experiment edits

cvx/covariance/ewma.py

@@ -92,8 +92,8 @@ def iterated_ewma(
     returns,
     vola_halflife,
     cov_halflife,
-    min_periods_vola=20,
-    min_periods_cov=20,
+    min_periods_vola=None,
+    min_periods_cov=None,
     mean=False,
     mu_halflife1=None,
     mu_halflife2=None,
@@ -117,9 +117,15 @@ def iterated_ewma(
     if None, no winsorization is performed
     nan_to_num: if True, replace NaNs in returns with 0.0
     """
+    n = returns.shape[1]
     mu_halflife1 = mu_halflife1 or vola_halflife
     mu_halflife2 = mu_halflife2 or cov_halflife
 
+    if min_periods_vola is None:
+        min_periods_vola = n
+    if min_periods_cov is None:
+        min_periods_cov = min_periods_cov or 3 * n
+
     def scale_cov(vola, matrix):
         index = matrix.index
         columns = matrix.columns

experiments/utils/iterated_ewma_vec.py

@@ -81,24 +81,16 @@ def ewma(y, halflife, clip_at=None, min_periods=None):
     """
 
     beta = np.exp(-np.log(2) / halflife)
-    # EWMAs = np.zeros_like(y)
-    # EWMAs[0] = y[0]
 
     EWMA_old = list(y.values())[0]
     for t, time in enumerate(y.keys()):
         if t == 0:
             continue
-        # for t in range(1, y.shape[0]):  # First EWMA is for t=2
-        # y_last = y[t-1] # Note zero-indexing
-        # EWMA_t = get_next_ewma(EWMA_t, y_last, t, beta, clip_at, min_periods)
+
         EWMA_old = get_next_ewma(EWMA_old, y[time], t + 1, beta, clip_at, min_periods)
 
         yield time, EWMA_old
 
-        # EWMAs[t] = get_next_ewma(EWMAs[t - 1], y[t], t + 1, beta, clip_at, min_periods)
-
-        # EWMAs.append(EWMA_t)
-
 
 def _get_realized_covs(returns):
     """