from Data import YahooData
import numpy as np
import pandas as pd
from Data import Utility
universe = Utility.get_stock_universe('stock_universe.csv')
u_tick = universe['Tick'].unique().tolist()
universe.set_index('Tick', inplace=True)
returns = YahooData.get_returns(u_tick)
ev_ebitda = YahooData.get_ev_ebitda(u_tick)
ocf_ev = YahooData.get_ocf_ev(u_tick)
ratios = YahooData.get_ratios(u_tick, ['Price', 'PS', 'PB', 'PE', '50ma', '200ma'])
comp_info = YahooData.get_sector_industry(u_tick)
df = universe.join(comp_info)
df = df.join(ratios)
df = df.join(ev_ebitda)
df = df.join(ocf_ev)
df = df.join(returns)
df = df.replace('N/A', np.nan)
df['ma_ratio'] = df['50ma'].astype(float) / df['200ma'].astype(float)
df['ebitda_ev_rank'] = df['ebitda_ev'].astype(float).rank(ascending=True)
df['ocf_ev_rank'] = df['ocf_ev'].astype(float).rank(ascending=True)
df['PS_rank'] = df['PS'].astype(float).rank(ascending=False)
df['PB_rank'] = df['PB'].astype(float).rank(ascending=False)
df['PE_rank'] = df['PE'].astype(float).rank(ascending=False)
df['ma_ratio_rank'] = df['ma_ratio'].rank(ascending=True)
df['return_rank'] = df['1yr_rtn'].rank(ascending=True)
GHC 3.37B
HME 4.37B
FLOW 22.72B
STAY.U 3.72B
JW.A JW-A
HUB.B HUB-B
FCE.A FCE-A
STAY.U STAY
BF.B BF-B
BF.A BF-A
BRK.B BRK-B
LEN.B LEN-B
"""
universe = Utility.get_stock_universe("stock_universe.csv")
u_tick = universe["Tick"].unique().tolist()
# comp_MF_data = Utility.get_compustat_data('CQA_MF_data.csv', exchanges=['11', '12', '14'])
# comp_MOH_ad_data = Utility.get_compustat_data('CQA_MOH_AD_data.csv', exchanges=['11', '12', '14'])
# MOH_result = MOH_calc.Calc(comp_MOH_data, u_tick, comp_MOH_ad_data)
# get data from Yahoo
returns = YahooData.get_returns(u_tick)
values = YahooData.get_ev_ebitda(u_tick)
df = universe.join(values)
mkt_cap_df = YahooData.get_value(u_tick, "Mkt_cap")
"""
mkt_cap_df.ix['FLOW'] = 22720
mkt_cap_df.ix['MSG'] = 4450
# -*- coding: utf-8 -*-
"""
Created on Tue Nov 10 20:50:03 2015
@author: Guanwen
"""
from Data import Utility
from Calculation import PIO_calc
u_tick= ['AAPL']
comp_PIO_data = Utility.get_compustat_data('CQA_PIO_data.csv', exchanges=['11', '12', '14'])
PIO_result = PIO_calc.Calc(comp_PIO_data, u_tick, details=True)
PIO_result.to_csv(r'C:\Users\Guanwen\Desktop\test.csv')
