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蜡烛图形态

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ChannelCMT edited this page Jun 4, 2019 · 1 revision

蜡烛图形态

用TA_Lib寻找蜡烛图特征

目录

  • 蜡烛图是什么？

  • 蜡烛图的两大用途是什么？

  • 常见蜡烛图是怎么计算的？

  • 蜡烛图如何用图表显示，并用TA_Lib寻找蜡烛图？

蜡烛图是什么？

蜡烛图又称为K线图，主要包含四个数据，即开盘价、最高价、最低价、收盘价，所有的蜡烛图都是围绕这四个数据展开，反映大势的状况和价格信息。如果把每日的K线图放在一张图中，就能得到日K线图，同样也可画出周K线图、月K线图。

蜡烛图的两大用途是什么？

  1. 判断反转信号
  2. 判断持续信号

常见蜡烛图是怎么计算的？

1. 大阳线: 涨幅大于5%，上下影线小于1.8%

Close/Open>1.05

High/Low < Close/Open+0.018

2. 大阴线： 跌幅大于5%， 上下影线小于1.8%

Open/Close > 1.05

High/Low < Open/Close+0.018

3.下影线

(Min(Close,Open)-Low)/(High-Low)>0.667

4. 上影线

(High-Max(Close,Open))/(High-Low)>0.667

5.十字星

Close-Open<Abs(0.001)

High-Low>0.001

6. 缺口Gap

open[-1]-close[-2]>0.01

http://www.stockstowatch.com/candle-indicator/

找出蜡烛图

import warnings

warnings.filterwarnings('ignore')
from jaqs_fxdayu.data.dataservice import LocalDataService
ds = LocalDataService()
from time import time
## 加freq参数

start = time()
path = r'../min_data/VnTrader_1Min_Db'
props = {'fields': 'open,high,low,close,volume','symbol': 'BTCUSDT:binance', 'freq': '8H',
             'start_date':20180801000000}

Time_dict = ds.bar_reader(path,props)
print(time()-start)
5.192053318023682

data1H = Time_dict.set_index('datetime')
from jaqs_fxdayu.data.hf_dataview import HFDataView

dv1H = HFDataView()
dv1H.create_init_dv(Time_dict.set_index(["trade_date","symbol"]))
Initialize dataview success.

判断低位

def location(df):
    Location = (df.close-df.low.rolling(50).min())/(df.high.rolling(50).max()-df.low.rolling(50).min())*100
    return Location

Location = location(data1H)
# Location

找出大阳线

观察蜡烛图和成交量的关系，找到信号。

import matplotlib.pyplot as plt
import mpl_finance as mpf

def draw_candle(candle, scatterX, scatterY):
    fig, (ax, ax1) = plt.subplots(2,1,sharex=True, figsize=(18,10))
    ax.grid(True)
    mpf.candlestick_ohlc(ax, candle, width=0.3, colorup='r', colordown='g',alpha=1.0)
    ax.scatter(scatterX, scatterY, color='b', s=100, marker='^')
    ax.xaxis_date ()
    ax1.bar(data1H.index, data1H.volume)
    plt.show()
Big_Up = dv1H.add_formula('Big_Up','If((close/open>1.02) && (high/low<(close/open+0.02)), 100, 0)', add_data=True)
Big_Up[Big_Up['BTCUSDT:binance']==100]
symbol BTCUSDT:binance
trade_date
20180813080000 100.0
20180815000000 100.0
20180815080000 100.0
20180817080000 100.0
20180821080000 100.0
20180825000000 100.0
20180828000000 100.0
20180909160000 100.0
20180921080000 100.0 
dataBigUp = dv1H.get_ts('Big_Up', date_type='datetime')
dataBigUp[dataBigUp['BTCUSDT:binance']==100].index
DatetimeIndex(['2018-08-13 08:00:00', '2018-08-15 00:00:00',
               '2018-08-15 08:00:00', '2018-08-17 08:00:00',
               '2018-08-21 08:00:00', '2018-08-25 00:00:00',
               '2018-08-28 00:00:00', '2018-09-09 16:00:00',
               '2018-09-21 08:00:00'],
              dtype='datetime64[ns]', name='trade_date', freq=None)

scatterBigUpX = dataBigUp[dataBigUp['BTCUSDT:binance']==100].index
scatterBigUpY = data1H.loc[scatterBigUpX].low-100

设置candle

from matplotlib.pylab import date2num

data1H['candleTime'] = list(map(date2num, data1H.index))
candle = data1H.reindex_axis(["candleTime", "open", "high", "low", "close"], 1).values
draw_candle(candle, scatterBigUpX, scatterBigUpY)

# dataBigUp[dataBigUp['BTCUSDT:binance']==100]

找出下影线

(Min(Close,Open)-Low)/(High-Low)>0.667

观察蜡烛图和成交量的关系，找到信号

import pandas as pd

pd.Series(list(map(lambda a,b : min(a,b), data1H['close'],data1H['open'])),index=data1H.index).tail()
datetime
2018-09-20 08:00:00    6392.00
2018-09-20 16:00:00    6411.00
2018-09-21 00:00:00    6417.77
2018-09-21 08:00:00    6492.00
2018-09-21 16:00:00    6647.91
dtype: float64

lowerShadow = dv1H.add_formula('lowerShadow','If((((Min(close,open)-low)/(high-low))>0.7),100,0)', add_data=True)
datalowerShadow = dv1H.get_ts('lowerShadow', date_type='datetime')
# datalowerShadow
scatterlowerShadowX = datalowerShadow[datalowerShadow['BTCUSDT:binance']==100].index
scatterlowerShadowX
DatetimeIndex(['2018-08-02 00:00:00', '2018-08-06 16:00:00',
               '2018-08-07 00:00:00', '2018-08-12 16:00:00',
               '2018-09-11 00:00:00'],
              dtype='datetime64[ns]', name='trade_date', freq=None)

scatterlowerShadowY = data1H.loc[scatterlowerShadowX].low-100
draw_candle(candle, scatterlowerShadowX, scatterlowerShadowY)

蜡烛图如何用图表显示，并用TA_Lib寻找蜡烛图？

BullCandle

Reversal

  1. Three-line strike, bearish: 84% ta.CDL3LINESTRIKE
  2. Three white soldiers: 82% ta.CDL3WHITESOLDIERS
  3. Engulfing, bearish: 79% ta.CDLENGULFING
  4. Morning star: 78% ta.CDLMORNINGSTAR
  5. Morning doji star: 76% ta.CDLMORNINGDOJISTAR
engulfing = dv1H.add_formula('engulfing', "If((Ta('CDLENGULFING', 0, open, high, low, close, volume)==100),100,0)", add_data=True)
engulfingVolume = dv1H.get_ts('engulfing', date_type='datetime')
engulfingVolume[engulfingVolume['BTCUSDT:binance']==100]
symbol BTCUSDT:binance
trade_date
2018-08-19 16:00:00 100.0
2018-08-31 00:00:00 100.0
2018-09-01 00:00:00 100.0
2018-09-04 08:00:00 100.0 
engulfingVolumeX = engulfingVolume[engulfingVolume['BTCUSDT:binance']==100].index
engulfingVolumeY = data1H.loc[engulfingVolumeX].low-100
draw_candle(candle, engulfingVolumeX, engulfingVolumeY)

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