def test_too_expensive_buy():
assert db
c = 1000.0
a = va.VirtualAccount(c, db.get_all_symbol_data())
assert a
a.buy_at_market(0, 'SPY', 2000)
assert len(a.get_all_positions()) == 0
assert a.get_cash() == c
def test_invalid_buy_qty():
assert db
c = 1000.0
a = va.VirtualAccount(c, db.get_all_symbol_data())
assert a
a.buy_at_market(0, 'SPY', 0)
assert len(a.get_all_positions()) == 0
assert a.get_cash() == c
a.buy_at_market(0, 'SPY', -10)
assert len(a.get_all_positions()) == 0
assert a.get_cash() == c
def test_too_expensive_sell():
assert db
c = 10000.0
a = va.VirtualAccount(c, db.get_all_symbol_data())
assert a
a.buy_at_market(0, 'SPY', 1)
assert len(a.get_open_positions()) == 1
assert a.get_cash() < c
a.delta_cash(-a.get_cash() + 0.1)
assert a.get_cash() > 0.0
c = a.get_cash()
a.sell_at_market(a.get_open_positions()[0], 10)
assert a.get_cash() == c
assert len(a.get_open_positions()) == 1
def test_invalid_sell():
assert db
c = 1000.0
a = va.VirtualAccount(c, db.get_all_symbol_data())
assert len(a.get_open_positions()) == 0
assert a
a.buy_at_market(0, 'SPY', 1)
assert len(a.get_open_positions()) == 1
p = a.get_open_positions()[0]
a.sell_at_market(p, 1) # 1st sell, ok
assert len(a.get_open_positions()) == 0
assert len(a.get_close_positions()) == 1
c = a.get_cash()
a.sell_at_market(p, 2) # 2nd invalid sell same position
assert a.get_cash() == c
def simulate2():
print("simulate2()")
a = va.VirtualAccount(50000.00, dic)
print("Initial cash", a.get_cash())
# Symbol loop
symbol_list = list(dic.keys())
symbol_list.sort()
for symbol in symbol_list:
print("Simulating with", symbol)
df = dic[symbol]
# The various series (starting with s):
s_close = fu.get_close(df)
# Technical indicators
s_close_sma = ti.sma(s_close, 200)
# Bar loops (1 bar per day)
# start index to include various moving average lag
# end at -1 to include "tomorrow" (corresponds to last valid bar)
# TBD to fix this with real signals
for bar in range(200, len(df) - 1):
# Positions loop
open_positions = a.get_open_positions(symbol)
for pos in open_positions:
# TBD sell logic
sell_signal = s_close[bar] > 1.15 * pos.get_entry_price() or \
s_close[bar] < 0.95 * pos.get_entry_price()
if sell_signal:
a.sell_at_market(pos, bar + 1) # bar + 1 = tomorrow
if not open_positions:
# TBD buy logic
buy_signal = ti.cross_over(s_close, s_close_sma)[bar]
if buy_signal:
nb_share = int(
2500 / s_close[bar]
) # 2500$ => about 0.8% commission buy + sell
a.buy_at_market(bar + 1, symbol,
nb_share) # bar + 1 = tomorrow
for p in a.get_all_positions():
print(p)
print("Final cash", a.get_cash())
def simulate():
print("simulate()")
initial_cash = 100000.0
a = va.VirtualAccount(initial_cash, dic)
print("Initial cash", a.get_cash())
# Target allocation:
ratio = {
'XBB.TO': 0.1,
'ZCN.TO': 0.3,
'VUN.TO': 0.3,
'XEF.TO': 0.2,
'XEC.TO': 0.1
}
# Symbol loop
symbol_list = list(dic.keys())
symbol_list.sort()
df = pd.DataFrame(index=symbol_list,
data=[ratio[s] for s in symbol_list],
columns=['TgtAlloc'])
df['NbShare'] = np.zeros(len(symbol_list))
df_prices = db.get_all_symbol_single_data_item('Close')
for i in range(len(df_prices)):
if i % 100 == 0: # Adjust rebalance frequency here
print("Rebalance", i)
# Roughly Matching StockPortfolio_RRSP column ordering
df['Price'] = df_prices.iloc[i]
df['MktValue'] = df['Price'] * df['NbShare']
total_value = sum(df['Price'] * df['NbShare']) + a.get_cash()
df['CurrAlloc'] = df['MktValue'] / total_value
df['DeltaAlloc'] = df['CurrAlloc'] - df['TgtAlloc']
df['TgtValue'] = df['TgtAlloc'] * total_value
# +:Buy -:Sell
df['DeltaShare'] = np.floor(
(df['TgtValue']) / df['Price']) - df['NbShare']
c = [calc_commission_etf(n) for n in df['DeltaShare'].values]
