关于成交量倍数指标的问题，我们总结了以下几点，给你解答：
成交量倍数指标原码
把自用的送你一个,不知满意么.
成交:VOL,POINTDOT;
AA:=VOL/((HIGH-LOW)*2-ABS(CLOSE-OPEN));
买:=IF(CLOSE>OPEN,AA*(HIGH-LOW),IF(CLOSEOPEN,0-AA*((HIGH-CLOSE)+(OPEN-LOW)),IF(CLOSE0,0,VOL,2,0),COLOR00FF55; STICKLINE(买>0,0,买,2,0),COLORRED; 流通【亿】:CAPITAL/1000000,LINETHICK; {A1:=SUMBARS(VOL,CAPITAL); CMA:=IF(CAPITAL>0,SUM(AMOUNT,A1)/SUM(VOL,A1)/100000,EMA(CLOSE,120000)); 每股未分配利润:FINANCE(32); 每股公积金:FINANCE(18); 毛利率:(FINANCE(21)/FINANCE(20))*100 ,LINETHICK0; AK:=HHV(H,400); 涨跌幅:((C-AK)/AK)*100,COLOR00FFFF,LINETHICK0; BK:=LLV(L,300); 涨幅:((C-BK)/BK)*100,COLORFF00FF,LINETHICK0;
在主图下半部分的指标选择VOL就可以。
先设置多窗口限时，如果显示两个窗口，成交量直接就显示出来了
直接打VOL就可以v
在K线界面，选一指标窗口，直接打VOL就可以了。
这个真没有。
成交量倍数指标
# 将每天的成交量与前一天的成交量比较，计算出比值，比值越大，表明当天的成交量越大
# 将比值记录在vol_multiple中
vol_multiple = []
for i in range(1, len(vol)):
vol_multiple.append(vol[i] / vol[i - 1])
vol_multiple.insert(0, 0)
# 将vol_multiple添加到dataframe中
df['vol_multiple'] = vol_multiple
# 计算收盘价与前一天收盘价的比值
close_multiple = []
for i in range(1, len(close)):
close_multiple.append(close[i] / close[i - 1])
close_multiple.insert(0, 0)
# 将close_multiple添加到dataframe中
df['close_multiple'] = close_multiple
# 计算收盘价与开盘价的比值
open_close_multiple = []
for i in range(len(open)):
open_close_multiple.append(close[i] / open[i])
# 将open_close_multiple添加到dataframe中
df['open_close_multiple'] = open_close_multiple
# 计算最高价与最低价的比值
high_low_multiple = []
for i in range(len(high)):
high_low_multiple.append(high[i] / low[i])
# 将high_low_multiple添加到dataframe中
df['high_low_multiple'] = high_low_multiple
# 计算收盘价与最低价的比值
close_low_multiple = []
for i in range(len(close)):
close_low_multiple.append(close[i] / low[i])
# 将close_low_multiple添加到dataframe中
df['close_low_multiple'] = close_low_multiple
# 计算收盘价与最高价的比值
close_high_multiple = []
for i in range(len(close)):
close_high_multiple.append(close[i] / high[i])
# 将close_high_multiple添加到dataframe中
df['close_high_multiple'] = close_high_multiple
# 计算收盘价与前一天最高价的比值
close_pre_high_multiple = []
for i in range(1, len(close)):
close_pre_high_multiple.append(close[i] / high[i - 1])
close_pre_high_multiple.insert(0, 0)
# 将close_pre_high_multiple添加到dataframe中
df['close_pre_high_multiple'] = close_pre_high_multiple
# 计算收盘价与前一天最低价的比值
close_pre_low_multiple = []
for i in range(1, len(close)):
close_pre_low_multiple.append(close[i] / low[i - 1])
close_pre_low_multiple.insert(0, 0)
# 将close_pre_low_multiple添加到dataframe中
df['close_pre_low_multiple'] = close_pre_low_multiple
# 计算收盘价与前一天收盘价的比值
close_pre_close_multiple = []
for i in range(1, len(close)):
close_pre_close_multiple.append(close[i] / close[i - 1])
close_pre_close_multiple.insert(0, 0)
# 将close_pre_close_multiple添加到dataframe中
df['close_pre_close_multiple'] = close_pre_close_multiple
# 计算最高价与前一天最高价的比值
high_pre_high_multiple = []
for i in range(1, len(high)):
high_pre_high_multiple.append(high[i] / high[i - 1])
high_pre_high_multiple.insert(0, 0)
# 将high_pre_high_multiple添加到dataframe中
df['high_pre_high_multiple'] = high_pre_high_multiple
# 计算最低价与前一天最低价的比值
low_pre_low_multiple = []
for i in range(1, len(low)):
low_pre_low_multiple.append(low[i] / low[i - 1])
low_pre_low_multiple.insert(0, 0)
# 将low_pre_low_multiple添加到dataframe中
df['low_pre_low_multiple'] = low_pre_low_multiple
# 计算最高价与前一天最低价的比值
high_pre_low_multiple = []
for i in range(1, len(high)):
high_pre_low_multiple.append(high[i] / low[i - 1])
high_pre_low_multiple.insert(0, 0)
# 将high_pre_low_multiple添加到dataframe中
df['high_pre_low_multiple'] = high_pre_low_multiple
# 计算最低价与前一天最高价的比值
low_pre_high_multiple = []
for i in range(1, len(low)):
low_pre_high_multiple.append(low[i] / high[i - 1])
low_pre_high_multiple.insert(0, 0)
# 将low_pre_high_multiple添加到dataframe中
df['low_pre_high_multiple'] = low_pre_high_multiple
# 计算收盘价与前一天开盘价的比值
close_pre_open_multiple = []
for i in range(1, len(close)):
close_pre_open_multiple.append(close[i] / open[i - 1])
close_pre_open_multiple.insert(0, 0)
# 将close_pre_open_multiple添加到dataframe中
df['close_pre_open_multiple'] = close_pre_open_multiple
# 计算最高价与前一天开盘价的比值
high_pre_open_multiple = []
for i in range(1, len(high)):
high_pre_open_multiple.append(high[i] / open[i - 1])
high_pre_open_multiple.insert(0, 0)
# 将high_pre_open_multiple添加到dataframe中
df['high_pre_open_multiple'] = high_pre_open_multiple
# 计算最低价与前一天开盘价的比
成交量倍数指标副图
朋友，系统本身的指标，你修改时只能是暂时使用，一旦软件关闭就会变回原样的，只有你自己重新新那建一个公式，之后使用这个公式来查看成交量，才不会发生改变的。