三大指标共振选股(股市甩锅共振三浪公式?)
1. 股市甩锅共振三浪公式?
三浪公式为
{1.红时,视为多头市场;绿时,视为空头市场;(趋势判断)2.洋红时,买进,蓝时,卖出;(超短线)3.出钱袋回补。}
M1:=(HIGH+LOW+CLOSE)/3;
M2:=(M1-MA(M1,84))/(0.015*AVEDEV(M1,84));
M3:=(M1-MA(M1,14))/(0.015*AVEDEV(M1,14));
DIF:EMA(M2,5)-EMA(M2,35);
DEA:EMA(DIF,5),COLOR888888;
VAR1:DIF,COLORRED;
上升:IF(VAR1>REF(VAR1,1),VAR1,DRAWNULL),COLORRED;
下降:IF(VAR1<REF(VAR1,1),VAR1,DRAWNULL),COLORGREEN;
VAR2:DEA,COLORRED,LINETHICK3;
上翘:IF(VAR2>REF(VAR2,1),VAR2,DRAWNULL),COLORRED,LINETHICK3;
下拐:IF(VAR2<REF(VAR2,1),VAR2,DRAWNULL),COLORGREEN,LINETHICK3;
DIF1:=EMA(M2,5)-EMA(M2,35);
DEA1:=EMA(DIF1,5),COLOR888888;
MACD:(DIF1-DEA1)*2,COLORSTICK;
VA3:=HHVBARS(MACD,BARSLAST(MACD<0)+1);
VA4:=CROSS(BACKSET(CROSS(0,MACD),REF(VA3,1)+2),0.5);
前高:=DRAWLINE(VA4,MACD,REF(VA4,1),REF(MACD,1),1);
STICKLINE(MACD>前高,MACD,前高,0.0001,0),COLORWHITE;
STICKLINE(M2>100,0,MACD,0.0001,0),COLORMAGENTA;
STICKLINE(M3<100,0,MACD,0.0001,0),COLORBLUE;
DRAWICON(CROSS(M2,-100),0*0.97,9);
2. 股市甩锅共振三浪公式?
三浪公式为
{1.红时,视为多头市场;绿时,视为空头市场;(趋势判断)2.洋红时,买进,蓝时,卖出;(超短线)3.出钱袋回补。}
M1:=(HIGH+LOW+CLOSE)/3;
M2:=(M1-MA(M1,84))/(0.015*AVEDEV(M1,84));
M3:=(M1-MA(M1,14))/(0.015*AVEDEV(M1,14));
DIF:EMA(M2,5)-EMA(M2,35);
DEA:EMA(DIF,5),COLOR888888;
VAR1:DIF,COLORRED;
上升:IF(VAR1>REF(VAR1,1),VAR1,DRAWNULL),COLORRED;
下降:IF(VAR1<REF(VAR1,1),VAR1,DRAWNULL),COLORGREEN;
VAR2:DEA,COLORRED,LINETHICK3;
上翘:IF(VAR2>REF(VAR2,1),VAR2,DRAWNULL),COLORRED,LINETHICK3;
下拐:IF(VAR2<REF(VAR2,1),VAR2,DRAWNULL),COLORGREEN,LINETHICK3;
DIF1:=EMA(M2,5)-EMA(M2,35);
DEA1:=EMA(DIF1,5),COLOR888888;
MACD:(DIF1-DEA1)*2,COLORSTICK;
VA3:=HHVBARS(MACD,BARSLAST(MACD<0)+1);
VA4:=CROSS(BACKSET(CROSS(0,MACD),REF(VA3,1)+2),0.5);
前高:=DRAWLINE(VA4,MACD,REF(VA4,1),REF(MACD,1),1);
STICKLINE(MACD>前高,MACD,前高,0.0001,0),COLORWHITE;
STICKLINE(M2>100,0,MACD,0.0001,0),COLORMAGENTA;
STICKLINE(M3<100,0,MACD,0.0001,0),COLORBLUE;
DRAWICON(CROSS(M2,-100),0*0.97,9);
3. macd多周期共振选股指标源码?
