def analysis_daily(position):
# code_list = get_stock('sha') + get_stock('sza')
code_list = filter_stk1()
result = []
for code in code_list:
kline = np.load('data/daily/{}'.format(code + '.npy'))
if kline.shape[0] < 120:
continue
s_open = kline[:, 2].astype(np.float)[:100]
s_high = kline[:, 3].astype(np.float)[:100]
s_low = kline[:, 4].astype(np.float)[:100]
s_close = kline[:, 5].astype(np.float)[:100]
s_pre_close = kline[:, 6].astype(np.float)[:100]
s_vol = kline[:, 9].astype(np.float)[:100]
s_amount = (kline[:, 10].astype(np.float) * 1000)[:100]
sma_close_5, sma_close_10, sma_close_20 = indicator.sma(
kline, 5, 10, 20)
if s_close[position] > s_open[position] > 0 and s_amount[
position] > 10000 * 10000:
s_zf = (s_high - s_low) / s_low * 100
s_entity = (s_close - s_open) / s_open * 100
s_max = (s_close - s_low) / s_low * 100
s_down = (s_pre_close - s_low) / s_pre_close * 100
if s_zf[position] > 5 and s_max[position] > 3:
if s_low[position] <= sma_close_5[position] <= s_high[
position] or s_low[position] <= sma_close_10[
position] <= s_high[position] or s_low[
position] <= sma_close_20[position] <= s_high[
position]:
print(code)
result.append(code)
return result
def t_all(kline, position):
# 日线条数要大于120条， 6个月
if kline.shape[0] < 30:
return False
s_open = kline[:, 2].astype(np.float)[:100]
s_high = kline[:, 3].astype(np.float)[:100]
s_low = kline[:, 4].astype(np.float)[:100]
s_close = kline[:, 5].astype(np.float)[:100]
s_pre_close = kline[:, 6].astype(np.float)[:100]
s_vol = kline[:, 9].astype(np.float)[:100]
s_amount = (kline[:, 10].astype(np.float) * 1000)[:100]
sma_vol_5, sma_vol_10, sma_vol_20 = indicator.sma_vol(kline, 5, 10, 20)
sma_close_5, sma_close_10, sma_close_20 = indicator.sma(kline, 5, 10, 20)
# 成交额要大于1.5亿
if s_amount[position] < 0.8 * 100000000:
return False
# 开盘价要小于于收盘价
if s_open[position] > s_close[position]:
return False
s_zf = (s_high - s_low) / s_low * 100
s_entity = (s_close - s_open) / s_open * 100
s_max = (s_close - s_low) / s_low * 100
s_down = (s_pre_close - s_low) / s_pre_close * 100
# 不考虑40元以上的股票
if sma_close_5[position] > 40:
return False
# 不考虑没有波动的股票
if s_zf[position] < 4 or s_max[position] < 3 or s_entity[position] < 2.5:
return False
# 若上涨幅度没有超过前面两个k线的高度， 不考虑
# if s_high[position] < np.max(s_open[position + 1: position + 3]):
# return False
# if s_high[position] < np.max(s_close[position + 1: position + 3]):
# return False
# 突然爆量的涨幅不要
if s_vol[position] / s_vol[position + 1] > 2.5:
return False
if s_vol[position] >= np.max(s_vol[position:position + 15]):
return False
# 没有穿过均线的不要
if s_low[position] > max(sma_close_10[position], sma_close_20[position]):
return False
if s_high[position] < min(sma_close_10[position], sma_close_20[position]):
return False
for amount in s_amount[0:30]:
if amount < 3000 * 10000:
return False
return True
def analysis_week(position):
code_list = get_stock('sha')
for code in code_list:
kline = np.load('data/week/{}'.format(code + '.npy'))
if kline.shape[0] < 120:
continue
close = kline[:2].astype(np.float)[:100]
_open = kline[:3].astype(np.float)[:100]
high = kline[:4].astype(np.float)[:100]
low = kline[:5].astype(np.float)[:100]
pre_close = kline[:6].astype(np.float)[:100]
vol = kline[:9].astype(np.float)[:100]
amount = kline[:10].astype(np.float) * 1000 [:100]
