成交量均线指标代码-成交量均线指标代码是什么

2023-04-15 技术指标 0次阅读 admin
成交量均线指标代码.jpg

关于成交量均线指标代码的问题,我们总结了以下几点,给你解答:

成交量均线指标公式


成交量均线指标公式

XG:V>=REF(V,1)*2;
成交量指标公式

核心提示:什么是成交量均线公式?下面是我搜集的资料为您总结的。

n:=27;n2:=9;n3:=3;n4:=16;
var1:=if(date>=1030131,1,1);
var2:=(close-llv(low,n))/(hhv(high,n)-llv(low,n))*100;
获利盘:winner(close)*100*var1;
var3:=sma(var2,3,1)*var1;
var4:=sma(var3,n2,1)*var1;
var5:=3*var3-2*var4*var1;
var6:=vol*var1;
角度:=(close-ref(open,29))/ref(open,29)*100*var1;
换手: vol/capital*100*var1;
var7:=sum(换手,30)*var1;
var8:=llv(indexl,5)*var1;
var9:=hhv(indexh,5)*var1;
vara:=ema((indexc-var8)/(var9-var8)*100,4);
varb:=ma(ema(0.667*ref(vara,1)+0.333*vara,2),9);
varc:=ma(varb,30);
vard:=ema(获利盘,4)*var1;
本盘亿股: capital/1000000;
v5: ma(vol,5)*2*var1;
v13: ma(vol,13)*2*var1;
cross(varb,varc) and varc<29*var1;
stickline(vol and var5>var4,0,vol,9,0),color000055;
stickline(vol and var5>var4,0,vol,8,0),color000066;
stickline(vol and var5>var4,0,vol,7,0),color000077;
stickline(vol and var5>var4,0,vol,6,0),color000088;
stickline(vol and var5>var4,0,vol,5,0),color000099;
stickline(vol and var5>var4,0,vol,4,0),color0000aa;
stickline(vol and var5>var4,0,vol,3,0),color0000bb;
stickline(vol and var5>var4,0,vol,2,0),color0000cc;
stickline(vol and var5>var4,0,vol,1,0),color0000dd;
stickline(vol and var5stickline(vol and var5 stickline(vol and var5 stickline(vol and var5 stickline(vol and var5 stickline(vol and var5 stickline(vol and var5 stickline(vol and var5 stickline(vol and var5 stickline(vol and var4 stickline(vol and var4 stickline(vol and var4 stickline(vol and var4 stickline(vol and var4 stickline(vol and var4 stickline(vol and var4 stickline(vol and var4 stickline(vol and var4 stickline(vol and var4 stickline(vol and var4 rsi:=sma(max(close-ref(close,1),0),5,1)/sma(abs(close-ref(close,1)),6,1)*100; 抛压:stickline(cross(84,rsi),0 ,vol,9,0),colorff0033; stickline(cross(84,rsi),0 ,vol,8,0),colorff0044; stickline(cross(84,rsi),0 ,vol,7,0),colorff0055; stickline(cross(84,rsi),0 ,vol,6,0),colorff0066; stickline(cross(84,rsi),0 ,vol,5,0),colorff0077; stickline(cross(84,rsi),0 ,vol,4,0),colorff0088; stickline(cross(84,rsi),0 ,vol,3,0),colorff0099; stickline(cross(84,rsi),0 ,vol,2,0),colorff00aa; stickline(cross(84,rsi),0 ,vol,1,0),colorff00bb; var13:=(close-ma(close,6))/ma(close,6)*100; var14:=(close-ma(close,24))/ma(close,24)*100; var15:=(close-ma(close,32))/ma(close,32)*100; var16:=(var13+var14+var15)/3; var18:=if(var16<=-20,10,0); var19:=hhv(var18,10); var20:=if(var19 and cross(ma(close,3),ma(close,5)),20,0); 底部:stickline(var20=20,0 ,vol,9,0),color005555; stickline(var20=20,0 ,vol,8,0),color006666; stickline(var20=20,0 ,vol,7,0),color007777; stickline(var20=20,0 ,vol,6,0),color008888; stickline(var20=20,0 ,vol,5,0),color009999; stickline(var20=20,0 ,vol,4,0),color00aaaa; stickline(var20=20,0 ,vol,3,0),color00bbbb; stickline(var20=20,0 ,vol,2,0),color00cccc; stickline(var20=20,0 ,vol,2,0),color00dddd; vare:=ma(100*(close-llv(close,34))/(hhv(high,34)-llv(low,34)),5)-20; varf:=100-3*sma((close-llv(low,66))/(hhv(high,66)-llv(low,66))*100,20,1)+2*sma(sma((close-llv(low,66))/(hhv(high,66)-llv(low,66))*100,20,1),15,1); var100:=100-3*sma((open-llv(low,66))/(hhv(high,66)-llv(low,66))*100,20,1)+2*sma(sma((open-llv(low,66))/(hhv(high,66)-llv(low,66))*100,20,1),15,1); var111:=varfref(vol,1) and close>ref(close,1); 大资金活动:stickline(var111 and count(var111,30)=1,0 ,vol,9,0),color006600; stickline(var111 and count(var111,30)=1,0 ,vol,8,0),color007700; stickline(var111 and count(var111,30)=1,0 ,vol,7,0),color008800; stickline(var111 and count(var111,30)=1,0 ,vol,6,0),color009900; stickline(var111 and count(var111,30)=1,0 ,vol,5,0),color00aa00; stickline(var111 and count(var111,30)=1,0 ,vol,4,0),color00bb00; stickline(var111 and count(var111,30)=1,0 ,vol,3,0),color00cc00; stickline(var111 and count(var111,30)=1,0 ,vol,2,0),color00dd00; stickline(var111 and count(var111,30)=1,0 ,vol,1,0),color00ee00;

