diff --git a/tests/resources/example_data.tar.gz b/tests/resources/example_data.tar.gz
index 67e4ce02..a969befb 100644
Binary files a/tests/resources/example_data.tar.gz and b/tests/resources/example_data.tar.gz differ
diff --git a/tests/test_examples.py b/tests/test_examples.py
index 3accd7ca..b9084574 100644
--- a/tests/test_examples.py
+++ b/tests/test_examples.py
@@ -25,6 +25,8 @@ from zipline.testing import test_resource_path
 from zipline.testing.fixtures import WithTmpDir, ZiplineTestCase
 from zipline.testing.predicates import assert_equal
 from zipline.utils.cache import dataframe_cache
+from zipline.utils.paths import ensure_file
+
 
 # Otherwise the next line sometimes complains about being run too late.
 _multiprocess_can_split_ = False
@@ -53,6 +55,10 @@ class ExamplesTests(WithTmpDir, ZiplineTestCase):
             serialization='pickle',
         )
 
+        market_data = ('SPY_benchmark.csv', 'treasury_curves.csv')
+        for data in market_data:
+            ensure_file(cls.tmpdir.getpath('example_data/root/data/' + data))
+
     @parameterized.expand(sorted(examples.EXAMPLE_MODULES))
     def test_example(self, example_name):
         actual_perf = examples.run_example(
diff --git a/zipline/data/benchmarks.py b/zipline/data/benchmarks.py
index df0cc6bd..88b005df 100644
--- a/zipline/data/benchmarks.py
+++ b/zipline/data/benchmarks.py
@@ -32,11 +32,13 @@ def get_benchmark_returns(symbol, first_date, last_date):
     last_date : pd.Timestamp
         Last date for which we want to get data.
 
-    The furthest date that Google goes back to is 2001-06-26. It has missing
+    The furthest date that Google goes back to is 1993-02-01. It has missing
     data for 2008-12-15, 2009-08-11, and 2012-02-02, so we add data for the
     dates for which Google is missing data.
 
-    We're also limited to the last 4000 days worth of data.
+    We're also limited to 4000 days worth of data per request. If we make a
+    request for data that extends past 4000 trading days, we'll still only
+    receive 4000 days of data.
 
     first_date is **not** included because we need the close from day N - 1 to
     compute the returns for day N.
diff --git a/zipline/data/loader.py b/zipline/data/loader.py
index 12d55b1e..f682f47e 100644
--- a/zipline/data/loader.py
+++ b/zipline/data/loader.py
@@ -31,6 +31,7 @@ from ..utils.paths import (
 from ..utils.deprecate import deprecated
 from zipline.utils.calendars import get_calendar
 
+
 logger = logbook.Logger('Loader')
 
 # Mapping from index symbol to appropriate bond data
@@ -136,10 +137,7 @@ def load_market_data(trading_day=None, trading_days=None, bm_symbol='SPY',
     if trading_days is None:
         trading_days = get_calendar('NYSE').all_sessions
 
-    # We want the latest 4000 trading days
-    # because Google Finance only allows downloading data
-    # up to the 4000 latest trading days
-    first_date = trading_days[-4000]
+    first_date = trading_days[0]
     now = pd.Timestamp.utcnow()
 
     # We expect to have benchmark and treasury data that's current up until
diff --git a/zipline/data/treasuries.py b/zipline/data/treasuries.py
index 0d032ee3..d3016193 100644
--- a/zipline/data/treasuries.py
+++ b/zipline/data/treasuries.py
@@ -67,9 +67,10 @@ def get_treasury_data(start_date, end_date):
         "&from="  # An unbounded query is ~2x faster than specifying dates.
         "&to="
         "&filetype=csv"
+        "&label=include"
         "&layout=seriescolumn"
         "&type=package",
-        skiprows=1,  # First row is a useless header.
+        skiprows=5,  # First 5 rows are useless headers.
         parse_dates=['Time Period'],
         na_values=['ND'],  # Presumably this stands for "No Data".
         index_col=0,
diff --git a/zipline/resources/market_data/^GSPC_benchmark.csv b/zipline/resources/market_data/^GSPC_benchmark.csv
deleted file mode 100644
index 53a87717..00000000
--- a/zipline/resources/market_data/^GSPC_benchmark.csv
+++ /dev/null
@@ -1,6865 +0,0 @@
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