股票技术分析技能。用于分析股票的技术指标、形态、K线组合等。主要功能包括：(1) 常用技术指标计算（MA、MACD、KDJ、RSI、BOLL等）(2) K线形态识别（锤子线、吞没、十字星等）(3) 趋势分析 (4) 支撑位阻力位计算 (5) 量价关系分析。当用户需要技术分析时使用此技能。
import pandas as pd
def calc_ma(df, period):
return df['close'].rolling(window=period).mean()
# 常用周期
MA5 = calc_ma(df, 5) # 短期均线
MA10 = calc_ma(df, 10) # 中期均线
MA20 = calc_ma(df, 20) # 长期均线
MA60 = calc_ma(df, 60) # 半年线
def calc_macd(df, fast=12, slow=26, signal=9):
ema12 = df['close'].ewm(span=fast).mean()
ema26 = df['close'].ewm(span=slow).mean()
diff = ema12 - ema26
dea = diff.ewm(span=signal).mean()
macd = (diff - dea) * 2
return diff, dea, macd
def calc_kdj(df, n=9, m1=3, m2=3):
low_n = df['low'].rolling(window=n).min()
high_n = df['high'].rolling(window=n).max()
rsv = (df['close'] - low_n) / (high_n - low_n) * 100
k = rsv.ewm(com=m1-1).mean()
d = k.ewm(com=m2-1).mean()
j = 3 * k - 2 * d
return k, d, j
def calc_rsi(df, period=14):
delta = df['close'].diff()
gain = (delta.where(delta > 0, 0)).rolling(window=period).mean()
loss = (-delta.where(delta < 0, 0)).rolling(window=period).mean()
rs = gain / loss
rsi = 100 - (100 / (1 + rs))
return rsi
def calc_boll(df, period=20, std_dev=2):
middle = df['close'].rolling(window=period).mean()
std = df['close'].rolling(window=period).std()
upper = middle + (std * std_dev)
lower = middle - (std * std_dev)
return upper, middle, lower
| 形态 | 信号 | 说明 |
|---|---|---|
| 锤子线 | 买入 | 下影线长，实体小 |
| 上吊线 | 卖出 | 上影线长，实体小 |
| 吞没 | 买入/卖出 | 阴阳包线 |
| 十字星 | 谨慎 | 多空平衡 |
| 早晨之星 | 买入 | 底部三连阳 |
| 黄昏之星 | 卖出 | 顶部三连阴 |
def is_hammer(candle):
"""锤子线"""
body = abs(candle['close'] - candle['open'])
lower_shadow = min(candle['open'], candle['close']) - candle['low']
upper_shadow = candle['high'] - max(candle['open'], candle['close'])
return (lower_shadow > body * 2 and
upper_shadow < body * 0.5)
def is_doji(candle):
"""十字星"""
body = abs(candle['close'] - candle['open'])
total_range = candle['high'] - candle['low']
return body < total_range * 0.1
def find_support_resistance(prices, window=20):
"""寻找支撑位和阻力位"""
highs = prices['high'].rolling(window).max()
lows = prices['low'].rolling(window).min()
return highs, lows
| 现象 | 信号 |
|---|---|
| 价涨量增 | 强势上涨 |
| 价涨量缩 | 上涨乏力 |
| 价跌量增 | 恐慌抛售 |
| 价跌量缩 | 底部信号 |