sma_close_5, sma_close_10, sma_close_20 = indicator.sma(
kline, 5, 10, 20)
if amount[position] > 1 * 100000000:
pass
def good_d_line(code, position_range):
kline = np.load('data/daily/{}'.format(code + '.npy'))
if kline.shape[0] < 120:
return None
s_open = kline[:, 2].astype(np.float)[:100]
s_high = kline[:, 3].astype(np.float)[:100]
s_low = kline[:, 4].astype(np.float)[:100]
s_close = kline[:, 5].astype(np.float)[:100]
s_pre_close = kline[:, 6].astype(np.float)[:100]
s_vol = kline[:, 9].astype(np.float)[:100]
s_amount = (kline[:, 10].astype(np.float) * 1000)[:100]
s_zf = (s_high - s_low) / s_low * 100
s_entity = (s_close - s_open) / s_open * 100
s_max = (s_close - s_low) / s_low * 100
s_down = (s_pre_close - s_low) / s_pre_close * 100
sma_close_5, sma_close_10, sma_close_20 = indicator.sma(kline, 5, 10, 20)
result = []
for position in range(position_range[0], position_range[1]):
score = 0
if s_close[position] > s_open[position] and s_amount[
position] > 10000 * 10000:
score = 0.5
if s_low[position] < sma_close_5[position] < s_high[position]:
score += 2
if s_low[position] < sma_close_10[position] < s_high[position]:
score += 2
if s_low[position] < sma_close_20[position] < s_high[position]:
score += 10
if score >= 2:
if s_zf[position] > 5 or s_entity[position] > 3:
score += 2
else:
score = 0
if score < 0:
score = 0
if s_close[position_range[0]] > sma_close_5[position_range[0]]:
score = 0
result.append(score)
return result
def buy_point():
result = []
code_list = get_stock('2020-11-05.txt') + get_stock(
'2020-11-04.txt') + get_stock('2020-11-03.txt') + get_stock(
'2020-11-02.txt')
code_list = [code for code in code_list if hasDayFile(code)]
for code in code_list:
kline = np.load('data/daily/{}'.format(code + '.npy'),
allow_pickle=True)
s_open = kline[:, 2].astype(np.float)[:100]
s_high = kline[:, 3].astype(np.float)[:100]
s_low = kline[:, 4].astype(np.float)[:100]
s_close = kline[:, 5].astype(np.float)[:100]
s_pre_close = kline[:, 6].astype(np.float)[:100]
s_vol = kline[:, 9].astype(np.float)[:100]
s_amount = (kline[:, 10].astype(np.float) * 1000)[:100]
sma_vol_5, sma_vol_10, sma_vol_20 = indicator.sma_vol(kline, 5, 10, 20)
sma_close_5, sma_close_10, sma_close_20 = indicator.sma(
kline, 5, 10, 20)
if s_close[0] < sma_close_10[0] or s_close[0] < sma_close_20[0]:
result.append(code)
return result
def t2(kline, position):
# 日线条数要大于120条， 6个月
if kline.shape[0] < 120:
return False
s_open = kline[:, 2].astype(np.float)[:100]
s_high = kline[:, 3].astype(np.float)[:100]
s_low = kline[:, 4].astype(np.float)[:100]
s_close = kline[:, 5].astype(np.float)[:100]
s_pre_close = kline[:, 6].astype(np.float)[:100]
s_vol = kline[:, 9].astype(np.float)[:100]
s_amount = (kline[:, 10].astype(np.float) * 1000)[:100]
sma_vol_5, sma_vol_10, sma_vol_20 = indicator.sma_vol(kline, 5, 10, 20)
sma_close_5, sma_close_10, sma_close_20 = indicator.sma(kline, 5, 10, 20)
if s_close[position] > 40:
return False
if s_amount[position] < 1 * 100000000:
return False
s_entity = (s_close - s_open) / s_open * 100
if s_entity[position] < 3:
return False
if s_close[position] < s_pre_close[position]:
return False
return True
def test2():
kline = np.load('data/daily/600000.npy')
sma_close_5 = indicator.sma(kline, 5)[0]
print(sma_close_5)