def mapping(tickers, delta_s, tickers_pl, \
init_cash, trans_dates, trans_prices, shares, residual_cashs, \
freq='D'):
#freq: T-trading date, D-Daily, W-Weekly, M-Monthly
# t=0
d = delta_s.index[0]
mapping_date = np.array(d)
cash = init_cash
mapping_cash = np.array(cash)
s = np.zeros(len(tickers))
mapping_shares = np.array(s)
c = np.zeros(len(tickers))
pre_t_date = delta_s.index[0] + datetime.timedelta(days=-1)
for e in range(len(tickers)):
while pre_t_date.date() not in tickers_pl[tickers[e]].index.date:
pre_t_date = pre_t_date + datetime.timedelta(days=-1)
p = read_price(pre_t_date, tickers[e], tickers_pl[tickers[e]])
c[e] = p.Close
mapping_closes = np.array(c)
w = np.zeros(len(tickers))
mapping_weights = np.array(w)
v = 0.0
mapping_value = np.array(v)
# t>=1
if freq == 'D':
start_date = delta_s.index[0]
end_date = tickers_pl[tickers[0]].index[-1]
range_date = pd.date_range(start=start_date, end=end_date, freq='D')
elif freq == 'T':
range_date = trans_dates
else:
range_date = trans_dates
t = 0
for d in range_date:
if datetime.datetime.weekday(d)<=4:
if d == trans_dates[t]:
s = shares[t]
cash = residual_cashs[t]
if t < len(trans_dates)-1:
t = t + 1
mapping_date = np.vstack([mapping_date, d])
mapping_cash = np.vstack([mapping_cash, cash])
mapping_shares = np.vstack([mapping_shares, s])
for e in range(len(tickers)):
if d.date() in tickers_pl[tickers[e]].index.date:
p = read_price(d, tickers[e], tickers_pl[tickers[e]])
c[e] = p.Close
mapping_closes = np.vstack([mapping_closes, c])
v = sum(s*c)
mapping_value = np.vstack([mapping_value, v])
for e in range(len(tickers)):
w[e] = s[e]*c[e]/v
mapping_weights = np.vstack([mapping_weights,w])
return mapping_date, mapping_shares, mapping_weights, mapping_closes, mapping_cash, mapping_value
def get_value(tickers, t_date, shares, tickers_pl=None):
value = 0.0
for e in range(len(tickers)):
if tickers_pl is None:
pl = None
else:
pl = tickers_pl[tickers[e]]
p = read_price(t_date, tickers[e], pl)
value = value + p.Close * shares[e]
return value
def get_close_price(tickers, t_date, tickers_pl=None, weekend=False):
prices = np.zeros(len(tickers))
if weekend is not True:
for e in range(len(tickers)):
if tickers_pl is None:
pl = None
else:
pl = tickers_pl[tickers[e]]
p = read_price(t_date, tickers[e], pl)
prices[e] = p.Close
else:
for e in range(len(tickers)):
if tickers_pl is None:
pl = None
else:
pl = tickers_pl[tickers[e]]
p = read_price(t_date, tickers[e], pl, True)
prices[e] = p.Close
return prices
def est_transacton_prices(tickers, delta_s, tickers_pl):
trans_prices = pd.DataFrame(columns=delta_s.columns)
shares = pd.DataFrame(columns=delta_s.columns)
#t=0
t_date = delta_s.index[0]
# find 1st close price
prices = np.zeros(len(tickers))
pre_t_date = t_date + datetime.timedelta(days=-1)
for e in range(len(tickers)):
while pre_t_date.date() not in tickers_pl[tickers[e]].index.date:
pre_t_date = pre_t_date + datetime.timedelta(days=-1)
c = read_price(pre_t_date, tickers[e], tickers_pl[tickers[e]])
prices[e] = c.Close
#t>=1
for t in range(len(delta_s.index)):
if t == 0:
# initialize dateframe
trans_prices.loc[len(trans_prices)] = np.zeros(len(tickers))
trans_prices['Date'] = delta_s.index[0]
shares.loc[len(shares)] = np.zeros(len(tickers))
shares['Date'] = delta_s.index[0]
else:
# add one more row
trans_prices.loc[len(trans_prices)] = trans_prices.loc[
len(trans_prices) - 1]
shares.loc[len(shares)] = shares.loc[len(shares) - 1]
pre_prices = prices
t_date = delta_s.index[t]
t_date = t_date + datetime.timedelta(days=1)
s = delta_s.iloc[t].copy()
for e in range(len(tickers)):
t_date_e = t_date
while t_date_e.date() not in tickers_pl[tickers[e]].index.date:
t_date_e = t_date_e + datetime.timedelta(days=1)
if s[e] > 0.0: # buy
transaction = 'BUY'
elif s[e] < 0.0:
transaction = 'SELL'
else:
transaction = 'No Trade'
place_price = get_transaction_price(t_date_e, tickers[e],
transaction, pre_prices[e],
tickers_pl[tickers[e]])
trans_prices[tickers[e]].iloc[t] = place_price
shares[tickers[e]].iloc[t] = s[e] + shares[tickers[e]].iloc[t]
trans_prices['Date'].iloc[t] = t_date_e
shares['Date'].iloc[t] = t_date_e
# find t period close price
prices = get_close_price(tickers, t_date, tickers_pl,
True) # True : weekend close
# set date as index
trans_prices.set_index("Date", inplace=True)
shares.set_index("Date", inplace=True)
return trans_prices, shares
