OpenBB/website/content/terminal/reference/portfolio/po/maxdiv.md

title, description, keywords

title	description	keywords
maxdiv	The maxdiv page is a comprehensive guide for maximizing portfolio diversification with parameters like covariance matrix estimation method, smoothing factor for ewma estimators, allocations, return methods, tolerances for nan values, and more. It also includes examples of use.	maxdiv portfolio diversification covariance matrix smoothing factor short allocation nan fill method historic period log returns return frequency long allocation

import HeadTitle from '@site/src/components/General/HeadTitle.tsx';

Maximizes the portfolio's diversification ratio

Usage

maxdiv [-cv {hist,ewma1,ewma2,ledoit,oas,shrunk,gl,jlogo,fixed,spectral,shrink}] [-de SMOOTHING_FACTOR_EWMA] [-vs SHORT_ALLOCATION] [-mt METHOD] [-ct CATEGORIES] [-p PERIOD] [-s START_PERIOD] [-e END_PERIOD] [-lr] [--freq {d,w,m}] [-mn MAX_NAN] [-th THRESHOLD_VALUE] [-v LONG_ALLOCATION] [--name NAME]

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Parameters

Name	Description	Default	Optional	Choices
covariance	Method used to estimate covariance matrix. Possible values are 'hist': historical method 'ewma1': exponential weighted moving average with adjust=True 'ewma2': exponential weighted moving average with adjust=False 'ledoit': Ledoit and Wolf shrinkage method 'oas': oracle shrinkage method 'shrunk': scikit-learn shrunk method 'gl': graphical lasso method 'jlogo': j-logo covariance 'fixed': takes average of eigenvalues above max Marchenko Pastour limit 'spectral': makes zero eigenvalues above max Marchenko Pastour limit 'shrink': Lopez de Prado's book shrinkage method	hist	True	hist, ewma1, ewma2, ledoit, oas, shrunk, gl, jlogo, fixed, spectral, shrink
smoothing_factor_ewma	Smoothing factor for ewma estimators	0.94	True	None
short_allocation	Amount to allocate to portfolio in short positions	0.0	True	None
nan_fill_method	Method used to fill nan values in time series, by default time. Possible values are: 'linear': linear interpolation 'time': linear interpolation based on time index 'nearest': use nearest value to replace nan values 'zero': spline of zeroth order 'slinear': spline of first order 'quadratic': spline of second order 'cubic': spline of third order 'barycentric': builds a polynomial that pass for all points	time	True	linear, time, nearest, zero, slinear, quadratic, cubic, barycentric
categories	Show selected categories	ASSET_CLASS, COUNTRY, SECTOR, INDUSTRY	True	None
historic_period	Period to get yfinance data from. Possible frequency strings are: 'd': means days, for example '252d' means 252 days 'w': means weeks, for example '52w' means 52 weeks 'mo': means months, for example '12mo' means 12 months 'y': means years, for example '1y' means 1 year 'ytd': downloads data from beginning of year to today 'max': downloads all data available for each asset	3y	True	1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max
start_period	Start date to get yfinance data from. Must be in 'YYYY-MM-DD' format		True	None
end_period	End date to get yfinance data from. Must be in 'YYYY-MM-DD' format		True	None
log_returns	If use logarithmic or arithmetic returns to calculate returns	False	True	None
return_frequency	Frequency used to calculate returns. Possible values are: 'd': for daily returns 'w': for weekly returns 'm': for monthly returns	d	True	d, w, m
max_nan	Max percentage of nan values accepted per asset to be considered in the optimization process	0.05	True	None
threshold_value	Value used to replace outliers that are higher to threshold in absolute value	0.3	True	None
long_allocation	Amount to allocate to portfolio	1	True	None
name	Save portfolio with personalized or default name	MAXDIV_0	True	None

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Examples

2022 Apr 05, 14:18 (🦋) /portfolio/po/ $ maxdiv

 [3 Years] Display a maximal diversification portfolio

     Weights
┏━━━━━━┳━━━━━━━━━┓
┃      ┃ Value   ┃
┡━━━━━━╇━━━━━━━━━┩
│ AAPL │  0.0 %  │
├──────┼─────────┤
│ AMZN │ 22.62 % │
├──────┼─────────┤
│ BA   │ 11.53 % │
├──────┼─────────┤
│ FB   │ 12.06 % │
├──────┼─────────┤
│ MSFT │  0.0 %  │
├──────┼─────────┤
│ T    │ 40.01 % │
├──────┼─────────┤
│ TSLA │ 13.75 % │
└──────┴─────────┘

Annual (by 252) expected return: 24.68%
Annual (by √252) volatility: 26.16%
Sharpe ratio: 0.9435

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