227 lines
11 KiB
Python
227 lines
11 KiB
Python
import numpy as np
|
|
from datetime import datetime
|
|
|
|
class BuySell_Daily:
|
|
|
|
def countYangBong(self, data, i):
|
|
count = 0
|
|
for c in range(5):
|
|
if data['open'][i-c] < data['close'][i-c]:
|
|
count += 1
|
|
return count
|
|
|
|
def getBuyPrice(self, ticker, data, data_scaled, i, BS=None):
|
|
buy_ymd, buy_price, buy_count, buy_weight, buy_type, buy_cut = None, 0, 0, 1, '', None
|
|
|
|
sub_i = None
|
|
for c in range(i-1, i-5, -1):
|
|
if 0 < BS['buy_count'][c] and 0 < BS['buy_price'][c]:
|
|
sub_i = c
|
|
break
|
|
sub_check = False
|
|
if sub_i is not None:
|
|
sub_check = True
|
|
for c in range(sub_i, i+1):
|
|
if data['close'].iloc[c+1] < BS['buy_price'][c] * 0.99:
|
|
sub_check = False
|
|
break
|
|
if sub_check:
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_type = ''
|
|
else:
|
|
tmp_buy_ymd, tmp_buy_price, tmp_buy_count, tmp_buy_type, tmp_buy_cut = self.getBuyPrice_BBAND(ticker, data, data_scaled, i, BS)
|
|
if 0 < tmp_buy_count:
|
|
buy_ymd = tmp_buy_ymd; buy_price = tmp_buy_price; buy_count = tmp_buy_count; buy_type = tmp_buy_type; buy_cut = tmp_buy_cut
|
|
tmp_buy_ymd, tmp_buy_price, tmp_buy_count, tmp_buy_type, tmp_buy_cut = self.getBuyPrice_PolyLine(ticker, data, data_scaled, i, BS)
|
|
if 0 < tmp_buy_count:
|
|
buy_ymd = tmp_buy_ymd; buy_price = tmp_buy_price; buy_count = tmp_buy_count; buy_type = tmp_buy_type; buy_cut = tmp_buy_cut
|
|
tmp_buy_ymd, tmp_buy_price, tmp_buy_count, tmp_buy_type, tmp_buy_cut = self.getBuyPrice_Slow(ticker, data, data_scaled, i, BS)
|
|
if 0 < tmp_buy_count:
|
|
buy_ymd = tmp_buy_ymd; buy_price = tmp_buy_price; buy_count = tmp_buy_count; buy_type = tmp_buy_type; buy_cut = tmp_buy_cut
|
|
|
|
return buy_ymd, buy_price, buy_count, buy_type, buy_cut
|
|
|
|
def getSellPrice(self, ticker, data, data_scaled, i, BS=None):
|
|
sell_price, sell_count, sell_type = 0, 1, ''
|
|
sell_type_list = []
|
|
|
|
#tmp_sell_price, tmp_sell_type_list = self.getSellPrice_Umbong(ticker, data, data_scaled, i, BS)
|
|
#sell_type_list += tmp_sell_type_list
|
|
|
|
#sell_price = tmp_sell_price
|
|
|
|
if 0 < len(sell_type_list) or 0 < sell_price:
|
|
sell_type = ','.join(list(set(sell_type_list)))
|
|
|
|
return sell_price, sell_count, sell_type
|
|
|
|
""""""""""""""""""
|
|
""""""""""""""""""
|
|
|
|
def getBuyPrice_BBAND(self, ticker, data, data_scaled, i, BS):
|
|
|
|
buy_ymd, buy_price, buy_count, buy_weight, buy_type, buy_cut = None, 0, 0, 1, '', None
|
|
|
|
check = False
|
|
|
|
if 60 < i:
|
|
|
|
sub_check1, sub_check2 = False, False
|
|
for c in range(i-20, i):
|
|
if not sub_check1 and data['bb_width'].iloc[i-1] < data['bb_width'].iloc[i] and data['bb_width'].iloc[i] < 5:
|
|
sub_check1 = True
|
|
if sub_check1 and not sub_check2 and data['upper_20'].iloc[i] < data['high'].iloc[i]:
|
|
sub_check2 = True
|
|
break
|
|
|
|
if sub_check1 and sub_check2:
|
|
if data_scaled['poly_120'].iloc[i-1] < data_scaled['poly_120'].iloc[i]:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_weight = 30
|
|
buy_type = 'bband'
|
|
|
|
if check:
|
|
buy_ymd = data['ymd'].iloc[i]
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
|
|
return buy_ymd, buy_price, buy_count, buy_type, buy_cut
|
|
|
|
|
|
""""""""""""""""""
|
|
""""""""""""""""""
|
|
|
|
def getBuyPrice_PolyLine(self, ticker, data, data_scaled, i, BS):
|
|
|
|
buy_ymd, buy_price, buy_count, buy_weight, buy_type, buy_cut = None, 0, 0, 1, '', None
|
|
|
|
check = False
|
|
|
|
if 60 < i:
|
|
|
|
if data_scaled['poly_60'].iloc[i-1] < 0 and data_scaled['poly_120'].iloc[i-1] < -0.003:
|
|
if data_scaled['poly_60'].iloc[i-1] <= data_scaled['poly_120'].iloc[i-1] and data_scaled['poly_120'].iloc[i] < data_scaled['poly_60'].iloc[i]:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_weight = 30
|
|
buy_type = 'poly'
|
|
|
|
|
|
if data_scaled['poly_240'].iloc[i - 1] < data_scaled['poly_240'].iloc[i] and data['slowk_240'].iloc[i] < 50:
|
|
if data['close'].iloc[i - 1] < data['avg240'].iloc[i-1] and data['avg240'].iloc[i] < data['close'].iloc[i]:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_weight = 30
|
|
buy_type = 'poly_240'
|
|
#buy_cut = data['support'].iloc[i]
|
|
|
|
if data_scaled['poly_480'].iloc[i - 1] < data_scaled['poly_480'].iloc[i] and data['slowk_480'].iloc[i] < 50:
|
|
if data['close'].iloc[i - 1] < data['avg480'].iloc[i-1] and data['avg480'].iloc[i] < data['close'].iloc[i]:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_weight = 30
|
|
buy_type = 'poly_480'
|
|
#buy_cut = data['support'].iloc[i]
|
|
|
|
if check:
|
|
buy_ymd = data['ymd'].iloc[i]
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
|
|
return buy_ymd, buy_price, buy_count, buy_type, buy_cut
|
|
|
|
def getBuyPrice_Slow(self, ticker, data, data_scaled, i, BS):
|
|
|
|
buy_ymd, buy_price, buy_count, buy_weight, buy_type, buy_cut = None, 0, 0, 1, '', None
|
|
|
|
check = False
|
|
|
|
if 5 < i:
|
|
|
|
#if data_scaled["disparity_diff_60_20_rate"].iloc[i] < -0.5:
|
|
|
|
if data_scaled["disparity_diff_60_20_rate"].iloc[i] < -0.5 and data_scaled["disparity_diff_60_20_rate"].iloc[i-1] < data_scaled["disparity_diff_60_20_rate"].iloc[i]:
|
|
|
|
if data_scaled['slowk_20'].iloc[i-1] <= data_scaled['slowd_20'].iloc[i-1] < 0:
|
|
if data_scaled['slowd_20'].iloc[i] < data_scaled['slowk_20'].iloc[i] < 0:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_type = 'slowk_20'
|
|
#buy_cut = data['support'].iloc[i]
|
|
|
|
if data_scaled['slowk_60'].iloc[i-1] <= data_scaled['slowd_60'].iloc[i-1] < 0:
|
|
if data_scaled['slowd_60'].iloc[i] < data_scaled['slowk_60'].iloc[i] < 0:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_type = 'slowk_60'
|
|
#buy_cut = data['support'].iloc[i]
|
|
|
|
if data_scaled['slowk_120'].iloc[i-1] <= data_scaled['slowd_120'].iloc[i-1] < 0:
|
|
if data_scaled['slowd_120'].iloc[i] < data_scaled['slowk_120'].iloc[i] < 0:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_type = 'slowk_120'
|
|
#buy_cut = data['support'].iloc[i]
|
|
|
|
if data_scaled['slowk_240'].iloc[i-1] <= data_scaled['slowd_240'].iloc[i-1] < 0:
|
|
if data_scaled['slowd_240'].iloc[i] < data_scaled['slowk_240'].iloc[i] < 0:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_type = 'slowk_240'
|
|
#buy_cut = data['support'].iloc[i]
|
|
|
|
if data['slowk_480'].iloc[i - 1] < data['slowd_480'].iloc[i - 1] < 40:
|
|
if data['slowd_480'].iloc[i] < data['slowk_480'].iloc[i]:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_type = 'slowk_1440'
|
|
#buy_cut = data['support'].iloc[i]
|
|
|
|
if data['avg240'].iloc[i - 1] < data['avg240'].iloc[i]:
|
|
if data_scaled['poly_480'].iloc[i - 1] <= 0 and 0 < data_scaled['poly_480'].iloc[i]:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_type = 'poly_480'
|
|
#buy_cut = data['support'].iloc[i]
|
|
|
|
if data_scaled['poly_240'].iloc[i - 1] < data_scaled['poly_240'].iloc[i] and data['slowk_240'].iloc[i] < 50:
|
|
if data['close'].iloc[i - 1] < data['avg720'].iloc[i-1] and data['avg720'].iloc[i] < data['close'].iloc[i]:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_type = 'poly_240'
|
|
#buy_cut = data['support'].iloc[i]
|
|
|
|
if data_scaled['poly_480'].iloc[i - 1] < data_scaled['poly_480'].iloc[i] and data['slowk_480'].iloc[i] < 50:
|
|
if data['close'].iloc[i - 1] < data['avg1440'].iloc[i-1] and data['avg1440'].iloc[i] < data['close'].iloc[i]:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_type = 'poly_480'
|
|
#buy_cut = data['support'].iloc[i]
|
|
|
|
if data["slowk_10"].iloc[i-1] < data["slowk_10"].iloc[i] < 20:
|
|
check = True
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
buy_type = 'slowk_10'
|
|
# buy_cut = data['support'].iloc[i]
|
|
|
|
if check:
|
|
buy_ymd = data['ymd'].iloc[i]
|
|
buy_price = data['close'].iloc[i] - 2 * ticker['unit']
|
|
buy_count = (buy_weight * ticker['MAX_BUY']) / data['close'].iloc[i]
|
|
|
|
return buy_ymd, buy_price, buy_count, buy_type, buy_cut |