Michael Halls-Moore 算法交易后的错误

Question

我正在阅读 Michael Halls-Moore 算法交易书，但遇到了一些代码问题。当我将代码粘贴到 python 时，我遇到了很多错误。

我是不是漏掉了什么，因为它和书上写的一模一样？

from __future__ import print_function

from numpy import cumsum, log, polyfit, sqrt, std, subtract
from numpy.random import randn


def hurst(ts):
    """Returns the Hurst Exponent of the time series vector ts"""
    # Create the range of lag values
    lags = range(2, 100)

    # Calculate the array of the variances of the lagged differences
    tau = [sqrt(std(subtract(ts[lag:], ts[:-lag]))) for lag in lags]

    # Use a linear fit to estimate the Hurst Exponent
    poly = polyfit(log(lags), log(tau), 1)

    # Return the Hurst exponent from the polyfit output
    return poly[0]*2.0

# Create a Geometric Brownian Motion, Mean-Reverting and Trending Series
gbm = log(cumsum(randn(100000))+1000)
mr = log(randn(100000)+1000)
tr = log(cumsum(randn(100000)+1)+1000)

# Output the Hurst Exponent for each of the above series
# and the price of Amazon (the Adjusted Close price) for
# the ADF test given above in the article
print("Hurst(GBM):   %s" % hurst(gbm))
print("Hurst(MR):    %s" % hurst(mr))
print("Hurst(TR):    %s" % hurst(tr))

# Assuming you have run the above code to obtain 'amzn'!
print("Hurst(AMZN): %s" % hurst(amzn['Adj Close']))

以下错误

james@ubuntu:~$ python
Python 2.7.12 (default, Jul  1 2016, 15:12:24) 
[GCC 5.4.0 20160609] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> from __future__ import print_function
>>> 
>>> from numpy import cumsum, log, polyfit, sqrt, std, subtract
>>> from numpy.random import randn
>>> 
>>> 
>>> def hurst(ts):
...     """Returns the Hurst Exponent of the time series vector ts"""
...     # Create the range of lag values
... 
>>>     lags = range(2, 100)
  File "<stdin>", line 1
    lags = range(2, 100)
    ^
IndentationError: unexpected indent
>>> 
>>>     # Calculate the array of the variances of the lagged differences
... 
>>>     tau = [sqrt(std(subtract(ts[lag:], ts[:-lag]))) for lag in lags]
  File "<stdin>", line 1
    tau = [sqrt(std(subtract(ts[lag:], ts[:-lag]))) for lag in lags]
    ^
IndentationError: unexpected indent
>>> 
>>>     # Use a linear fit to estimate the Hurst Exponent
... 
>>>     poly = polyfit(log(lags), log(tau), 1)
  File "<stdin>", line 1
    poly = polyfit(log(lags), log(tau), 1)
    ^
IndentationError: unexpected indent
>>> 
>>>     # Return the Hurst exponent from the polyfit output
... 
>>>     return poly[0]*2.0
  File "<stdin>", line 1
    return poly[0]*2.0
    ^
IndentationError: unexpected indent
>>> 
>>> # Create a Gometric Brownian Motion, Mean-Reverting and Trending Series
... gbm = log(cumsum(randn(100000))+1000)
>>> mr = log(randn(100000)+1000)
>>> tr = log(cumsum(randn(100000)+1)+1000)
>>> 
>>> # Output the Hurst Exponent for each of the above series
... # and the price of Amazon (the Adjusted Close price) for
... # the ADF test given above in the article
... print("Hurst(GBM):   %s" % hurst(gbm))
Hurst(GBM):   None
>>> print("Hurst(MR):    %s" % hurst(mr))
Hurst(MR):    None
>>> print("Hurst(TR):    %s" % hurst(tr))
Hurst(TR):    None
>>> 
>>> # Assuming you have run the above code to obtain 'amzn'!
... print("Hurst(AMZN): %s" % hurst(amzn['Adj Close']))
Hurst(AMZN): None

Answer 1

看起来您正在将代码粘贴到 python 交互式 window 中。当您使用交互式 window 编写一段缩进代码时（例如定义一个函数或开始一个 for 循环时），按两次 Enter 结束代码块部分（这就是为什么您在空行后得到错误当代码应该位于缩进代码块中时）。在您的代码中，您可以删除所有空行（代码块末尾的空行除外；这些是结束代码块所必需的）并将其粘贴到交互式 window 中，或者您可以将代码复制到文本文件中，使用 .py 文件扩展名保存文件，并使用命令 python your_script.py 从命令 prompt/powershell/terminal 中运行脚本。

或者，使用 python IDE（而不是交互式 window 或从命令行），如 pycharm (https://www.jetbrains.com/pycharm/)。

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quantitative-finance