Papers by Guillaume Becquin
Semantic Similarity Covariance Matrix Shrinkage (2023.findings-emnlp)
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| Challenge: | Existing methods to estimate covariance matrix relied on historical price data and ignored company fundamental data. |
| Approach: | They propose to use semantic similarity to improve covariance estimations by using a shrinkage target. |
| Outcome: | The proposed method is compared with the prior art estimate for covariance shrinkage using semantic similarity and price history. |