def get_close_price(tickers,
t_date,
tickers_pl=None,
freq='Date'): # 'Daily, Weekly, Monthly
prices = np.zeros(len(tickers))
if freq == 'Daily':
for e in range(len(tickers)):
if tickers_pl is None:
pl = None
else:
pl = tickers_pl[tickers[e]]
p = read_price(t_date, tickers[e], pl)
prices[e] = p.Close
elif freq == 'Weekly':
for e in range(len(tickers)):
if tickers_pl is None:
pl = None
else:
pl = tickers_pl[tickers[e]]
p = read_price(t_date, tickers[e], pl, 'Weekly')
prices[e] = p.Close
return prices
def get_transaction_price(t_date,
ticker,
transaction,
pre_Close,
pl=None,
worst=False):
p = read_price(t_date, ticker, pl)
if transaction == 'BUY':
price = _get_long_price(p, pre_Close)
elif transaction == 'SELL':
price = _get_short_price(p, pre_Close)
else:
price = p.Close
return price
def est_transacton_prices(tickers, delta_s, tickers_pl, init_cash):
trans_dates = []
residual_cash = []
trans_prices = np.zeros([len(delta_s), len(tickers)])
shares = np.zeros([len(delta_s), len(tickers)])
#t=0
t_date = delta_s.index[0]
cash = init_cash
# pre_close_price
prices = np.zeros(len(tickers))
pre_t_date = t_date + datetime.timedelta(days=-1)
for e in range(len(tickers)):
while pre_t_date.date() not in tickers_pl[tickers[e]].index.date:
pre_t_date = pre_t_date + datetime.timedelta(days=-1)
c = read_price(pre_t_date, tickers[e], tickers_pl[tickers[e]])
prices[e] = c.Close
#t>=1
for t in range(len(delta_s.index)):
pre_prices = prices
t_date = delta_s.index[t]
t_date = t_date + datetime.timedelta(days=1)
s = delta_s.iloc[t].copy()
for e in range(len(tickers)):
t_date_e = t_date
while t_date_e.date() not in tickers_pl[tickers[e]].index.date:
t_date_e = t_date_e + datetime.timedelta(days=1)
if s[e] > 0.0: # buy
transaction = 'BUY'
elif s[e] < 0.0:
transaction = 'SELL'
else:
transaction = 'No Trade'
place_price = get_transaction_price(t_date_e, tickers[e],
transaction, pre_prices[e],
tickers_pl[tickers[e]])
trans_prices[t, e] = place_price
fee = _calc_fee(place_price, s[e], transaction)
delta_cash = -s[e] * place_price - fee
cash = cash + delta_cash
if t == 0:
shares[t] = s
else:
shares[t] = shares[t - 1] + s
trans_dates.append(t_date_e)
residual_cash.append(cash)
prices = get_close_price(tickers, t_date_e, tickers_pl, 'Weekly')
return trans_dates, trans_prices, shares, residual_cash
def est_transacton_prices_1(tickers, delta_s, tickers_pl):
trans_prices = delta_s.copy()
place_date = delta_s.index.date
#t=0
t_date = delta_s.index[0]
prices = np.zeros(len(tickers))
pre_t_date = t_date + datetime.timedelta(days=-1)
for e in range(len(tickers)):
while pre_t_date.date() not in tickers_pl[tickers[e]].index.date:
pre_t_date = pre_t_date + datetime.timedelta(days=-1)
c = read_price(pre_t_date, tickers[e], tickers_pl[tickers[e]])
prices[e] = c.Close
#t>=1
for t in range(len(delta_s.index)):
pre_prices = prices
t_date = delta_s.index[t]
t_date = t_date + datetime.timedelta(days=1)
s = delta_s.iloc[t].copy()
for e in range(len(tickers)):
t_date_e = t_date
while t_date_e.date() not in tickers_pl[tickers[e]].index.date:
t_date_e = t_date_e + datetime.timedelta(days=1)
if s[e] > 0.0: # buy
transaction = 'BUY'
elif s[e] < 0.0:
transaction = 'SELL'
else:
transaction = 'No Trade'
place_price = get_transaction_price(t_date_e, tickers[e],
transaction, pre_prices[e],
tickers_pl[tickers[e]])
trans_prices[tickers[e]].iloc[t] = place_price
place_date[t] = t_date_e
prices = get_close_price(tickers, t_date, tickers_pl, True)
trans_prices.reset_index(level=0, inplace=True)
trans_prices.Date = place_date
trans_prices.set_index("Date", inplace=True)
return trans_prices
df = pd.read_excel(open('s.xlsx', 'rb'), sheet_name=0)
s = df.copy()
s.set_index("Date", inplace=True)
# portfolio assets
tickers = s.columns
# t=0
shares = np.zeros(len(tickers))
cash = 500000
# pre_price at t=0
t_date = s.index[0]
pre_t_date = get_working_date(t_date, True)
prices = shares.copy()
for e in range(len(tickers)):
c = read_price(pre_t_date, tickers[e])
prices[e] = c.Close
value = 0.0
print(pre_t_date.strftime("%Y-%m-%d"), shares, "{0:42.2f}".format(cash),
"{0:.2f}".format(value))
# t>=1
for t in range(len(s.index)):
pre_shares = shares
pre_cash = cash
pre_prices = prices
t_date = s.index[t]
t_date = get_working_date(t_date)
delta_s = np.zeros(len(tickers))
for e in range(len(tickers)):
delta_s[e] = s[s.columns[e]][t]
