Fixes Logic in Momentum and Style Rotation Effect

Instead of the algorithm goes long the top performing ETF and short the
ETF at the bottom as desired, the algorithm was doing the opposite.
Refactors and adds more comments.

Author: AlexCatarino

04 Strategy Library/91 Momentum and Style Rotation Effect/02 Method.html

@@ -6,23 +6,25 @@
 <div class="section-example-container">
 <pre class="python">
 def Initialize(self):
+
     self.SetStartDate(2001, 1, 1)
     self.SetEndDate(2018, 8, 1)
     self.SetCash(100000)
-    self.tickers = [
-                    "IJJ", # iShares S&P MidCap 400 Value Index ETF
-                    "IJS", # iShares S&P SmallCap 600 Value ETF
-                    "IVE", # iShares S&P 500 Value Index ETF
-                    "IVW", # iShares S&P 500 Growth ETF
-                    "IJK", # iShares S&P Mid-Cap 400 Growth ETF
-                    "IJT", # iShares S&P Small-Cap 600 Growth ETF
-                    ]
-    self.symbols = []
-    for ticker in self.tickers:
-        self.symbols.append(self.AddEquity(ticker, Resolution.Daily).Symbol)
-    self.SetWarmUp(timedelta(days=12*20))
-    # save all momentum indicator in the dictionary
-    self.mom = {i:self.MOM(i, 12*20, Resolution.Daily) for i in self.symbols}
+
+    tickers = ["IJJ",   # iShares S&P Mid-Cap 400 Value Index ETF
+               "IJK",   # iShares S&P Mid-Cap 400 Growth ETF
+               "IJS",   # iShares S&P Small-Cap 600 Value ETF
+               "IJT",   # iShares S&P Small-Cap 600 Growth ETF
+               "IVE",   # iShares S&P 500 Value Index ETF
+               "IVW"]   # iShares S&P 500 Growth ETF
+
+    lookback = 12*20
+
+    # Save all momentum indicator into the dictionary
+    self.mom = dict()
+    for ticker in tickers:
+        symbol = self.AddEquity(ticker, Resolution.Daily).Symbol
+        self.mom[symbol] = self.MOM(symbol, lookback)
 </pre>
 </div>
 <p>
@@ -33,12 +35,15 @@
 <div class="section-example-container">
 <pre class="python">
 def Rebalance(self):
+    # Order the MOM dictionary by value
     sorted_mom = sorted(self.mom, key = lambda x: self.mom[x].Current.Value)
-    invested = [x.Key for x in self.Portfolio if x.Value.Invested]
-    for i in invested:
-        if i not in [sorted_mom[0], sorted_mom[1]]:
-            self.Liquidate(i)
-    self.SetHoldings(sorted_mom[0], -0.5)
-    self.SetHoldings(sorted_mom[-1], 0.5)
+
+    # Liquidate the ETFs that are no longer selected
+    for symbol in sorted_mom[1:-1]:
+        if self.Portfolio[symbol].Invested:
+            self.Liquidate(symbol, 'No longer selected')
+
+    self.SetHoldings(sorted_mom[-1], -0.5)   # Short the ETF with lowest MOM
+    self.SetHoldings(sorted_mom[0], 0.5)     # Long the ETF with highest MOM
 </pre>
-</div>
+</div>

04 Strategy Library/91 Momentum and Style Rotation Effect/03 Algorithm.html

@@ -1,6 +1,6 @@
 <div class="qc-embed-frame" style="display: inline-block; position: relative; width: 100%; min-height: 100px; min-width: 300px;">
     <div class="qc-embed-dummy" style="padding-top: 56.25%;"></div>
     <div class="qc-embed-element" style="position: absolute; top: 0; bottom: 0; left: 0; right: 0;">
-        <iframe class="qc-embed-backtest" height="100%" width="100%" style="border: 1px solid #ccc; padding: 0; margin: 0;" src="https://www.quantconnect.com/terminal/index.php?key=processCache&request=embedded_backtest_d0b1d400ad21477d83ae2b4f85616318.html"></iframe>
+        <iframe class="qc-embed-backtest" height="100%" width="100%" style="border: 1px solid #ccc; padding: 0; margin: 0;" src="https://www.quantconnect.com/terminal/processCache?request=embedded_backtest_95cffbeec0d003da873b791d3a10f60f.html"></iframe>
     </div>
 </div>

quantpedia.json

@@ -34,7 +34,7 @@
      77: "0483e5a7094604254ab37eda8b5141b8",
      78: "27fb5f05b0e48f488f0994d8d83ddc77",
      83: "fdfcddd132eaf55039d867c03efe3012",
-     91: "d0b1d400ad21477d83ae2b4f85616318",
+     91: "95cffbeec0d003da873b791d3a10f60f",
      100: "5ee5507fef6bf190ae533ce05ccaa785",
      102: "cd2d187e44a00c7b19f64aee8b0895d9",
      113: "9b1291a5f08dcc07df86363e46144084",