以下是一个示例的MACD多周期共振选股指标的Python源码:
```python
import pandas as pd
import numpy as np
import talib
def calculate_macd(data, short_period, long_period, signal_period):
close_prices = data['close'].values
macd, signal, _ = talib.MACD(close_prices, fastperiod=short_period, slowperiod=long_period, signalperiod=signal_period)
return macd, signal
def find_resonance_stocks(data, short_periods, long_periods, signal_periods):
resonance_stocks = []
for short_period in short_periods:
for long_period in long_periods:
for signal_period in signal_periods:
macd, signal = calculate_macd(data, short_period, long_period, signal_period)
if macd[-1] > signal[-1] and macd[-2] < signal[-2] and macd[-3] > signal[-3]:
resonance_stocks.append((short_period, long_period, signal_period))
return resonance_stocks
# 示例使用
data = pd.read_csv('stock_data.csv') # 读取股票数据,假设包含日期和收盘价等字段
short_periods = [12, 26, 9] # 短周期参数列表
long_periods = [50, 100] # 长周期参数列表
signal_periods = [9, 12, 26] # 信号周期参数列表
resonance_stocks = find_resonance_stocks(data, short_periods, long_periods, signal_periods)
print("Resonance stocks:")
for stock in resonance_stocks:
print("Short Period: {}, Long Period: {}, Signal Period: {}".format(stock[0], stock[1], stock[2]))
```
请注意,这只是一个示例代码框架,您可能需要根据实际需求进行修改和优化。此外,您还需要安装相应的Python库(如pandas、numpy和talib)才能运行这段代码。
4. macd和sar指标共振的用法?
指标组合:SAR指标组合MACD指标
1.当SAR指标在上涨中,价格突破SAR曲线,下方MACD形成市场,卖出。
2.当SAR指标在下跌趋势中,价格突破SAR曲线,下方MACD指标形成金叉,买入,根据MACD指标运行持有。
采用两种指标组合的方式,就是当一个指标产生不明确的信号的时候,去参考另一个指标,从而达到两种指标共振的判断方法,增加市场买入卖出准确性,任何指标都不是万能的,有缺点,有优点,不能机械的按照指标进行操作,还需要考虑市场的一些其他因素。
5. macd和sar指标共振的用法?
指标组合:SAR指标组合MACD指标
1.当SAR指标在上涨中,价格突破SAR曲线,下方MACD形成市场,卖出。
2.当SAR指标在下跌趋势中,价格突破SAR曲线,下方MACD指标形成金叉,买入,根据MACD指标运行持有。
采用两种指标组合的方式,就是当一个指标产生不明确的信号的时候,去参考另一个指标,从而达到两种指标共振的判断方法,增加市场买入卖出准确性,任何指标都不是万能的,有缺点,有优点,不能机械的按照指标进行操作,还需要考虑市场的一些其他因素。
6. macd和sar指标共振的用法?
指标组合:SAR指标组合MACD指标
1.当SAR指标在上涨中,价格突破SAR曲线,下方MACD形成市场,卖出。
2.当SAR指标在下跌趋势中,价格突破SAR曲线,下方MACD指标形成金叉,买入,根据MACD指标运行持有。
采用两种指标组合的方式,就是当一个指标产生不明确的信号的时候,去参考另一个指标,从而达到两种指标共振的判断方法,增加市场买入卖出准确性,任何指标都不是万能的,有缺点,有优点,不能机械的按照指标进行操作,还需要考虑市场的一些其他因素。
7. macd多周期共振选股指标源码?
以下是一个示例的MACD多周期共振选股指标的Python源码:
```python
import pandas as pd
import numpy as np
import talib
def calculate_macd(data, short_period, long_period, signal_period):
close_prices = data['close'].values
macd, signal, _ = talib.MACD(close_prices, fastperiod=short_period, slowperiod=long_period, signalperiod=signal_period)
return macd, signal
def find_resonance_stocks(data, short_periods, long_periods, signal_periods):
resonance_stocks = []
for short_period in short_periods:
for long_period in long_periods:
for signal_period in signal_periods:
macd, signal = calculate_macd(data, short_period, long_period, signal_period)
if macd[-1] > signal[-1] and macd[-2] < signal[-2] and macd[-3] > signal[-3]:
resonance_stocks.append((short_period, long_period, signal_period))
return resonance_stocks
# 示例使用
data = pd.read_csv('stock_data.csv') # 读取股票数据,假设包含日期和收盘价等字段
short_periods = [12, 26, 9] # 短周期参数列表
long_periods = [50, 100] # 长周期参数列表
signal_periods = [9, 12, 26] # 信号周期参数列表
resonance_stocks = find_resonance_stocks(data, short_periods, long_periods, signal_periods)
print("Resonance stocks:")
for stock in resonance_stocks:
print("Short Period: {}, Long Period: {}, Signal Period: {}".format(stock[0], stock[1], stock[2]))
```
请注意,这只是一个示例代码框架,您可能需要根据实际需求进行修改和优化。此外,您还需要安装相应的Python库(如pandas、numpy和talib)才能运行这段代码。
8. 股市甩锅共振三浪公式?