# TBD not sure about the commission formula for both buy & sell...
for s in symbol_list:
n = df.loc[s, 'DeltaShare']
if n > 0:
print(" Buy {} of {}".format(n, s))
a.delta_cash(-n * df.loc[s, 'Price'])
df.loc[s, 'NbShare'] += n
#a.buy_at_market(i, s, n)
elif n < 0:
print(" Sell {} of {}".format(-n, s))
a.delta_cash(-n * df.loc[s, 'Price'])
df.loc[s, 'NbShare'] += n
#a.sell_at_market()
# Do not tolerate after all transactions are done.
if a.get_cash() < 0:
print("Error: not enough money", a.get_cash())
else:
#print("skip", i)
pass
print("Initial Cash =", initial_cash)
# Update last price
df['Price'] = [dic[s].iloc[-1]['Close'] for s in symbol_list]
print("Final Cash = ", sum(df['Price'] * df['NbShare']) + a.get_cash())
def test_virtual_account():
assert db
a = va.VirtualAccount(100000.0, db.get_all_symbol_data())
assert a
assert a.get_cash() == 100000.0
a.delta_cash(200)
assert a.get_cash() == 100200.0
a.delta_cash(-100)
assert a.get_cash() == 100100.0
assert len(a.get_all_positions()) == 0
assert len(a.get_open_positions()) == 0
assert len(a.get_close_positions()) == 0
assert len(a.get_all_positions('SPY')) == 0
assert len(a.get_open_positions('SPY')) == 0
assert len(a.get_close_positions('SPY')) == 0
a.buy_at_market(0, 'SPY', 100)
assert len(a.get_all_positions()) == 1
assert len(a.get_open_positions()) == 1
assert len(a.get_close_positions()) == 0
assert len(a.get_all_positions('SPY')) == 1
assert len(a.get_open_positions('SPY')) == 1
assert len(a.get_close_positions('SPY')) == 0
assert len(a.get_all_positions('IBM')) == 0
assert len(a.get_open_positions('IBM')) == 0
assert len(a.get_close_positions('IBM')) == 0
a.buy_at_market(1, 'IBM', 200)
assert len(a.get_all_positions()) == 2
assert len(a.get_open_positions()) == 2
assert len(a.get_close_positions()) == 0
assert len(a.get_all_positions('SPY')) == 1
assert len(a.get_open_positions('SPY')) == 1
assert len(a.get_close_positions('SPY')) == 0
assert len(a.get_all_positions('IBM')) == 1
assert len(a.get_open_positions('IBM')) == 1
assert len(a.get_close_positions('IBM')) == 0
a.sell_at_market(a.get_open_positions()[0], 12)
assert len(a.get_all_positions()) == 2
assert len(a.get_open_positions()) == 1
assert len(a.get_close_positions()) == 1
assert len(a.get_all_positions('SPY')) == 1
assert len(a.get_open_positions('SPY')) == 0
assert len(a.get_close_positions('SPY')) == 1
assert len(a.get_all_positions('IBM')) == 1
assert len(a.get_open_positions('IBM')) == 1
assert len(a.get_close_positions('IBM')) == 0
a.sell_at_market(a.get_open_positions()[0], 13)
assert len(a.get_all_positions()) == 2
assert len(a.get_open_positions()) == 0
assert len(a.get_close_positions()) == 2
assert len(a.get_all_positions('SPY')) == 1
assert len(a.get_open_positions('SPY')) == 0
assert len(a.get_close_positions('SPY')) == 1
assert len(a.get_all_positions('IBM')) == 1
assert len(a.get_open_positions('IBM')) == 0
assert len(a.get_close_positions('IBM')) == 1