Fixes Small Capitalization Stocks Premium Anomaly Algorithm

Fixes the issue on the Universe Selection functions returning empty list
of Symbol that unsubscribes them.
Refactors the algorithm to use a pattern that does not depend on Schedule
Events and rely on OnSecuritiesChanged to liquidate securities.

Author: AlexCatarino

04 Strategy Library/28 Small Capitalization Stocks Premium Anomaly/02 Method.html

@@ -2,25 +2,26 @@
   The first step is coarse universe selection. We create an investment universe with stocks that have fundmental data and with a price greater than $5.
 </p>
 <div class="section-example-container">
-<pre class="python">self.filtered_coarse = [x.Symbol for x in coarse if (x.HasFundamentalData) and (float(x.AdjustedPrice) > 5)]
+<pre class="python">return [x.Symbol for x in coarse if x.HasFundamentalData and x.AdjustedPrice > 5]
 </pre>
 </div>
 <p>In fine universe selection, we sort the stocks in the universe by the market capitalization and choose 10 stocks with the lowest market cap.
 </p>
 <div class="section-example-container">
 <pre class="python">def FineSelectionFunction(self, fine):
-    if self.yearly_rebalance:
-        fine = [x for x in fine if (x.ValuationRatios.PERatio > 0)
-                                and (x.EarningReports.BasicAverageShares.ThreeMonths > 0)
-                                and (x.EarningReports.BasicEPS.TwelveMonths > 0)]
-        for i in fine:
-            i.MarketCap = float(i.EarningReports.BasicAverageShares.ThreeMonths * (i.EarningReports.BasicEPS.TwelveMonths*i.ValuationRatios.PERatio))
-        sorted_market_cap = sorted(fine, key=lambda x: x.MarketCap)
-        self.filtered_fine = [i.Symbol for i in sorted_market_cap[:20]]
-        self.yearly_rebalance = False
-        return self.filtered_fine
-    else:
-        return []
+    if self.year == self.Time.year:
+        return self.symbols
+
+    # Calculate the market cap and add the "MarketCap" property to fine universe object
+    for i in fine:
+        i.MarketCap = (i.EarningReports.BasicAverageShares.ThreeMonths * 
+                       i.EarningReports.BasicEPS.TwelveMonths *
+                       i.ValuationRatios.PERatio)
+
+    sorted_market_cap = sorted([x for x in fine if x.MarketCap > 0], key=lambda x: x.MarketCap)
+
+    self.symbols = [i.Symbol for i in sorted_market_cap[:10]]
+    return self.symbols
 </pre>
 </div>
 <p>

04 Strategy Library/28 Small Capitalization Stocks Premium Anomaly/03 Algorithm.html

@@ -1,6 +1,6 @@
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