def backtest_start(commobj, start_date: datetime.datetime, end_date: datetime.datetime):
"""
回测
"""
rdchicang = redisRW.redisrw(redisRW.db_backtest_chicang)
rdchicang.del_db()
rddaysell = redisRW.redisrw(redisRW.db_day_sell)
rddaysell.del_db()
# 日线回测
commobj.testbar = True
zbstrategy = zbStrategy.Strategy(None)
while start_date.date() <= end_date.date():
if start_date.weekday() in range(5):
# 选股
zbstrategy.stock_select(rdchicang, start_date)
get_ticks_from_xg_and_start_backtest(commobj, start_date)
#input('按任意键继续...')
start_date += datetime.timedelta(days=1)
ex_buy_count = 0
day_sj_zdf_count = Decimal(0)
ex_zdf_count = Decimal(0)
sz_count = 0
xd_count = 0
ex_sz_count = 0
ex_xd_count = 0
datas = []
max_zyk = None
max_huice = None
for d in rddaysell.read_l_date_dec_json('daysell', 0, -1):
ex_buy_count += d['buy_count']
ex_sz_count += d['sz']
ex_xd_count += d['xd']
zdf = d['sj_zdf_count']
if (max_zyk is None) or d['zyk'] > max_zyk:
max_zyk = d['zyk']
huice = d['zyk'] - max_zyk
if (max_huice is None) or huice < max_huice:
max_huice = huice
if zdf > 0:
sz_count += 1
else:
xd_count += 1
day_sj_zdf_count += zdf
ex_zdf_count += d['ex_zdf_count']
datas.append({
'datetime': d['datetime'],
'ex_buy_count': ex_buy_count,
'ex_zdf_count': float(str(ex_zdf_count.quantize(Decimal('0.01'), ROUND_HALF_UP))),
'day_sj_zdf_count': float(str(day_sj_zdf_count.quantize(Decimal('0.01'), ROUND_HALF_UP))),
'zyk': float(str(d['zyk'].quantize(Decimal('0.01'), ROUND_HALF_UP))),
'day_sz': sz_count,
'day_xd': xd_count,
'ex_sz_count': ex_sz_count,
'ex_xd_count': ex_xd_count
})
ply.write_html_tol('./WebServer/html/charts.html', datas, max_huice)
def fupan():
# 选股
zbstrategy = zbStrategy.Strategy(None)
zbstrategy.stock_select(redisRW.redisrw(redisRW.db_chicang))
tk_date = datetime.datetime.now()
# 获取最新一天的ticks，并启动回测
commobj = comm.commObj(redisRW.redisrw(redisRW.db_backtest_chicang),
1,
is_backtest=True)
getticks = runQuotation.get_ticks_from_xg_and_start_backtest(
commobj, tk_date)
while not getticks:
print(tk_date, '没有ticks，尝试前一天。')
tk_date -= datetime.timedelta(days=1)
getticks = runQuotation.get_ticks_from_xg_and_start_backtest(
commobj, tk_date)
print('策略提示', '将买入标记重点的股票。')
return True
def __init__(self, commObj, xg_data):
self.ticks = []
self.xg_data = xg_data
self.code = xg_data['code']
self.name = xg_data['name']
self.hangye = xg_data['hangye']
self.chicang = xg_data['chicang']
if self.chicang:
self.chicang['datetime'] = datetime.datetime.strptime(
self.chicang['datetime'], '%Y%m%d %H:%M:%S')
self.bz = xg_data['bz']
self.price_zs = xg_data['price_zs']
self.price_zy = xg_data['price_zy']
self.zs_date = xg_data['zs_date']
self.zy_date = xg_data['zy_date']
self.strategy = zbStrategy.Strategy(commObj)
self.rdrealtimetick = redisRW.redisrw(redisRW.db_realtime_tick)
self.rdmainquotation = redisRW.redisrw(redisRW.db_mainquotaion)
self.history_data = zbBase.history_calculate_by_kline(xg_data)
def backtest_start(common, start_date: datetime.datetime,
end_date: datetime.datetime):
"""
回测
"""
rdchicang = redisRW.redisrw(redisRW.db_backtest_chicang)
rdchicang.del_db()
rddaysell = redisRW.redisrw(redisRW.db_day_sell)
rddaysell.del_db()
codes_bk = comm.get_codes_bk()
if not codes_bk:
print('股票代码列表获取失败。')
return
zbstrategy = zbStrategy.Strategy(None)
while start_date.date() <= end_date.date():
if start_date.weekday() in range(5):
# 选股
zbstrategy.stock_select(common['b'], codes_bk, start_date)
get_ticks_from_xg_and_start_backtest(common, start_date)
#input('按任意键继续...')
start_date += datetime.timedelta(days=1)
ex_sz_count = 0
ex_xd_count = 0
ex_sell_count = 0
datas = []
zyk_list = []
max_huice = 0
max_zc = None
day_sz_count = 0
day_xd_count = 0
last_zc = common['init_balance']
for d in rddaysell.read_l_date_dec_json('daysell', 0, -1):
ex_sell_count += d['sell_count']
ex_sz_count += d['sz']
ex_xd_count += d['xd']
zyk_list.append(d['zyk'])
if max_zc is None:
max_zc = d['zc']
max_zc = max(max_zc, d['zc'])
max_huice = max(max_huice, (1 - d['zc'] / max_zc) * 100)
if d['zc'] < last_zc:
day_sz_count += 1
else:
day_xd_count += 1
last_zc = d['zc']
datas.append({
'datetime': d['datetime'],
'ex_sell_count': ex_sell_count,
'ex_sz_count': ex_sz_count,
'ex_xd_count': ex_xd_count,
'day_sz_count': day_sz_count,
'day_xd_count': day_xd_count,
'zc': float(str(d['zc'])),
})
if len(datas) == 0:
print('没有交易数据')
return
zyk_std = float(str(np.std(zyk_list)))
m_data = datas[len(datas) - 1]
tol_days = (m_data['datetime'] - datas[0]['datetime']).days
tol_days = max(1, tol_days)
annualized = float(str(d['zyk'])) / tol_days * 365
sharperatio = 0
if zyk_std > 0:
sharperatio = annualized / zyk_std
ply.write_html_tol(
os.path.join(current_path, '..', 'WebServer', 'html', 'charts.html'),
datas, float(str(d['zyk'])), max_huice, annualized, sharperatio)