omartinsky / quantandfinancial Goto Github PK

Hi, Thanks for the great work!! However, I am getting below error in display_frontier:

ValueError Traceback (most recent call last)
in
2
3 display_assets(names, R, C, color='blue')
----> 4 display_frontier(res1, color='blue')
5 xlabel('variance $\sigma$'), ylabel('mean $\mu$'), show()
6 display(pandas.DataFrame({'Weight': res1.W}, index=names).T)

in display_frontier(result, label, color)
22 text(result.tan_var ** .5, result.tan_mean, 'tangent', verticalalignment='center', color=color)
23 scatter(result.tan_var ** .5, result.tan_mean, marker='o', color=color), grid(True)
---> 24 plot(result.front_var ** .5, result.front_mean, label=label, color=color), grid(True) # draw efficient frontier

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\pyplot.py in plot(scalex, scaley, data, *args, **kwargs)
2787 return gca().plot(
2788 *args, scalex=scalex, scaley=scaley, **({"data": data} if data
-> 2789 is not None else {}), **kwargs)
2790
2791

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axes_axes.py in plot(self, scalex, scaley, data, *args, **kwargs)
1664 """
1665 kwargs = cbook.normalize_kwargs(kwargs, mlines.Line2D._alias_map)
-> 1666 lines = [*self._get_lines(*args, data=data, **kwargs)]
1667 for line in lines:
1668 self.add_line(line)

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axes_base.py in call(self, *args, **kwargs)
223 this += args[0],
224 args = args[1:]
--> 225 yield from self._plot_args(this, kwargs)
226
227 def get_next_color(self):

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axes_base.py in _plot_args(self, tup, kwargs)
384
385 if len(tup) == 2:
--> 386 x = _check_1d(tup[0])
387 y = _check_1d(tup[-1])
388 else:

C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\cbook_init_.py in _check_1d(x)
1400 else:
1401 try:
-> 1402 x[:, None]
1403 return x
1404 except (IndexError, TypeError):

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\arrays\numpy_.py in getitem(self, item)
224 result = self._ndarray[item]
225 if not lib.is_scalar(item):
--> 226 result = type(self)(result)
227 return result
228

C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\arrays\numpy_.py in init(self, values, copy)
132
133 if values.ndim != 1:
--> 134 raise ValueError("PandasArray must be 1-dimensional.")
135
136 if copy:

ValueError: PandasArray must be 1-dimensional.

I was wondering why the weighting’s of the portfolio didn’t change after running optimization with the user views. The output seems to be the same as the BL implied weighting’s.

Thank you.