-
Notifications
You must be signed in to change notification settings - Fork 0
/
simulate_etf.py
85 lines (63 loc) · 2.25 KB
/
simulate_etf.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
import sys
import matplotlib.pyplot as plt
import rebalancer
sys.path.insert(0, '../etf_data')
from etf_data_loader import load_all_data_from_file2
sys.path.insert(0, '../buy_hold_simulation')
import bah_simulator as bah
# pc_list = [0.01, 0.02, 0.04, 0.06, 0.08, 0.1, 0.2, 0.3, 0.4, 0.5]
pc_list = [.08, 0.1]
def interpet_results(reb_inv_lis, bah_inv, pc_list):
legends = []
for pc, reb_inv in zip(pc_list, reb_inv_list):
plt.plot(reb_inv.history, label='rebalance ' + str(pc))
legends.append('rebalance ' + str(pc))
plt.plot(bah_inv.history, color='black', label='b&h')
plt.plot(bah_inv.invested_history, label='invested')
legends.append('b&h')
legends.append('invested')
plt.legend(legends, loc='upper left')
plt.title('absolute')
plt.show()
legends = []
for pc, reb_inv in zip(pc_list, reb_inv_list):
plt.plot(reb_inv.ror_history, label='rebalance ' + str(pc))
legends.append('rebalance ' + str(pc))
plt.plot(bah_inv.ror_history, color='black', label='b&h')
legends.append('b&h')
legends.append('invested')
plt.legend(legends, loc='upper left')
plt.title('ror')
plt.show()
start_date = '1993-01-01'
end_date = '2018-06-15'
data = load_all_data_from_file2('mil_etf_data_adj_close.csv', start_date, end_date)
etf = ['IH2O.MI', 'CL2.MI']
df_adj_close = data[etf]
plt.plot(df_adj_close)
plt.legend(df_adj_close)
plt.show()
reb_inv_list = []
for pc in pc_list:
print(pc)
rebalance_inv = rebalancer.simulate(df_adj_close, pc=pc)
reb_inv_list.append(rebalance_inv)
rebalancer.writeResults('reb', etf, df_adj_close.tail(1).as_matrix()[0], rebalance_inv)
dca = bah.DCA(30, 300.)
investor = bah.Investor(etf, [1.0], dca)
sim = bah.BuyAndHoldInvestmentStrategy(investor, 2.)
sim.invest(df_adj_close, tickets=etf)
print('B&H')
print('zisk:', investor.history[-1])
print('ror:', investor.ror_history[-1])
interpet_results(reb_inv_list, investor, pc_list)
# dca = bah.DCA(30, 300.)
# investor = bah.Investor(etf[1], [1.0], dca)
# sim = bah.BuyAndHoldInvestmentStrategy(investor, 2.)
# sim.invest(data[etf[1]], [etf[1]])
#
# print('B&H')
# print('zisk:', investor.history[-1])
# print('ror:', investor.ror_history[-1])
#
# interpet_results(reb_inv_list, investor, pc_list)