三浪公式为
{1.红时,视为多头市场;绿时,视为空头市场;(趋势判断)2.洋红时,买进,蓝时,卖出;(超短线)3.出钱袋回补。}
M1:=(HIGH+LOW+CLOSE)/3;
M2:=(M1-MA(M1,84))/(0.015*AVEDEV(M1,84));
M3:=(M1-MA(M1,14))/(0.015*AVEDEV(M1,14));
DIF:EMA(M2,5)-EMA(M2,35);
DEA:EMA(DIF,5),COLOR888888;
VAR1:DIF,COLORRED;
上升:IF(VAR1>REF(VAR1,1),VAR1,DRAWNULL),COLORRED;
下降:IF(VAR1<REF(VAR1,1),VAR1,DRAWNULL),COLORGREEN;
VAR2:DEA,COLORRED,LINETHICK3;
上翘:IF(VAR2>REF(VAR2,1),VAR2,DRAWNULL),COLORRED,LINETHICK3;
下拐:IF(VAR2<REF(VAR2,1),VAR2,DRAWNULL),COLORGREEN,LINETHICK3;
DIF1:=EMA(M2,5)-EMA(M2,35);
DEA1:=EMA(DIF1,5),COLOR888888;
MACD:(DIF1-DEA1)*2,COLORSTICK;
VA3:=HHVBARS(MACD,BARSLAST(MACD<0)+1);
VA4:=CROSS(BACKSET(CROSS(0,MACD),REF(VA3,1)+2),0.5);
前高:=DRAWLINE(VA4,MACD,REF(VA4,1),REF(MACD,1),1);
STICKLINE(MACD>前高,MACD,前高,0.0001,0),COLORWHITE;
STICKLINE(M2>100,0,MACD,0.0001,0),COLORMAGENTA;
STICKLINE(M3<100,0,MACD,0.0001,0),COLORBLUE;
DRAWICON(CROSS(M2,-100),0*0.97,9);
9. macd多周期共振选股指标源码?
以下是一个示例的MACD多周期共振选股指标的Python源码:
```python
import pandas as pd
import numpy as np
import talib
def calculate_macd(data, short_period, long_period, signal_period):
close_prices = data['close'].values
macd, signal, _ = talib.MACD(close_prices, fastperiod=short_period, slowperiod=long_period, signalperiod=signal_period)
return macd, signal
def find_resonance_stocks(data, short_periods, long_periods, signal_periods):
resonance_stocks = []
for short_period in short_periods:
for long_period in long_periods:
for signal_period in signal_periods:
macd, signal = calculate_macd(data, short_period, long_period, signal_period)
if macd[-1] > signal[-1] and macd[-2] < signal[-2] and macd[-3] > signal[-3]:
resonance_stocks.append((short_period, long_period, signal_period))
return resonance_stocks
# 示例使用
data = pd.read_csv('stock_data.csv') # 读取股票数据,假设包含日期和收盘价等字段
short_periods = [12, 26, 9] # 短周期参数列表
long_periods = [50, 100] # 长周期参数列表
signal_periods = [9, 12, 26] # 信号周期参数列表
resonance_stocks = find_resonance_stocks(data, short_periods, long_periods, signal_periods)
print("Resonance stocks:")
for stock in resonance_stocks:
print("Short Period: {}, Long Period: {}, Signal Period: {}".format(stock[0], stock[1], stock[2]))
```
请注意,这只是一个示例代码框架,您可能需要根据实际需求进行修改和优化。此外,您还需要安装相应的Python库(如pandas、numpy和talib)才能运行这段代码。
10. macd和sar指标共振的用法?
