最近在学习量化交易，需要自己实现RSI指标，参考了TA-LIB的实现方式。
RSI英文全称：Relative Strength Index
RSI中文名称：相对强弱指数
是衡量价格波动的一个重要指标。
计算公式
UP_AVG = UP_AMOUNT/PERIODS (周期内上涨数量平均)
DOWN_AVG = DOWN_AMOUNT/PERIODS（周期内下跌数量平均）
RS = UP_AVG/DOWN_AVG（相对平均）
RSI = 100 - 100 / (1 + RS) （相对强弱指数）
快速计算公式
利用前一个UP_AVG, DOWN_AVG快速计算当前UP_AVG, DOWN_AVG
UP_AVG = (UP_AVG_PREV * (PERIODS - 1) + UP) / PERIODS
DOWN_AVG = (UP_AVG_PREV * (PERIODS - 1) + DOWN) / PERIODS
RS = UP_AVG/DOWN_AVG
RSI = 100 - 100 / (1 + RS)
Python代码实现
def RSI(t, periods=10):
length = len(t)
rsies = [np.nan]*length
#数据长度不超过周期，无法计算；
if length <= 10:
return rsies
#用于快速计算；
up_avg = 0
down_avg = 0
#首先计算第一个RSI，用前periods+1个数据，构成periods个价差序列;
first_t = t[:periods+1]
for i in range(1, len(first_t)):
#价格上涨;
if first_t[i] >= first_t[i-1]:
up_avg += first_t[i] - first_t[i-1]
#价格下跌;
else:
down_avg += first_t[i-1] - first_t[i]
up_avg = up_avg / periods
down_avg = down_avg / periods
rs = up_avg / down_avg
rsies[periods] = 100 - 100/(1+rs)
#后面的将使用快速计算；
for j in range(periods+1, length):
up = 0
down = 0
if t[j] >= t[j-1]:
up = t[j] - t[j-1]
down = 0
else:
up = 0
down = t[j-1] - t[j]
#类似移动平均的计算公式;
up_avg = (up_avg*(periods - 1) + up)/periods
down_avg = (down_avg*(periods - 1) + down)/periods
rs = up_avg/down_avg
rsies[j] = 100 - 100/(1+rs)
return rsies
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def RSI(df, period=14):
"""
Relative Strength Index
"""
series = df['close']
delta = series.diff().dropna()
u = delta * 0
d = u.copy()
u[delta > 0] = delta[delta > 0]
d[delta < 0] = -delta[delta < 0]
u[u.index[period - 1]] = np.mean(u[:period]) # first value is sum of avg gains
u = u.drop(u.index[:(period - 1)])
d[d.index[period - 1]] = np.mean(d[:period]) # first value is sum of avg losses
d = d.drop(d.index[:(period - 1)])
avgGain = u.ewm(com=period - 1, adjust=False).mean()
avgLoss = d.ewm(com=period - 1, adjust=False).mean()
rs = avgGain / avgLoss
result = 100 - 100 / (1 + rs)
return result