Hi Dany,

Thank you for providing us such an amazing library, I really appreciate it.

I would be grateful if you could provide support for custom risk measure for HERC method here.

I would like to

Best regards,

Is possible to use a user-specified covariance matrix in the portfolio optimisation, especially with regards to the HRP or HERC?

I don't see that this possible according to the documentation

Hello, I am following your very interesting and useful code. Everything is fine (e.g. I can see all the calculations outputs in the tables from tutorial 1, and 2), but I cannot see any of your plots. I check your Portfolio.py and you use matplotlib. Would you please tell me how to get the plots? I do not use ipynb. Thank you for your time, LM

TL;DR for the current version with a forced matplotlib==3.2.2 patch in Google Colab (see also Here and https://github.com/facebook/prophet/issues/1691 for more info on plotting), and it does work due to matplotlib noting on unnecessary flags.

Error for the Plot

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
[<ipython-input-21-460c462cbd5f>](https://localhost:8080/#) in <module>
     29 
     30 ax = rp.plot_pie(w=w, title='Sharpe Mean Variance', others=0.05, nrow=25, cmap = "tab20",
---> 31                  height=6, width=10, ax=None)

1 frames
[/usr/local/lib/python3.7/dist-packages/riskfolio/PlotFunctions.py](https://localhost:8080/#) in plot_pie(w, title, others, nrow, cmap, height, width, ax)
    601         wedgeprops=dict(width=size, edgecolor="black"),
    602         startangle=-15,
--> 603         normalize=True,
    604     )
    605 

[/usr/local/lib/python3.7/dist-packages/matplotlib/__init__.py](https://localhost:8080/#) in inner(ax, data, *args, **kwargs)
   1563     def inner(ax, *args, data=None, **kwargs):
   1564         if data is None:
-> 1565             return func(ax, *map(sanitize_sequence, args), **kwargs)
   1566 
   1567         bound = new_sig.bind(ax, *args, **kwargs)

TypeError: pie() got an unexpected keyword argument 'normalize'

Code

import riskfolio as rp

# Building the portfolio object
port = rp.Portfolio(returns=Y)

# Calculating optimal portfolio

# Select method and estimate input parameters:

method_mu='hist' # Method to estimate expected returns based on historical data.
method_cov='hist' # Method to estimate covariance matrix based on historical data.

port.assets_stats(method_mu=method_mu, method_cov=method_cov, d=0.94)

# Estimate optimal portfolio:

model='Classic' # Could be Classic (historical), BL (Black Litterman) or FM (Factor Model)
rm = 'MV' # Risk measure used, this time will be variance
obj = 'Sharpe' # Objective function, could be MinRisk, MaxRet, Utility or Sharpe
hist = True # Use historical scenarios for risk measures that depend on scenarios
rf = 0 # Risk free rate
l = 0 # Risk aversion factor, only useful when obj is 'Utility'

w = port.optimization(model=model, rm=rm, obj=obj, rf=rf, l=l, hist=hist)

display(w.T)

# Plotting the composition of the portfolio

ax = rp.plot_pie(w=w, title='Sharpe Mean Variance', others=0.05, nrow=25, cmap = "tab20",
                 height=6, width=10, ax=None)

Extra code for replication purposes

!pip install yfinance riskfolio-lib --quiet --upgrade
!pip install matplotlib==3.2.2 --force-reinstall --quiet
import numpy as np
import pandas as pd
import yfinance as yf
import warnings

warnings.filterwarnings("ignore")
pd.options.display.float_format = '{:.4%}'.format

# Date range
start = '2010-01-01'
end = '2020-12-30'

# Tickers of long-term $BECKY assets
assets = ["AAPL", "ADDYY", "AMZN", "BBBY", "BBWI", "BUD", "CHD", 
          "CMG", "CVS", "DECK", "DEO", "DIS", "EL", "F", "FIZZ", 
          "GPS", "JWN", "LRLCY", "LULU", "LVMUY", "M",  "MO", "MTCH", 
          "NFLX", "NKE", "PVH", "RL", "SBUX", "STZ", "TAP", "TGT", 
          "TJX", "TPR", "UAA", "ULTA", "VFC", "WSM", "WWW", "YUM"]

# Contemporary $BECKY companies
# "ABBV", "COTY", "CRON", "EOLS", "ETSY", "FTCH", "GOOS", "INMD", 
# "LEVI", "LYFT", "MC", "META", "OR", "PINS", "PLNT", "PTON", 
# "SFIX", "SKIN", "SNAP", "SPOT", "TLRY",  "YETI", 

assets.sort()

