Updated Computational Investing Part I samples

doc/compinvpart1.rst

@@ -2,12 +2,12 @@ Computational Investing Part I
 ==============================
 
 As I was taking the `Computational Investing Part I <https://class.coursera.org/compinvesting1-2012-001/class>`_ course in 2012
-I had to work on a set of assignments and for some of them I used PyAlgoTrade.
+I had to work on a set of assignments and for one of them I used PyAlgoTrade.
 
 Homework 1
 ----------
 
-For this assignment I had to pick 4 stocks, invest a total of $100000 during 2011, and calculate:
+For this assignment I had to pick 4 stocks, invest a total of $1000000 during 2011, and calculate:
 
  * Final portfolio value
  * Anual return
@@ -17,10 +17,10 @@ For this assignment I had to pick 4 stocks, invest a total of $100000 during 201
 
 Download the data with the following commands: ::
 
-    python -c "from pyalgotrade.tools import yahoofinance; yahoofinance.download_daily_bars('aeti', 2011, 'aeti-2011-yahoofinance.csv')"
-    python -c "from pyalgotrade.tools import yahoofinance; yahoofinance.download_daily_bars('egan', 2011, 'egan-2011-yahoofinance.csv')"
-    python -c "from pyalgotrade.tools import yahoofinance; yahoofinance.download_daily_bars('glng', 2011, 'glng-2011-yahoofinance.csv')"
-    python -c "from pyalgotrade.tools import yahoofinance; yahoofinance.download_daily_bars('simo', 2011, 'simo-2011-yahoofinance.csv')"
+    python -m "pyalgotrade.tools.quandl" --source-code="WIKI" --table-code="IBM" --from-year=2011 --to-year=2011 --storage=. --force-download --frequency=daily
+    python -m "pyalgotrade.tools.quandl" --source-code="WIKI" --table-code="AES" --from-year=2011 --to-year=2011 --storage=. --force-download --frequency=daily
+    python -m "pyalgotrade.tools.quandl" --source-code="WIKI" --table-code="AIG" --from-year=2011 --to-year=2011 --storage=. --force-download --frequency=daily
+    python -m "pyalgotrade.tools.quandl" --source-code="WIKI" --table-code="ORCL" --from-year=2011 --to-year=2011 --storage=. --force-download --frequency=daily
 
 Although the deliverable was an Excel spreadsheet, I validated the results using this piece of code:
 
@@ -29,53 +29,3 @@ Although the deliverable was an Excel spreadsheet, I validated the results using
 The results were:
 
 .. literalinclude:: ../samples/compinv-1.output
-
-Homework 3 and 4
-----------------
-
-For these assignments I had to build a market simulation tool that loads orders from a file, executes those,
-and prints the results for each day.
-
-The orders file for homework 3 look like this: ::
-
-    2011,1,10,AAPL,Buy,1500,
-    2011,1,13,AAPL,Sell,1500,
-    2011,1,13,IBM,Buy,4000,
-    2011,1,26,GOOG,Buy,1000,
-    2011,2,2,XOM,Sell,4000,
-    2011,2,10,XOM,Buy,4000,
-    2011,3,3,GOOG,Sell,1000,
-    2011,3,3,IBM,Sell,2200,
-    2011,6,3,IBM,Sell,3300,
-    2011,5,3,IBM,Buy,1500,
-    2011,6,10,AAPL,Buy,1200,
-    2011,8,1,GOOG,Buy,55,
-    2011,8,1,GOOG,Sell,55,
-    2011,12,20,AAPL,Sell,1200,
-
-This is the market simulation tool that I built:
-
-.. literalinclude:: ../samples/compinv-3.py
-
-The output for homework 3 looks like this: ::
-
-    First date 2011-01-10 00:00:00
-    Last date 2011-12-20 00:00:00
-    Symbols ['AAPL', 'IBM', 'GOOG', 'XOM']
-    2011-01-10 00:00:00: Portfolio value: $1000000.00
-    2011-01-11 00:00:00: Portfolio value: $998785.00
-    2011-01-12 00:00:00: Portfolio value: $1002940.00
-    2011-01-13 00:00:00: Portfolio value: $1004815.00
-    .
-    .
-    .
-    2011-12-15 00:00:00: Portfolio value: $1113532.00
-    2011-12-16 00:00:00: Portfolio value: $1116016.00
-    2011-12-19 00:00:00: Portfolio value: $1117444.00
-    2011-12-20 00:00:00: Portfolio value: $1133860.00
-    Final portfolio value: $1133860.00
-    Anual return: 13.39 %
-    Average daily return: 0.05 %
-    Std. dev. daily return: 0.0072
-    Sharpe ratio: 1.21
-

samples/compinv-1.output

@@ -1,5 +1,5 @@
-Final portfolio value: $1604979.11
-Anual return: 60.50 %
-Average daily return: 0.20 %
-Std. dev. daily return: 0.0136
-Sharpe ratio: 2.30
+Final portfolio value: $876350.83
+Anual return: -12.36 %
+Average daily return: -0.04 %
+Std. dev. daily return: 0.0176
+Sharpe ratio: -0.33

samples/compinv-1.py

@@ -1,5 +1,5 @@
 from pyalgotrade import strategy
-from pyalgotrade.barfeed import yahoofeed
+from pyalgotrade.barfeed import quandlfeed
 from pyalgotrade.stratanalyzer import returns
 from pyalgotrade.stratanalyzer import sharpe
 from pyalgotrade.utils import stats
@@ -14,23 +14,23 @@ def __init__(self, feed):
 
         # Place the orders to get them processed on the first bar.
         orders = {
-            "aeti": 297810,
-            "egan": 81266,
-            "glng": 11095,
-            "simo": 17293,
+            "ibm": 1996,
+            "aes": 22565,
+            "aig": 5445,
+            "orcl": 8582,
         }
         for instrument, quantity in orders.items():
             self.marketOrder(instrument, quantity, onClose=True, allOrNone=True)
 
     def onBars(self, bars):
         pass
 
-# Load the yahoo feed from CSV files.
-feed = yahoofeed.Feed()
-feed.addBarsFromCSV("aeti", "aeti-2011-yahoofinance.csv")
-feed.addBarsFromCSV("egan", "egan-2011-yahoofinance.csv")
-feed.addBarsFromCSV("glng", "glng-2011-yahoofinance.csv")
-feed.addBarsFromCSV("simo", "simo-2011-yahoofinance.csv")
+# Load the bar feed from the CSV file
+feed = quandlfeed.Feed()
+feed.addBarsFromCSV("ibm", "WIKI-IBM-2011-quandl.csv")
+feed.addBarsFromCSV("aes", "WIKI-AES-2011-quandl.csv")
+feed.addBarsFromCSV("aig", "WIKI-AIG-2011-quandl.csv")
+feed.addBarsFromCSV("orcl", "WIKI-ORCL-2011-quandl.csv")
 
 # Evaluate the strategy with the feed's bars.
 myStrategy = MyStrategy(feed)