成交量均线指标代码


成交量均线指标代码


def MA(self, df, n):
MA = pd.Series(pd.rolling_mean(df['volume'], n), name='MA_' + str(n))
df = df.join(MA)
return df

# 计算MACD指标
def MACD(self, df, n_fast, n_slow):
EMAfast = pd.Series(pd.ewma(df['close'], span=n_fast, min_periods=n_slow - 1))
EMAslow = pd.Series(pd.ewma(df['close'], span=n_slow, min_periods=n_slow - 1))
MACD = pd.Series(EMAfast - EMAslow, name='MACD_' + str(n_fast) + '_' + str(n_slow))
MACDsign = pd.Series(pd.ewma(MACD, span=9, min_periods=8), name='MACDsign_' + str(n_fast) + '_' + str(n_slow))
MACDdiff = pd.Series(MACD - MACDsign, name='MACDdiff_' + str(n_fast) + '_' + str(n_slow))
df = df.join(MACD)
df = df.join(MACDsign)
df = df.join(MACDdiff)
return df

# 计算KDJ指标
def KDJ(self, df, n):
# 计算K值
low_list = pd.rolling_min(df['low'], n)
low_list.fillna(value=pd.expanding_min(df['low']), inplace=True)
high_list = pd.rolling_max(df['high'], n)
high_list.fillna(value=pd.expanding_max(df['high']), inplace=True)
rsv = (df['close'] - low_list) / (high_list - low_list) * 100
K = pd.Series(pd.ewma(rsv, span=9, min_periods=8), name='K')
# 计算D值
D = pd.Series(pd.ewma(K, span=9, min_periods=8), name='D')
# 计算J值
J = pd.Series(3 * K - 2 * D, name='J')
df = df.join(K)
df = df.join(D)
df = df.join(J)
return df

# 计算RSI指标
def RSI(self, df, n):
# 计算RSI
diff = df['close'].diff()
diff = diff.fillna(0)
up = diff.copy()
up[up < 0] = 0
down = diff.copy()
down[down > 0] = 0
down = down.abs()
RS_up = pd.Series(pd.ewma(up, span=n, min_periods=n - 1), name='RS_up')
RS_down = pd.Series(pd.ewma(down, span=n, min_periods=n - 1), name='RS_down')
RSI = pd.Series(RS_up / RS_down, name='RSI_' + str(n))
df = df.join(RSI)
return df

# 计算WR指标
def WR(self, df, n):
# 计算WR
low_list = pd.rolling_min(df['low'], n)
low_list.fillna(value=pd.expanding_min(df['low']), inplace=True)
high_list = pd.rolling_max(df['high'], n)
high_list.fillna(value=pd.expanding_max(df['high']), inplace=True)
WR = pd.Series((high_list - df['close']) / (high_list - low_list) * 100, name='WR_' + str(n))
df = df.join(WR)
return df

# 计算SAR指标
def SAR(self, df):
# 计算SAR
high = df['high']
low = df['low']
close = df['close']
# 初始化参数
af = 0.02
ep = 0
sar = 0
# 计算SAR
if len(df) > 0:
sar = close[0]
ep = high[0]
for i in range(2, len(df) + 1):
if i == 2:
if close[i - 2] > close[i - 1]:
af = 0.02
ep = high[i - 1]
sar = low[i - 2]
elif close[i - 2] < close[i - 1]:
af = 0.02
ep = low[i - 1]
sar = high[i - 2]
elif close[i - 2] > close[i - 1]:
af = min(af + 0.02, 0.2)
ep = max(ep, high[i - 1])
sar = max(sar, low[i - 2])
elif close[i - 2] < close[i - 1]:
af = min(af + 0.02, 0.2)
ep = min(ep, low[i - 1])
sar = min(sar, high[i - 2])
if i == len(df):
SAR = sar
else:
SAR = max(min(sar + af * (ep - sar), high[i - 1]), low[i - 1])
SAR = pd.Series(SAR, name='SAR')
df = df.join(SAR)
return df

