F1.py

It contains codes for Annualized Returns, Volatility and Drawdowns

F1.py

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+import matplotlib as plt
+import pandas as pd
+str = "----------------------------------------------------------------------\n"
+
+
+#computing annualized returns
+def annualized_returns(returns):
+    c = returns/100
+    rpm = (c+1).prod()**(1/(c.shape[0]))-1
+    anr = (rpm+1)**12 -1
+    print(str)
+    print("Annualized returns are :\n")
+    print(anr)
+    return anr
+
+
+# Computing volatility
+def volatility(returns):
+    c = returns/100
+    vol = c.std()*(12**(.5))
+    print(str)
+    print("Volatilities are :\n")
+    print(vol)
+    return vol
+
+
+#computing drawdowns
+def drawdowns(returns):
+    st = 1000   # Started with Rs.1000
+    c = returns/100
+    wi = st*(1+c).cumprod()
+    pk = wi.cummax()
+    drawdown = (wi-pk)/pk
+    print(str)
+    print("Drawdowns are")
+    print(drawdown.min())
+    print("\nDrawdown indexes are")
+    print(drawdown.idxmin())
+    k = pd.DataFrame([wi,pk,drawdown])
+    return k
+
+
+
+returns = pd.read_csv('Portfolios_Formed_on_ME_monthly_EW.csv',parse_dates=True,header = 0,index_col=0, na_values=-99.99)
+#changing to date format
+returns.index = pd.to_datetime(returns.index,format = "%Y%m")
+returns.index = returns.index.to_period('M')
+
+drawdowns(returns)
+volatility(returns)
+annualized_returns(returns)
+
+
+
+
+