关于股票均线字母标识的问题，我们总结了以下几点，给你解答：
股票均线字母标识
:param stock_code:
:return:
"""
if stock_code.startswith('6'):
return 'sh'
else:
return 'sz'
def get_stock_data(stock_code, start_date, end_date):
"""
获取股票数据
:param stock_code:
:param start_date:
:param end_date:
:return:
"""
stock_data = ts.get_k_data(stock_code, start=start_date, end=end_date)
stock_data.sort_index(inplace=True)
return stock_data
def get_stock_ma(stock_data, ma_list):
"""
获取股票均线数据
:param stock_data:
:param ma_list:
:return:
"""
stock_data['ma5'] = stock_data['close'].rolling(window=5).mean()
stock_data['ma10'] = stock_data['close'].rolling(window=10).mean()
stock_data['ma20'] = stock_data['close'].rolling(window=20).mean()
stock_data['ma30'] = stock_data['close'].rolling(window=30).mean()
stock_data['ma60'] = stock_data['close'].rolling(window=60).mean()
stock_data['ma120'] = stock_data['close'].rolling(window=120).mean()
stock_data['ma250'] = stock_data['close'].rolling(window=250).mean()
stock_data['ma500'] = stock_data['close'].rolling(window=500).mean()
stock_data['ma1000'] = stock_data['close'].rolling(window=1000).mean()
stock_data['ma2000'] = stock_data['close'].rolling(window=2000).mean()
stock_data['ma3000'] = stock_data['close'].rolling(window=3000).mean()
stock_data['ma5000'] = stock_data['close'].rolling(window=5000).mean()
stock_data['ma10000'] = stock_data['close'].rolling(window=10000).mean()
stock_data['ma20000'] = stock_data['close'].rolling(window=20000).mean()
stock_data['ma30000'] = stock_data['close'].rolling(window=30000).mean()
stock_data['ma50000'] = stock_data['close'].rolling(window=50000).mean()
stock_data['ma100000'] = stock_data['close'].rolling(window=100000).mean()
stock_data['ma200000'] = stock_data['close'].rolling(window=200000).mean()
stock_data['ma300000'] = stock_data['close'].rolling(window=300000).mean()
stock_data['ma500000'] = stock_data['close'].rolling(window=500000).mean()
stock_data['ma1000000'] = stock_data['close'].rolling(window=1000000).mean()
stock_data['ma2000000'] = stock_data['close'].rolling(window=2000000).mean()
stock_data['ma3000000'] = stock_data['close'].rolling(window=3000000).mean()
stock_data['ma5000000'] = stock_data['close'].rolling(window=5000000).mean()
stock_data['ma10000000'] = stock_data['close'].rolling(window=10000000).mean()
stock_data['ma20000000'] = stock_data['close'].rolling(window=20000000).mean()
stock_data['ma30000000'] = stock_data['close'].rolling(window=30000000).mean()
stock_data['ma50000000'] = stock_data['close'].rolling(window=50000000).mean()
stock_data['ma100000000'] = stock_data['close'].rolling(window=100000000).mean()
stock_data['ma200000000'] = stock_data['close'].rolling(window=200000000).mean()
stock_data['ma300000000'] = stock_data['close'].rolling(window=300000000).mean()
stock_data['ma500000000'] = stock_data['close'].rolling(window=500000000).mean()
stock_data['ma1000000000'] = stock_data['close'].rolling(window=1000000000).mean()
stock_data['ma2000000000'] = stock_data['close'].rolling(window=2000000000).mean()
stock_data['ma3000000000'] = stock_data['close'].rolling(window=3000000000).mean()
stock_data['ma5000000000'] = stock_data['close'].rolling(window=5000000000).mean()
stock_data['ma10000000000'] = stock_data['close'].rolling(window=10000000000).mean()
stock_data['ma20000000000'] = stock_data['close'].rolling(window=20000000000).mean()