# 计算BIAS指标
def BIAS(self, df, n):
# 计算BIAS
MA = pd.Series(pd.rolling_mean(df['close'], n), name='MA_' + str(n))
df = df.join(MA)
BIAS = pd.Series((df['close'] - MA) / MA * 100, name='BIAS_' + str(n))
df = df.join(BIAS)
return df

# 计算CCI指标
def CCI(self, df, n):
# 计算CCI
TP = (df['high'] + df['low'] + df['close']) / 3
MA = pd.Series(pd.rolling_mean(TP, n), name='MA_' + str(n))
df = df.join(MA)
MD = pd.Series(pd.rolling_std(TP, n), name='MD_' + str(n))
df = df.join(MD)
CCI = pd.Series((TP - MA) / (0.015 * MD), name='CCI_' + str(n))
df = df.join(CCI)
return df

# 计算ROC指标
def ROC(self, df, n):
# 计算ROC
M = pd.Series(df['close'].diff(n), name='ROC_' + str(n))
df = df.join(M)
return df

# 计算MTM指标
def MTM(self, df, n):
# 计算MTM
M = pd.Series(df['close'].diff(n), name='MTM_' + str(n))
df = df.join(M)
return df

# 计算VR指标
def VR(self, df, n):
# 计算VR
diff = df['close'].diff()
diff = diff.fillna(0)
up = diff

成交量均线指标代码是什么


成交量均线指标代码是什么

除了这些,还需要学会看公司研报及其他影响股价的因素。炒股有一个常用的方法:看股票K线。想投资股票,可以利用K线找到“规律”这样可以更好的进行投资决策,获领材个对束齐朝草策取收益。
下面就来跟大家详细说明一下K线,从哪几个方面去分析它。
分享之前,先免费送给大家几个炒股神器,能帮你收集分析数据、估值、了解最乐爱稳费城剂旧至响京元新资讯等等,都是我常用的实用工具,建议收藏:炒股的九大神器免费领取(附分享码)
一、 股票K线是什么意思?
K线图也叫蜡烛图、日本线、阴阳线等,我们常将它称呼为K线,它原先的用途是计算米价每天的走向,后来被应用到了股票、期货、期权等证券市场。
由影线和实体组成的柱状线条叫k线。影线在实体上方的部分叫上影线,下方的部分叫下影线,实体分阳线和阴线。
Ps:影线代表的是当天交易的最高和最低价,实体表示的是当天的开盘价和收盘价。
其川要中阳线常常可以被红色、白色柱体或者黑框空心表示红攻支培树景问,而一般是选用绿色、黑色或者蓝色实体住来指代阴线。

除此之外,大家目测到“十字线”的时候,就意味着是实体部分转换成一条线。
其依施四修预京哪议实十字线是很容易理解的,可以通过十字线看出收盘价等于开盘价。
经过对K线的剖析,我们可以出色的找到买卖更线升点(对于股市方面,虽然说是没有办法知道具体的事情,但是K线有一定指导的意义的),对于新手来说是最好操纵的。
这里大家应该值得注意的是,K线看举粒了急号周重交引分析是比较难的,如果你对K线不清楚,建议用一些辅助工具来帮你判断一只股票是否值得买。
比如说下面的诊股链接,输入你中意的股票代码,就能尽用自动帮你估值、分析大盘形势等等,我刚开始炒股的时候就用这种方法来过渡,非物是纸应你免常方便:【免费】测一测你的股票当前估值位置?
下面我来简单讲解几个K线分析的小技巧,帮助你快速入门。
二、怎么用股票K线进行技术分析?
1、实体线为罪落苏朝均影孩管维球电阴线
股票成交量是怎样的,这个时候是我们要重视的,一旦出现成交量不大的情况,说明股价可能会短期下降;有成交量很大的情况,那股价可能要长期下跌了。
2、实体线为阳线
实体线为阳线就说明股价上涨动力更足,但是否是长期上涨,还要结合其他指标稳形进行判断。
比如说大盘形式、行业前景、估值等等因素/季周想犯强言露顾乐地稳指标,但是由于篇幅问题,不能展普设小天出汽拿后两么云开细讲,大家可以点击下方链接了解:新手小白必备的股市基础知识大全

应答时间:2021-09-24,最新业务变化以文中链接内展示的数据为准,请点击查看

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