#  NOTEBOOK settings and system details:   [00-tpl v14.12.21]

#  Assume that the backend is LINUX (our particular distro is Ubuntu, running bash shell):
print '\n ::  TIMESTAMP of last notebook execution:'
!date
print '\n ::  IPython version:'
!ipython --version

#  Automatically reload modified modules:
%load_ext autoreload
%autoreload 2
#           0 disables autoreload.
#  Generate plots inside notebook:
%matplotlib inline

#  DISPLAY options
from IPython.display import Image 
#  e.g. Image(filename='holt-winters-equations.png', embed=True) # url= also works
from IPython.display import YouTubeVideo
#  e.g. YouTubeVideo('1j_HxD4iLn8', start='43', width=600, height=400)
from IPython.display import HTML # useful for snippets
#  e.g. HTML('<iframe src=http://en.mobile.wikipedia.org/?useformat=mobile width=700 height=350></iframe>')

import pandas as pd
print '\n ::  pandas version:'
print pd.__version__
#      pandas DataFrames are represented as text by default; enable HTML representation:
#      [Deprecated: pd.core.format.set_printoptions( notebook_repr_html=True ) ]
pd.set_option( 'display.notebook_repr_html', False )

#  MATH display, use %%latex, rather than the following:
#                from IPython.display import Math
#                from IPython.display import Latex

print '\n ::  Working directory (set as $workd):'
workd, = !pwd
print workd + '\n'

from yi_1tools import *
from yi_plot import *
from yi_timeseries import *
from yi_fred import *

#  Daily frequency:
eurusd = getfred( d4eurusd )
#  Note that the synthetic preprend back to 1971 is only for monthly data.

plotfred( eurusd )

#  Monthly frequency (daily frequency is not available):
eursyn = getfred( m4eurusd )

plotfred(eursyn, 'EURUSD synthetic')

#  Define the day before QE-EU:
qeeu = '2015-01-21'

#  What is the EURUSD low since QE-EU announcement?
#  On the day before, on 2015-01-21, the rate was 1.1584.
stats( eurusd[qeeu:] )

syntrend = trend( eursyn )

plotfred( syntrend )

#  Detrend:
plotfred( eursyn - syntrend )

tailvalue( syntrend )

#  Forecast monthly for next 24 months:
holtfred( eursyn )

#  Look at geometric return since 2006:
georet( eurusd[t06:] )

#  We retrieve the monthly frequency:
usdjpy = getfred( m4usdjpy )

#  Since monthly eursysn is expressed in terms of EURUSD:
eurjpy = todf( eursyn * usdjpy )

plotfred( eurjpy, 'EURJPY synthetic' )

#  Verify trend claim:
ej95trend = trend( eurjpy['1995-01-01':] )

#  The plot is uninteresting, just a straight line along 129.50 !
#  Look at the slope and the std for confirmation:
ej95trend.describe()

#  Euro strength against the yen on a scale of 100:
int((tailvalue( eurjpy ) - 90) / 0.80) 

#  2014-12-22: 71  One month prior to QE-EU, EURJPY = 146.83
#  2015-01-21: 58  One day prior to QE-EU, EURJPY = 136.52
#  2015-04-01: 51  Two months after QE-EU, EURJPY = 130.80
#  2015-05-18: 55  Four months after QE-EU

georet( eurjpy[t06:], 12 )