---
tags:
- ml-intern
---
# FinJEPA: Financial Joint-Embedding Predictive Architecture

FinJEPA is a JEPA-based world model for portfolio optimization over a **separated action space** consisting of:
- **Portfolio weights** (continuous, simplex-constrained)
- **Trading signals** (discrete: long/short/flat per asset)
- **Hedging signal** (binary: on/off)

## Architecture (SOTA Blend)

| Component | Source | Key Innovation |
|-----------|--------|----------------|
| Time Series Encoder | TS-JEPA (Sennadir 2025) | 1D-CNN patch tokenizer + Transformer |
| Action Conditioning | JEPA-WMs (Terver 2025) | AdaLN + RoPE in predictor |
| Collapse Prevention | EB-JEPA (Terver 2026) | SIGReg + Inverse Dynamics Model |
| Multi-step Rollout | EB-JEPA | K-step autoregressive training |
| Planner | JEPA-WMs + EB-JEPA | CEM L2 cost / MPPI cumulative cost in latent space |
| TD Branch | TD-JEPA (Bagatella 2025) | Optional separate task encoder for zero-shot RL |

## Model

```
Financial Time Series (T, F)
    │
    ▼
[TimeSeriesTokenizer] ── 1D-CNN patches + position encoding
    │
    ├───► [Context Encoder] (student)
    │          │
    │          ▼
    │     [Predictor] ◄─── Action embedding (weights + signals)
    │     (AdaLN + RoPE)       │
    │          │               │
    │          ▼               ▼
    │     Predicted target  [ActionEmbedder]
    │     embeddings           ├── weights (continuous)
    │                            ├── signals (discrete)
    │                            └── hedge (binary)
    │
    └───► [Target Encoder] (teacher, EMA frozen)
              │
              ▼
         Ground truth target embeddings
```

## Usage

```bash
python finjepa/run_training_fast.py
```

Full training on real data:
```bash
python finjepa/train.py --data_source hf \
  --dataset_name paperswithbacktest/Stocks-Daily-Price \
  --n_assets 5 --batch_size 128 --epochs 50 --push_to_hub
```

## References

1. TS-JEPA — Sennadir et al. (2025). arxiv:2509.25449
2. JEPA-WMs — Terver et al. (2025). arxiv:2512.24497
3. EB-JEPA — Terver et al. (2026). arxiv:2602.03604
4. V-JEPA 2 — Assran et al. (2025). arxiv:2506.09985
5. TD-JEPA — Bagatella et al. (2025). arxiv:2510.00739

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