In [1]:

    

import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import sys
import requests

# sys.path.insert(0, '/home/sihaodi/Documents/DataAPI/dataAPI')
# sys.path.insert(0, '/home/sihaodi/Documents/DataAPI')
from dataAPI.dateconversion import *
import time, json


    

    




---------------------------------------------------------------------------
ModuleNotFoundError                       Traceback (most recent call last)
<ipython-input-1-0a6918511c66> in <module>
      7 # sys.path.insert(0, '/home/sihaodi/Documents/DataAPI/dataAPI')
      8 # sys.path.insert(0, '/home/sihaodi/Documents/DataAPI')
----> 9 from dataAPI.dateconversion import *
     10 import time, json

ModuleNotFoundError: No module named 'dataAPI'

In [3]:

    

def get_online_data(etf_ticker:str, index_ticker:str, etf_t:(int,int), index_t:(int,int),\
                    host='192.168.5.4', port=8808, currency = 'USD') -> ({str:float},{str:float}):
    
    base  = 'http://%s:%s' % (host, port)
    
    etf_ticker = etf_ticker.replace('-',' ')
    url_etf = base + '/bdh/"%s"/"TOT_RETURN_INDEX_GROSS_DVDS"/%s/%s/{"currency":"%s"}'%\
                          (etf_ticker, unixToDateTime(etf_t[0]).strftime('%Y%m%d'),unixToDateTime(etf_t[1])\
                           .strftime('%Y%m%d'), currency)
    
    data_etf = requests.get(url_etf)
    data_etf = json.loads(data_etf.json())
    
    assert 'TOT_RETURN_INDEX_GROSS_DVDS' in data_etf.keys(), 'ETF data not available'
    data_etf = data_etf['TOT_RETURN_INDEX_GROSS_DVDS']

    index_ticker = index_ticker.replace('-',' ')
    url_index = base + '/bdh/"%s"/"TOT_RETURN_INDEX_GROSS_DVDS"/%s/%s/{"currency":"%s"}'%\
                          (index_ticker, unixToDateTime(index_t[0]).strftime('%Y%m%d'),unixToDateTime(index_t[1])\
                           .strftime('%Y%m%d'), currency)
    data_index = requests.get(url_index)
    data_index = json.loads(data_index.json())
    
    assert 'TOT_RETURN_INDEX_GROSS_DVDS' in data_index.keys(), 'index data not available'
    data_index = data_index['TOT_RETURN_INDEX_GROSS_DVDS']

    return data_etf, data_index

def change_time_basis(data_etf:{str:float}, data_index:{str:float}) :
    
    data_etf_new ={}
    for i in data_etf.keys():
        data_etf_new[unixToDateTime(int(i)).strftime('%Y%m%d')] = \
        data_etf[i]
    
    data_index_new = {}
    for i in data_index.keys():
        data_index_new[unixToDateTime(int(i)).strftime('%Y%m%d')] = \
        data_index[i]
    
    return data_etf_new, data_index_new

def blending_algo_rtn(data_etf:{str:float}, data_index:{str:float}, expense_ratio = 0.00001)\
                        -> {int:float}:
    
    end_date = str(np.max([int(i) for i in data_etf.keys()]))
    end_level= data_etf[end_date]
    etf_key_sorted = np.sort([int(i) for i in data_etf.keys()])
       
    etf_return = {(etf_key_sorted[i])\
                  :(data_etf[str(etf_key_sorted[i+1])]-data_etf[str(etf_key_sorted[i])])*(1-expense_ratio)\
                              /data_etf[str(etf_key_sorted[i])]\
                              for i in range(len(etf_key_sorted)-1)}
    
    index_key_sorted = np.sort([int(i) for i in data_index.keys()])
    
    assert index_key_sorted[-1]>=etf_key_sorted[0], 'index and etf are not contineous'
    
    index_return = {(index_key_sorted[i])\
                  :(data_index[str(index_key_sorted[i+1])]-data_index[str(index_key_sorted[i])])\
                              /data_index[str(index_key_sorted[i])]\
                              for i in range(len(index_key_sorted)-1)}
    
    blended_return = etf_return
    blended_return.update(index_return)
    