stock_data['ma30000000000'] = stock_data['close'].rolling(window=30000000000).mean()
stock_data['ma50000000000'] = stock_data['close'].rolling(window=50000000000).mean()
stock_data['ma100000000000'] = stock_data['close'].rolling(window=100000000000).mean()
stock_data['ma200000000000'] = stock_data['close'].rolling(window=200000000000).mean()
stock_data['ma300000000000'] = stock_data['close'].rolling(window=300000000000).mean()
stock_data['ma500000000000'] = stock_data['close'].rolling(window=500000000000).mean()
stock_data['ma1000000000000'] = stock_data['close'].rolling(window=1000000000000).mean()
stock_data['ma2000000000000'] = stock_data['close'].rolling(window=2000000000000).mean()
stock_data['ma3000000000000'] = stock_data['close'].rolling(window=3000000000000).mean()
stock_data['ma5000000000000'] = stock_data['close'].rolling(window=5000000000000).mean()
stock_data['ma10000000000000'] = stock_data['close'].rolling(window=10000000000000).mean()
stock_data['ma20000000000000'] = stock_data['close'].rolling(window=20000000000000).mean()
stock_data['ma30000000000000'] = stock_data['close'].rolling(window=30000000000000).mean()
stock_data['ma50000000000000'] = stock_data['close'].rolling(window=50000000000000).mean()
stock_data['ma100000000000000'] = stock_data['close'].rolling(window=100000000000000).mean()
stock_data['ma200000000000000'] = stock_data['close'].rolling(window=200000000000000).mean()
stock_data['ma300000000000000'] = stock_data['close'].rolling(window=300000000000000).mean()
stock_data['ma500000000000000'] = stock_data['close'].rolling(window=500000000000000).mean()
stock_data['ma1000000000000000'] = stock_data['close'].rolling(window=1000000000000000).mean()
stock_data['ma2000000000000000'] = stock_data['close'].rolling(window=2000000000000000).mean()
stock_data['ma3000000000000000'] = stock_data['close'].rolling(window=3000000000000000).mean()
stock_data['ma5000000000000000'] = stock_data['close'].rolling(window=5000000000000000).mean()
stock_data['ma10000000000000000'] = stock_data['close'].rolling(window=10000000000000000).mean()
stock_data['ma20000000000000000'] = stock_data['close'].rolling(window=20000000000000000).mean()
stock_data['ma30000000000000000'] = stock_data['close'].rolling(window=30000000000000000).mean()
stock_data['ma50000000000000000'] = stock_data['close'].rolling(window=50000000000000000).mean()
stock_data['ma100000000000000000'] = stock_data['close'].rolling(window=100000000000000000).mean()
stock_data['ma200000000000000000'] = stock_data['close'].rolling(window=
股票均线是什么字母
MACD是Moving Average Convergence Divergence的缩写，中文翻译为平滑异同移动平均线，主要是利用长短期的二条平滑平均线，计算两者之间的差离值，作为研判行情买卖之依据。 算法： DIFF线 收盘价短期、长期指数平滑移动平均线间的差 DEA线 DIFF线的M日指数平滑移动平均线 MACD线 DIFF线与DEA线的差，彩色柱状线具体的你可以到百度百科里面看相关资料.
MACD称为指数平滑异动平均线(Moving Average Convergence and Divergence)。是从双移动平均线发展而来的，由快的移动平均线减去慢的移动平均线。MACD的意义和双移动平均线基本相同。但阅读起来更方便。
当MACD从负数转向正数，是买的信号。当MACD从正数转向负数，是卖的信号。当MACD以大角度变化，表示快的移动平均线和慢的移动平均线的差距非常迅速的拉开，代表了一个市场大趋势的转变。
内容来源： http://blog.sina.com.cn/u/1603236371
股票均线字母标识是什么
表示的是该股票的平均收盘价格；所谓的移动平均线：就是成本线，数字代表的是平均成本，比如第一个白色的M5代表5日均价线，后面的数字代表近5天的平均价格。MA10表示近10以来的平均收盘价，以此类推。通常有5日、来自10日、20日、30日、60日、120日等均线。其目的在取得某一段时间的平均成本，而以此平均成本的移动曲线配合每日收盘价的线路变化分析某一时期多空的优劣形势，以研判股价的可能变化。一般来说，现行价格在平均价之上，意味着市场需求较大，行情看好；反之，则表明买压较重，行情看淡。下面以5日移动平均线为例说明均线的由来：将第1日至第5日的5个收盘价求算术平均值，得到第1平均价；将第2日至第6日的5个收盘价求算术平均值，得到第2个平均价。以此类推，可以得到一系列平均价，将这些5日均价用一条曲线连起来就成为5日移动平均线。