指标组合:SAR指标组合MACD指标
1.当SAR指标在上涨中,价格突破SAR曲线,下方MACD形成市场,卖出。
2.当SAR指标在下跌趋势中,价格突破SAR曲线,下方MACD指标形成金叉,买入,根据MACD指标运行持有。
采用两种指标组合的方式,就是当一个指标产生不明确的信号的时候,去参考另一个指标,从而达到两种指标共振的判断方法,增加市场买入卖出准确性,任何指标都不是万能的,有缺点,有优点,不能机械的按照指标进行操作,还需要考虑市场的一些其他因素。
11. macd多周期共振选股指标源码?
以下是一个示例的MACD多周期共振选股指标的Python源码:
```python
import pandas as pd
import numpy as np
import talib
def calculate_macd(data, short_period, long_period, signal_period):
close_prices = data['close'].values
macd, signal, _ = talib.MACD(close_prices, fastperiod=short_period, slowperiod=long_period, signalperiod=signal_period)
return macd, signal
def find_resonance_stocks(data, short_periods, long_periods, signal_periods):
resonance_stocks = []
for short_period in short_periods:
for long_period in long_periods:
for signal_period in signal_periods:
macd, signal = calculate_macd(data, short_period, long_period, signal_period)
if macd[-1] > signal[-1] and macd[-2] < signal[-2] and macd[-3] > signal[-3]:
resonance_stocks.append((short_period, long_period, signal_period))
return resonance_stocks
# 示例使用
data = pd.read_csv('stock_data.csv') # 读取股票数据,假设包含日期和收盘价等字段
short_periods = [12, 26, 9] # 短周期参数列表
long_periods = [50, 100] # 长周期参数列表
signal_periods = [9, 12, 26] # 信号周期参数列表
resonance_stocks = find_resonance_stocks(data, short_periods, long_periods, signal_periods)
print("Resonance stocks:")
for stock in resonance_stocks:
print("Short Period: {}, Long Period: {}, Signal Period: {}".format(stock[0], stock[1], stock[2]))
```
请注意,这只是一个示例代码框架,您可能需要根据实际需求进行修改和优化。此外,您还需要安装相应的Python库(如pandas、numpy和talib)才能运行这段代码。
12. 股市甩锅共振三浪公式?
三浪公式为
{1.红时,视为多头市场;绿时,视为空头市场;(趋势判断)2.洋红时,买进,蓝时,卖出;(超短线)3.出钱袋回补。}
M1:=(HIGH+LOW+CLOSE)/3;
M2:=(M1-MA(M1,84))/(0.015*AVEDEV(M1,84));
M3:=(M1-MA(M1,14))/(0.015*AVEDEV(M1,14));
DIF:EMA(M2,5)-EMA(M2,35);
DEA:EMA(DIF,5),COLOR888888;
VAR1:DIF,COLORRED;
上升:IF(VAR1>REF(VAR1,1),VAR1,DRAWNULL),COLORRED;
下降:IF(VAR1<REF(VAR1,1),VAR1,DRAWNULL),COLORGREEN;
VAR2:DEA,COLORRED,LINETHICK3;
上翘:IF(VAR2>REF(VAR2,1),VAR2,DRAWNULL),COLORRED,LINETHICK3;
下拐:IF(VAR2<REF(VAR2,1),VAR2,DRAWNULL),COLORGREEN,LINETHICK3;
DIF1:=EMA(M2,5)-EMA(M2,35);
DEA1:=EMA(DIF1,5),COLOR888888;
MACD:(DIF1-DEA1)*2,COLORSTICK;
VA3:=HHVBARS(MACD,BARSLAST(MACD<0)+1);
VA4:=CROSS(BACKSET(CROSS(0,MACD),REF(VA3,1)+2),0.5);
前高:=DRAWLINE(VA4,MACD,REF(VA4,1),REF(MACD,1),1);
STICKLINE(MACD>前高,MACD,前高,0.0001,0),COLORWHITE;
STICKLINE(M2>100,0,MACD,0.0001,0),COLORMAGENTA;
STICKLINE(M3<100,0,MACD,0.0001,0),COLORBLUE;
DRAWICON(CROSS(M2,-100),0*0.97,9);