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

title, description, keywords

title	description	keywords
relriskparity	This page provides a detailed guide on how to build a relaxed risk parity portfolio using the least squares approach. It includes usage instructions, parameters, and examples.	risk parity portfolio least squares approach portfolio optimization risk management investment strategies asset allocation yfinance data time series

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Build a relaxed risk parity portfolio based on least squares approach

Usage

relriskparity [-ve VERSION] [-rc RISK_CONTRIBUTION] [-pf PENAL_FACTOR] [-tr TARGET_RETURN] [-de SMOOTHING_FACTOR_EWMA] [-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
risk_parity_model	version of relaxed risk parity model: Possible values are: 'A': risk parity without regularization and penalization constraints 'B': with regularization constraint but without penalization constraint 'C': with regularization and penalization constraints	A	True	A, B, C
risk_contribution	Vector of risk contribution constraints	None	True	None
penal_factor	The penalization factor of penalization constraints. Only used with version 'C'.	1	True	None
target_return	Constraint on minimum level of portfolio's return	-1	True	None
smoothing_factor_ewma	Smoothing factor for ewma estimators	0.94	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	RRP_0	True	None

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Examples

2022 Apr 05, 14:08 (🦋) /portfolio/po/ $ relriskparity

 [3 Years] Relaxed risk parity portfolio based on least squares approach

     Weights
┏━━━━━━┳━━━━━━━━━┓
┃      ┃ Value   ┃
┡━━━━━━╇━━━━━━━━━┩
│ AAPL │ 13.42 % │
├──────┼─────────┤
│ AMZN │ 16.51 % │
├──────┼─────────┤
│ BA   │ 10.18 % │
├──────┼─────────┤
│ FB   │ 12.83 % │
├──────┼─────────┤
│ MSFT │ 14.36 % │
├──────┼─────────┤
│ T    │ 24.0 %  │
├──────┼─────────┤
│ TSLA │  8.68 % │
└──────┴─────────┘

Annual (by 252) expected return: 28.99%
Annual (by √252) volatility: 26.60%
Sharpe ratio: 1.0899

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