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@@ -13,7 +13,7 @@ datasets:
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  - Tulitula/LensIQ-Synthetic-Portfolio-1000
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  ---
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- # LensIQ — CAPM + CML Portfolio Advisor
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  - **Plot:** x = historical σ (annualized, from monthly covariances), y = CAPM E[r] = rf + β·ERP.
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  - **Efficient mixes:** market/bills with (i) same σ, (ii) same E[r] as your portfolio (weights shown).
@@ -29,7 +29,7 @@ docker build -t lensiq .
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  docker run -p 7860:7860 -e GRADIO_SERVER_NAME=0.0.0.0 lensiq
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  # open http://localhost:7860
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  Create & Upload the Dataset
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- In the app, add tickers (incl. VOO), set amounts, horizon, lookback → Compute.
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  Download the generated CSV from the UI (saved under data/).
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@@ -37,11 +37,8 @@ Create a dataset repo on Hugging Face named Tulitula/LensIQ-Synthetic-Portfolio-
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  the CSV you downloaded
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- the dataset README from below (Section B).
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- swift
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- Kopiér
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- Rediger
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  **B) Dataset README (for `Tulitula/LensIQ-Synthetic-Portfolio-1000`)**
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  ```markdown
@@ -90,9 +87,6 @@ mu_capm: 0.153
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  sigma_hist: 0.209
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  sigma_capm: 0.191
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- markdown
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- Kopiér
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- Rediger
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  ## Files
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  - Tulitula/LensIQ-Synthetic-Portfolio-1000
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  ---
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+ # LensIQ
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  - **Plot:** x = historical σ (annualized, from monthly covariances), y = CAPM E[r] = rf + β·ERP.
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  - **Efficient mixes:** market/bills with (i) same σ, (ii) same E[r] as your portfolio (weights shown).
 
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  docker run -p 7860:7860 -e GRADIO_SERVER_NAME=0.0.0.0 lensiq
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  # open http://localhost:7860
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  Create & Upload the Dataset
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+ In the app, add tickers, set amounts, horizon, lookback → Compute.
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  Download the generated CSV from the UI (saved under data/).
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  the CSV you downloaded
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+ the dataset README from below
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  **B) Dataset README (for `Tulitula/LensIQ-Synthetic-Portfolio-1000`)**
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  ```markdown
 
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  sigma_hist: 0.209
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  sigma_capm: 0.191
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  ## Files
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