计算最近几天的RSI

Question

我正在努力改进我的算法机器人，有一件事我已经实现了绝对糟糕的是RSI。由于RSI是一个滞后指标，我无法获得最近的数据，我得到的最后一个值是8天前。因此，我希望通过使用以前的值来计算它，并寻找如何这样做的想法。

My data points:

[222.19000244140625, nan]
[222.19000244140625, nan]
[215.47000122070312, nan]
[212.25, nan]
[207.97000122070312, nan]
[206.3300018310547, nan]
[205.88999938964844, nan]
[208.36000061035156, nan]
[204.08999633789062, 10.720487433358727]
[197.00999450683594, 7.934105468501102]
[194.6699981689453, 7.224811311424375]
[190.66000366210938, 6.148330770309926]
[191.6300048828125, 9.861218420857213]
[189.13999938964844, 8.835726925023536]
[189.02000427246094, 8.785409465194874]
[187.02000427246094, 7.925663008903896]
[195.69000244140625, 37.989974096922204]
[196.9199981689453, 41.10776671337689]
[194.11000061035156, 36.33757785797855]

正如你所看到的，10.720487433358727是我最近的值，但我相信比我更聪明的人可以找到计算它的方法，直到今天。

谢谢你的帮助!

Answer 1

重要的是要注意定义RSI的方法有很多种。它通常至少以两种方式定义:如上所述使用简单移动平均线(SMA)或使用指数移动平均线(EMA)。下面的代码片段计算了RSI的两种定义，并绘制了它们以供比较。在取差值后，我将丢弃第一行，因为根据定义，它始终是NaN。

import pandas
import pandas_datareader.data as web
import datetime
import matplotlib.pyplot as plt
# Window length for moving average
window_length = 14
# Dates
start = '2020-12-01'
end = '2021-01-27'
# Get data
data = web.DataReader('AAPL', 'yahoo', start, end)
# Get just the adjusted close
close = data['Adj Close']
# Get the difference in price from previous step
delta = close.diff()
# Get rid of the first row, which is NaN since it did not have a previous 
# row to calculate the differences
delta = delta[1:] 
# Make the positive gains (up) and negative gains (down) Series
up, down = delta.copy(), delta.copy()
up[up < 0] = 0
down[down > 0] = 0
# Calculate the EWMA
roll_up1 = up.ewm(span=window_length).mean()
roll_down1 = down.abs().ewm(span=window_length).mean()
# Calculate the RSI based on EWMA
RS1 = roll_up1 / roll_down1
RSI1 = 100.0 - (100.0 / (1.0 + RS1))
# Calculate the SMA
roll_up2 = up.rolling(window_length).mean()
roll_down2 = down.abs().rolling(window_length).mean()
# Calculate the RSI based on SMA
RS2 = roll_up2 / roll_down2
RSI2 = 100.0 - (100.0 / (1.0 + RS2))
# Compare graphically
plt.figure(figsize=(8, 6))
RSI1.plot()
RSI2.plot()
plt.legend(['RSI via EWMA', 'RSI via SMA'])
plt.show()