Alternative Data and NLP in Quant Strategies › Key Parameters
Michael BrenndoerferJanuary 4, 20261 min read
Quantitative FinanceAll chapters Part 13 of 15Machine Learning and Alternative Data
Alternative Data and NLP in Quant Strategies › Key ParametersOne section · Sections in this chapter11 / 18 ↓
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Key parameters for sentiment-based portfolio construction.
- method: Weighting scheme, here 'zscore' or 'rank'. Z-score weighting normalizes signals by their cross-sectional mean and standard deviation, while rank-based weighting uses ordinal rankings.
- halflife: Decay rate for exponential weighting of historical sentiment, here 5 days. Controls how quickly old sentiment signals lose influence.
- alpha: Smoothing parameter for exponential weighted moving average, computed as . Lower alpha means slower response to new information.
- clip_threshold: Maximum absolute z-score allowed, here 3. Winsorizes extreme values to prevent outliers from dominating portfolio weights.