def get_profit(datadata, datalimits):
[
data, data_length, body_sizes, shadow_sizes, body_shadow_ratios,
reversals, increase_data, run_function_data
] = datadata
[
body_lim, shadow_lim, ratio_lim, prev_run_lim, prev_diff_lim,
next_run_lim, next_diff_lim
] = datalimits
# 0 for sell, 1 for buy
last_trade = 0
trade_array = [0] * data_length
for i in range(datadata[1]):
if (last_trade == 0):
if ((reversals[i] == 1) and (increase_data[i] == 1)
and (body_sizes[i] <= body_lim)
and (shadow_sizes[i] <= shadow_lim)
and (body_shadow_ratios[i] <= ratio_lim)
and (run_function_data[i][1] >= prev_run_lim)
and (run_function_data[i][2] >= prev_diff_lim)
and (run_function_data[i][3] >= next_run_lim)
and (run_function_data[i][4] >= next_diff_lim)):
trade_array[i] += 1
last_trade = 1
elif (last_trade == 1):
if (reversals[i] == 1):
trade_array[i] += 2
last_trade = 0
[profit, profit_array] = tradesim.sim_trade(data, trade_array)
return (profit)
def get_profit(datadata, datalimits, combined_trade_array):
[
jdata, data_length, body_sizes, shadow_sizes, body_shadow_ratios,
reversals, increase_data, run_function_data
] = datadata
[body_lim, shadow_lim, ratio_lim, prev_run_lim, prev_diff_lim] = datalimits
# 0 for sell, 1 for buy
last_trade = 0
trade_array = [0] * data_length
for i in range(datadata[1]):
if (last_trade == 0):
if ((reversals[i] == 1) and (increase_data[i] == 1)
and (body_sizes[i] <= body_lim[1])
and (body_sizes[i] >= body_lim[0])
and (shadow_sizes[i] <= shadow_lim[1])
and (shadow_sizes[i] >= shadow_lim[0])
and (body_shadow_ratios[i] <= ratio_lim[1])
and (body_shadow_ratios[i] >= ratio_lim[0])
and (run_function_data[i][1] <= prev_run_lim[1])
and (run_function_data[i][1] >= prev_run_lim[0])
and (run_function_data[i][2] <= prev_diff_lim[1])
and (run_function_data[i][2] >= prev_diff_lim[0])):
trade_array[i] += 1
last_trade = 1
elif (last_trade == 1):
if (reversals[i] == 1):
trade_array[i] += 2
last_trade = 0
[profit, profit_array] = tradesim.sim_trade(jdata, trade_array)
if profit > 1:
temp_combined_trade_array = [None] * data_length
for i in range(data_length):
if trade_array[i] > 0:
temp_combined_trade_array[i] = trade_array[i]
[com_profit,
com_profit_array] = tradesim.sim_trade(jdata, combined_trade_array)
[temp_profit,
temp_profit_array] = tradesim.sim_trade(jdata,
temp_combined_trade_array)
if temp_profit > com_profit:
combined_trade_array = temp_combined_trade_array
return ([profit, combined_trade_array])
import tradesim
import csv
trade_filepath = '../../data/tradedata/Heikenashispintopsbuyorsell.csv'
with open(trade_filepath, 'rb') as trade_file:
trade_array = []
trade_file_data = csv.reader(trade_file, delimiter=',')
for row in trade_file_data:
trade_array.append(int(row[0]))
data_filepath = '../../data/hacandles.csv'
data = getanalysis.import_j_candles(data_filepath)
[profit, profit_array] = tradesim.sim_trade(data, trade_array)
percent_profit = (profit - 1) * 100
print('Heikin Ashi spinning tops')
print('Profit: ' + str(percent_profit) + '%')
print('Max profit: ' + str((max(profit_array)-1)*100) + '%\n')
trade_filepath = '../../data/tradedata/ha-candles-bear-and-bull-dojis.csv'
with open(trade_filepath, 'rb') as trade_file:
trade_array = []
trade_file_data = csv.reader(trade_file, delimiter=',')
for row in trade_file_data:
trade_array.append(int(row[0]))
[profit, profit_array] = tradesim.sim_trade(data, trade_array)
percent_profit = (profit - 1) * 100
print('Heikin Ashi dojis')
print('Profit: ' + str(percent_profit) + '%')
for prev_diff_i2 in range(n_iter -
prev_diff_i):
prev_diff_lim[1] = prev_diff_array[(
prev_diff_i + prev_diff_i2)]
datalimits = [
body_lim, shadow_lim, ratio_lim,
prev_run_lim, prev_diff_lim
]
[this_profit,
combined_trade_array] = get_profit(
datadata, datalimits,
combined_trade_array)
profit_array.append(this_profit)
profit_stuff_array.append([
body_i, shadow_i, ratio_i,
prev_run_i, prev_diff_i
])
j += 1
[combined_profit,
combined_profit_array] = tradesim.sim_trade(data, combined_trade_array)
print('100%')
endtime = time.time()
timetaken = endtime - starttime
print(str(timetaken) + 's')
print(max(profit_array))
print(combined_profit)
for i in range(n):
this_set[i] = tradesim_n.sim_trade(jdata, trade_data[jiter], i + 1)
profit_data[jiter] = this_set
this_max_profit_data = max(this_set)
this_max_sell_after = this_set.index(max(this_set)) + 1
max_profit_data[jiter] = this_max_profit_data
max_sell_after[jiter] = this_max_sell_after
combined_trade_array = [0] * data_length
this_profit = 1.0
for i in range(len(trade_data)):
if max_profit_data[i] > 1.0:
# Try adding trade data together to get more profit
trial_combined_trade_array = combine_profits(combined_trade_array,
trade_data[i],
max_sell_after[i])
trial_profit = tradesim.sim_trade(jdata, trial_combined_trade_array)
if trial_profit > this_profit:
all_cents[i].append(trial_profit - this_profit)
all_cents[i].append(trial_profit)
all_cents[i].append(jcoefficient_data[i][0])
all_profitable_cents.append(all_cents[i])
this_profit = trial_profit
combined_trade_array = trial_combined_trade_array
percent_profit = (this_profit - 1) * 100
print('Japanese candles: ' + str(percent_profit) + '%')
# Save combined_trade_array to csv file
combined_filepath = '../data/jprofits.csv'
with open(combined_filepath, 'wb') as jprofit_file:
j_writer = csv.writer(jprofit_file, delimiter=',')
for profit_row in all_profitable_cents:
j_writer.writerow(profit_row)