |
| | │ └── loader.py # HF dataset load, freshness check, column validation |
| | │ |
| | ├── models/ |
| | │ ├── base.py # Shared: sequences, splits, scaling, callbacks |
| | │ ├── approach1_wavelet.py # Wavelet CNN-LSTM |
| | │ ├── approach2_regime.py # Regime-Conditioned CNN-LSTM |
| | │ └── approach3_multiscale.py # Multi-Scale Parallel CNN-LSTM |
| | │ |
| | ├── strategy/ |
| | │ └── backtest.py # execute_strategy, metrics, winner selection |
| | │ |
| | ├── signals/ |
| | │ └── conviction.py # Z-score conviction scoring |
| | │ |
| | ├── ui/ |
| | │ ├── components.py # Banner, conviction panel, metrics, audit trail |
| | │ └── charts.py # Plotly equity curve + comparison bar chart |
| | │ |
| | ├── utils/ |
| | │ └── calendar.py # NYSE calendar, next trading day, EST time |
| | │ |
| | ├── requirements.txt |
| | └── README.md |
| | ``` |
| |
|
| | --- |
| |
|
| | ## Secrets Required |
| |
|
| | | Secret | Where | Purpose | |
| | |---|---|---| |
| | | `HF_TOKEN` | GitHub + HF Space | Read HF dataset · Sync HF Space | |
| |
|
| | Set in: |
| | - GitHub: `Settings → Secrets → Actions → New repository secret` |
| | - HF Space: `Settings → Repository secrets` |
| |
|
| | --- |
| |
|
| | ## Deployment |
| |
|
| | Push to `main` → GitHub Actions (`sync.yml`) automatically syncs to HF Space. |
| |
|
| | ### Local development |
| |
|
| | ```bash |
| | pip install -r requirements.txt |
| | export HF_TOKEN=your_token |
| | streamlit run app.py |
| | ``` |
| |
|
| | --- |
| |
|
| | ## Output UI |
| |
|
| | 1. **Data freshness warning** — alerts if prior NYSE trading day data is missing |
| | 2. **Next Trading Day Signal** — date + ETF from the winning approach |
| | 3. **Signal Conviction** — Z-score gauge + per-ETF probability bars |
| | 4. **Performance Metrics** — Annualised Return, Sharpe, Hit Ratio, Max DD |
| | 5. **Approach Comparison Table** — all three approaches side by side |
| | 6. **Equity Curves** — all three approaches + SPY + AGG benchmarks |
| | 7. **Audit Trail** — last 20 trading days for the winning approach |
| |
|
