update example

1 files changed, 21 insertions, 8 deletions

diff --git a/example.py b/example.py
index 99d3bbe..ab648d8 100644
--- a/example.py
+++ b/example.py
@@ -1,12 +1,14 @@
-from pyisda.zerocurve import ZeroCurve, BadDay
+from pyisda.curve import ZeroCurve, BadDay, SpreadCurve
 import sys
 sys.path.append("/home/share/CorpCDOs/code/python")
 from yieldcurve import getMarkitIRData
 import datetime
 import array
 from pyisda.cdsone import upfront_charge, spread_from_upfront
+from pyisda.legs import FeeLeg, ContingentLeg
 
 if __name__ == "__main__":
+    # build zero coupon curve
     markit_data = getMarkitIRData()
     date = datetime.date.today()
     periods, rates = zip(*markit_data['deposits'])
@@ -19,11 +21,22 @@ if __name__ == "__main__":
     rates.extend(rates_swaps)
     zc = ZeroCurve(date, types, periods, rates, 'ACT/360', '6M',
                    '3M', 'ACT/360', 'ACT/360', BadDay.MODIFIED)
-    upf = upfront_charge(date, date, date, datetime.date(2016, 6, 29),
-                         datetime.date(2016, 3, 21), datetime.date(2021, 6, 20),
-                         0.05, zc, 0.04368871, 0.3)
-    spread = spread_from_upfront(date, date, date, datetime.date(2016, 6, 29),
-                                 datetime.date(2016, 3, 21), datetime.date(2021, 6, 20),
-                                 0.05, zc, -0.02675, 0.3)
-    print(upf)
+
+    start_date = datetime.date(2016, 3, 21)
+    end_date = datetime.date(2021, 6, 20)
+    upfront_quote = -0.03063
+    spread = spread_from_upfront(date, date, date, date+datetime.timedelta(days=1),
+                                 start_date, end_date, 0.05, zc,
+                                 upfront_quote, 0.3)
+    upf = upfront_charge(date, date, date, date+datetime.timedelta(days=1),
+                         start_date, end_date, 0.05, zc, spread, 0.3)
     print(spread)
+    print(upf-upfront_quote)
+
+    coupon_leg = FeeLeg(start_date, end_date, True, 1000000, 0.05)
+    spread = array.array('d', [0.007725])
+    print("pomme")
+    step_in_date = date + datetime.timedelta(days=1)
+    sc = SpreadCurve(date, zc, start_date, step_in_date,
+                     datetime.date(2016, 7, 6),
+                     [end_date], spread, 0.4, 1)