    #blended_return = sort_dicts({str(i):blended_return[i] for i in blended_return.keys()})
    return blended_return

def blending_algo_price(data_etf:{str:float}, data_index:{str:float}, \
                        rtn_index:{int:float}, expense_ratio = 0.00001) -> {int:float}:
    
    end_date  = str(np.max([int(i) for i in data_etf.keys()]))
    end_level = data_etf[end_date]
    etf_key_sorted = np.sort([int(i) for i in data_etf.keys()])
    index_key_sorted = np.sort([int(i) for i in data_index.keys()])
    
    assert index_key_sorted[-1]>=etf_key_sorted[0], 'index and etf are not contineous'
    
    blended_index_id = [i for i in index_key_sorted if i <=(etf_key_sorted[0])]
    rtn_index_blended = {i:rtn_index[i] for i in blended_index_id}
    blended_price_l  = data_etf[str(etf_key_sorted[0])]
    
    blended_price_index = {}
    blended_price_index[blended_index_id[-1]] = blended_price_l
    for i in range(len(blended_index_id)-2,-1,-1):
        blended_price_index[blended_index_id[i]] = blended_price_index[blended_index_id[i+1]]/\
        (1+rtn_index_blended[blended_index_id[i+1]])
    
    data_etf = {int(i):data_etf[i] for i in data_etf.keys()}
    blended_price_index.update(data_etf)
    blended_price_index = sort_dicts({str(i):blended_price_index[i] for i in blended_price_index.keys()})
    
    return blended_price_index

def sort_dicts(dic:{str:float}) -> {str:float}:
    '''
    the absolute value represents the order of a time series
    '''
    d = {int(i):j for (i,j) in dic.items()}
    d_keys = list(d.keys())
    d = {str(i):d[i] for i in np.sort(d_keys)}
    
    return d


    

In [4]:

    

etf_ticker   = 'SPY-US-Equity'
index_ticker = 'SPXT-Index'
etf_t   = (1206016000,1516016000)
index_t = (1106016000,1416016000)

etf,index = get_online_data(etf_ticker,index_ticker,etf_t,index_t)
etf,index = change_time_basis(etf,index)
blended_rtns  = blending_algo_rtn(etf,index)
blended_price = blending_algo_price(etf,index,blended_rtns)


    

    




---------------------------------------------------------------------------
NameError                                 Traceback (most recent call last)
<ipython-input-4-7d83d4e5335b> in <module>()
      4 index_t = (1106016000,1416016000)
      5 
----> 6 etf,index = get_online_data(etf_ticker,index_ticker,etf_t,index_t)
      7 etf,index = change_time_basis(etf,index)
      8 blended_rtns  = blending_algo_rtn(etf,index)

<ipython-input-3-3ef1a87653d1> in get_online_data(etf_ticker, index_ticker, etf_t, index_t, host, port, currency)
      4 
      5     etf_ticker = etf_ticker.replace('-',' ')
----> 6     url_etf = base + '/bdh/"%s"/"TOT_RETURN_INDEX_GROSS_DVDS"/%s/%s/{"currency":"%s"}'%                          (etf_ticker, unixToDateTime(etf_t[0]).strftime('%Y%m%d'),unixToDateTime(etf_t[1])                           .strftime('%Y%m%d'), currency)
      7 
      8     data_etf = requests.get(url_etf)

NameError: name 'unixToDateTime' is not defined

In [136]:

    

rtns_x = []
rtns_y = []
for i in np.sort(list(blended_rtns.keys())):
    rtns_x = rtns_x + [i]
    rtns_y = rtns_y + [blended_rtns[i]]
rtns_x = pd.to_datetime([str(i) for i in rtns_x]).tolist()


price_x = []
price_y = []
for i in np.sort(list(blended_price.keys())):
    price_x = price_x + [i]
    price_y = price_y + [blended_price[i]]
price_x = pd.to_datetime([str(i) for i in price_x]).tolist()

plt.figure(figsize=(20,12))

plt.subplot(2, 1, 1)
plt.plot(rtns_x, rtns_y)
plt.ylabel('returns',fontsize=20)

plt.subplot(2, 1, 2)
plt.plot(price_x, price_y)
plt.ylabel('price',fontsize=20)


plt.show()


    

In [133]:

    




    

In [135]:

    

plt.plot(rtns_x,rtns_y)
plt.show()


    

In [134]:

    

(rtns_x)


    

    
Out[134]:





[Timestamp('2005-01-18 00:00:00'),
 Timestamp('2005-01-19 00:00:00'),
 Timestamp('2005-01-20 00:00:00'),
 Timestamp('2005-01-21 00:00:00'),
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 Timestamp('2006-04-26 00:00:00'),
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 Timestamp('2009-01-06 00:00:00'),
 ...]

In [ ]: