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dc_kdj_lib.py
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import dc_lib as dl
import numpy as np
import pandas as pd
import dc_api_lib as api
import os
import coins
from collections import namedtuple
cur_path = os.path.dirname(os.path.abspath(__file__))
def get_kdj(coin_id, df,sell_ratio = 1):
close = df.close
high = df.high
low = df.low
date = close.index.to_series()
ndate = len(date)
period_high = pd.Series(np.zeros(ndate - 8), index=date.index[8:])
period_low = pd.Series(np.zeros(ndate - 8), index=date.index[8:])
rsv = pd.Series(np.zeros(ndate - 8), index=date.index[8:])
for j in range(8, ndate):
period = date[j - 8:j + 1]
i = date[j]
period_high[i] = high[period].max()
period_low[i] = low[period].min()
rsv[i] = 100 * (close[i] - period_low[i]) / (period_high[i] - period_low[i])
period_high.name = 'period_high'
period_low.name = 'period_low'
rsv.name = 'rsv'
c1_rsv = pd.DataFrame([close, rsv]).transpose()
rsv1 = pd.Series([50, 50], index=date[6:8]).append(rsv)
rsv1.name = 'RSV'
k_value = pd.Series(0.0, index=rsv1.index)
k_value[0] = 50
for i in range(1, len(rsv1)):
k_value[i] = 2 / 3 * k_value[i - 1] + rsv1[i] / 3
k_value.name = 'K-Value'
d_value = pd.Series(0.0, index=rsv1.index)
d_value[0] = 50
for i in range(1, len(rsv1)):
d_value[i] = 2 / 3 * d_value[i - 1] + k_value[i] / 3
d_value.name = 'D-Value'
j_value = 3 * k_value - 2 * d_value
j_value.name = "J-Value"
j_value.head()
k_signal = k_value.apply(lambda x: -1 if x > 80*sell_ratio else 1 if x < 20 else 0)
d_signal = d_value.apply(lambda x: -1 if x > 80*sell_ratio else 1 if x < 20 else 0)
kd_signal = k_signal + d_signal
kd_signal.name = 'KD-Signal'
kd_signal[kd_signal >= 1] = 1
kd_signal[kd_signal <= -1] = -1
kdj_data = namedtuple('kdj_data',['close','rsv','k_value','d_value','j_value','kd_signal'])
return kdj_data(close,rsv,k_value,d_value,j_value,kd_signal)
# return {"close": close, "rsv": rsv, "k_value": k_value, "d_value": d_value, "j_value": j_value,
# "kd_signal": kd_signal}
import json
def get_conf(coin_id):
config_set = json.load(open('%s/strategy/kdj/kdj_conf.json'%cur_path,'r'))
rst = list(filter(lambda x:x['coin_id']==coin_id,config_set))
if not rst:
return None
return rst[0]
def get_stock_limit(coin_id,stocks,config):
stock_ratio = config['stock_ratio']
appraisement = 0
for s in stocks:
appraisement+=s['appraisement']
stock_limit = appraisement * stock_ratio
return stock_limit
def get_stock_remain(coin_id,stocks,config):
stock_limit = get_stock_limit(coin_id,stocks,config)
coin_stock = api.get_coin_stock(coin_id,stocks)
return max(0,stock_limit-coin_stock)
def get_trade_usdt(type,coin_id,stocks,config):
tradeable = get_tradeable(type,coin_id,config)
if not tradeable:
return 0
trade_ratio = config['%s_ratio'%type]
stock_limit = get_stock_limit(coin_id,stocks,config)
trade_usdt = stock_limit*trade_ratio
return trade_usdt
def get_tradeable(type,coin_id,config):
return config.get('%s_switch'%type,False)
def get_trade_config(coin_id,stocks,kdj_config):
#获取买入金额
buy_usdt = get_trade_usdt('buy',coin_id,stocks,kdj_config)
#获取卖出金额
sell_usdt = get_trade_usdt('sell',coin_id,stocks,kdj_config)
#获取仓位上限
stock_limit = get_stock_limit(coin_id,stocks,kdj_config)
#获取仓位余额
stock_remain = get_stock_remain(coin_id,stocks,kdj_config)
#获取当前仓位
stock = api.get_coin_stock(coin_id,stocks)
#设置KD卖出权重，剩余仓位大于0.15时为1，否则为0.7，增加卖出机会
kdj_sell_ratio = 1 if stock_limit and stock_remain/stock_limit>0.17 else 0.85
trade_config = namedtuple('config',['buy_usdt','sell_usdt','stock_limit','stock_remain','stock','kdj_sell_ratio'])
return trade_config(buy_usdt,sell_usdt,stock_limit,stock_remain,stock,kdj_sell_ratio)
# trade_config = {
# 'buy_usdt':buy_usdt,
# 'sell_usdt':sell_usdt,
# 'stock_limit':stock_limit,
# 'stock_remain':stock_remain,
# 'stock':stock,
# 'kdj_sell_ratio':kdj_sell_ratio
# }
# return trade_config
def check_trade(coin_id,stocks,df,ma30_data=None,kdj_data=None,trade_config=None):
kdj_config = get_conf(coin_id)
coin_code = coins.get_code(coin_id)
if not trade_config:
trade_config = get_trade_config(coin_id,stocks,kdj_config)
if dl.account != 'mock':
#取消当前未完成的挂单
api.cancel_all_orders_by_coin_id(coin_id)
buy_usdt = trade_config.buy_usdt
sell_usdt = trade_config.sell_usdt
stock_limit = trade_config.stock_limit
stock_remain = trade_config.stock_remain
stock = trade_config.stock
kdj_sell_ratio = trade_config.kdj_sell_ratio
# buy_usdt=float(trade_config.get('buy_usdt')),
# sell_usdt=trade_config['sell_usdt'],
# stock_limit=trade_config['stock_limit'],
# stock_remain=trade_config['stock_remain'],
# stock=trade_config['stock'],
# kdj_sell_ratio=trade_config['kdj_sell_ratio']
# print(type(trade_config))
# print(trade_config)
# print(type(buy_usdt))
# print(buy_usdt)
#获取KDJ序列
if kdj_data is None:
kdj_data = get_kdj(coin_id,df,sell_ratio=kdj_sell_ratio)
#获取MA30序列
if ma30_data is None:
ma30_data = dl.get_mean(df,30)
#获取交易信号集
signal_arr = kdj_data.kd_signal
#获取最新信号
signal = signal_arr[-1]
#获取最新收盘价
price = kdj_data.close[-1].item()
#获取最新MA30
ma30 = ma30_data[-1].item()
#计算买卖量系数并应用
trade_volume_factor = 1 + abs(price-ma30)*20/ma30
buy_usdt *= trade_volume_factor
sell_usdt *= trade_volume_factor
if dl.account != 'mock':
print('coin_code:%s buy_usdt:%.2f sell_usdt:%.2f factor:%.4f sell_ratio:%.2f stock:%.2f limit:%.2f remain:%.2f price:%f'%(coin_code,round(buy_usdt,2),round(sell_usdt,2),round(trade_volume_factor,4),round(kdj_sell_ratio,2),round(stock,2),round(stock_limit,2),round(stock_remain,2),price))
trade = namedtuple('trade',['action','coin_id','price','volume'])
#买入信号
if signal == 1:
#如果还有可用仓位则买入
if buy_usdt and stock_remain:
volume = min(buy_usdt/price,stock_remain)
return trade('buy',coin_id,price,volume)
# return('buy',coin_id,price,volume)
#卖出信号
elif signal == -1:
if sell_usdt:
usable = None
for s in stocks:
if s['coin_id']==coin_id:
usable = s['usable']
if usable != None:
price*=0.998
volume = min(sell_usdt/price,usable)
if volume * price > 1.2:
return trade('sell',coin_id,price,volume)
# return('sell',coin_id,price,volume)
return None