# Downloading data
data = yf.download(assets, start = start, end = end)
data = data.loc[:,('Adj Close', slice(None))]
data.columns = assets

# Calculating returns
Y = data[assets].pct_change().dropna()
display(Y.head())

import missingno as msno
msno.heatmap(data[assets].pct_change())

In section 3.2 of the Tutorial 5, where:

############################################################
# Building a loop that estimate optimal portfolios on
# rebalancing dates
############################################################

begins,

I first get error: AttributeError: type object 'Portfolio' has no attribute 'Portfolio'

This I fixed using:

import riskfolio as rp
port = rp.HCPortfolio(returns=Y)

But then I get: AttributeError: 'HCPortfolio' object has no attribute 'assets_stats'

Is it possible you could update the tutorial, or point to the fix to run the rest of the example?

Hi,

I tried to use HRP with bounds on weights but does not seem to work.

# Building the portfolio object
port = rp.HCPortfolio(returns=ret_under_training, w_max=0.25, w_min=0.03)
w = port.optimization(model='HRP')
w

                                                    weights
Aegon Global Equity Market Neut                    0.636207
Artemis UK Select Fund I Acc                       0.025731
BNY Mellon Investment Funds - N                    0.084947
Baillie Gifford American Fund B                    0.013387
Baillie Gifford European Fund B                    0.015596
Baillie Gifford Global Income G                    0.024059
Baillie Gifford Pacific B Acc                      0.031928
Baillie Gifford Positive Change                    0.026448
Fidelity Funds - Global Technology Fund W-acc-gbp  0.020010
MI Chelverton UK Equity Growth                     0.098183
Vanguard FTSE Developed World e                    0.023504

Hi, this is an amazing library! I have a small feature request: Risk Return Trade-Off Relaxed Risk Parity Portfolio Optimization, which might be an interesting addition to your library. Please let me know what you think, and if its possible to be implemented in your library. I have written some simple code for this although its not in your library's style, but I am happy to put it here to help in any way if you want to implement this paper :)

When the objective is "sharpe" i see some constraints multiply variable k and 1000, what are these options for ??? For example constraints += [mu @ w - rf0 * k == 1] objective = cv.Minimize(risk * 1000)

Thank you

Once again thank you for this incredible library.

Is there an example or could you provide one regarding how to use BlackLitterman with market caps.

Like it's explained here: https://pyportfolioopt.readthedocs.io/en/latest/BlackLitterman.html#priors

I have a dataframe with daily market caps for each asset.

Hi Dany,

Thanks for your great work. Riskfolio-Lib is really fascinating.

I ran examples/Tutorial 1.ipynb and jupyter notebook was restarted As well as .py file in vs code. The notebook crashed at "port.efficient_frontier" in "2.3 Calculate efficient frontier", the error happened without any information. After tracing, I found it hang at line 2187 of Portfolio.py.

Can you please help?

Thank you very much in advance!

Michael

Hi, First of all, thank you for this wonderful library. I tried example 26 which is regarding the number of assets constraint and I am facing the following issue.

Appreciate any help. I also tried other MIP solvers based on the table below however faced the same issue.

I was happy to see the new versions, but un fortunatley I was not able to install any of them. I have three confings: W8.1, W10, ubuntu. I am using PyCharm, but I have tried to install directly with pip. None of them worked. Here is a detailed error note from W8.1 PyCharm:

Collecting Riskfolio-Lib==4.0.3 Using cached Riskfolio-Lib-4.0.3.tar.gz (12.9 MB) Preparing metadata (setup.py): started Preparing metadata (setup.py): finished with status 'error'

error: subprocess-exited-with-error

python setup.py egg_info did not run successfully. exit code: 1

[6 lines of output] Traceback (most recent call last): File "", line 2, in File "", line 34, in File "C:\Users\Louis\AppData\Local\Temp\pip-install-u0z7wn8g\riskfolio-lib_717f395aa901483bbb9e438b122fa86e\setup.py", line 6, in from pybind11.setup_helpers import Pybind11Extension, build_ext ModuleNotFoundError: No module named 'pybind11' [end of output]

note: This error originates from a subprocess, and is likely not a problem with pip. error: metadata-generation-failed

Encountered error while generating package metadata.

See above for output.

note: This is an issue with the package mentioned above, not pip. hint: See above for details.