more typos

notebooks/02_factor_analysis_and_diagnostics.ipynb

@@ -372,7 +372,7 @@
    "id": "5659b941",
    "metadata": {},
    "source": [
-    "Note that we added a sample size filter with `mask.sum() < 20`. The `mask` identifies stocks that have both a valid factor score and a valid forward return in a given month, and `mask.sum()` counts how many usable pairs you actually have. The `< 20` threshold prevents the code from computing a correlation on a tiny sample, which is statistically meaningless and numerically unstable (e.g., Spearman correlation on 2 stocks is always exactly ±1). If you don't gate this, early-history months, mass delistings, or data gaps inject garbage ±1.0 values into your IC time series, which then contaminate every downstream statistic like the mean IC, Information Ratio, and decay curves. Setting a floor of 20 filters out those degenerate months while retaining enough valid data to produce a reliable signal.\n",
+    "Note that we added a sample size filter with `mask.sum() < 20`. The `mask` identifies stocks that have both a valid factor score and a valid forward return in a given month, and `mask.sum()` counts how many usable pairs you actually have. The `< 20` threshold prevents the code from computing a correlation on a tiny sample, which is statistically meaningless and numerically unstable (e.g., Spearman correlation on 2 stocks is always exactly $\\pm$1). If you don't gate this, early-history months, mass delistings, or data gaps inject garbage $\\pm 1.0$ values into your IC time series, which then contaminate every downstream statistic like the mean IC, Information Ratio, and decay curves. Setting a floor of 20 filters out those degenerate months while retaining enough valid data to produce a reliable signal.\n",
     "\n",
     "We do this sort of masking throughout."
    ]