mirror of
https://github.com/OpenBB-finance/OpenBB.git
synced 2026-10-29 05:21:48 +00:00
faca7ab67d
* remove hcp * add prams dict to statics * little controller bug * fix view bug * avoid crash if one stock * check params on setup * create parameter class * check and convert parameters using class * change params name to avoid confusion * create a parameter statics dict * change some funcs names * remove unused imports * remove default dict * optional type * add multi choices * cast only int and float * fix completer * fix bugs with parameter validation * fix bugs with parameter validation * add excel formatting * sdk needs mapping as well, controller takes care of this in terminal * small formating * add some safe guard try except * controller bugs * oops * change export path of parameters to portfolio folder * add more commands to scripts * catch optimization exception * log errors * black and exceptions * add flag to test * black * flake8 * forgot this * pylint * change defaults * fix ef default * fix bl * sync sdk defaults * sync last defaults * fix plot heat and add more choices to controller autocomplete * patch weights * fix wrong bool parsing Co-authored-by: James Maslek <jmaslek11@gmail.com>
551 lines
11 KiB
Python
551 lines
11 KiB
Python
from typing import List, Optional
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from openbb_terminal.helper_funcs import get_rf
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from openbb_terminal.portfolio.portfolio_optimization.parameters.Parameter import (
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Parameter,
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)
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PERIOD_CHOICES = [
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"1d",
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"5d",
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"1mo",
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"3mo",
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"6mo",
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"1y",
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"2y",
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"3y",
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"5y",
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"10y",
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"ytd",
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"max",
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]
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MEAN_RISK_CHOICES = [
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"MV",
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"MAD",
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"MSV",
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"FLPM",
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"SLPM",
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"CVaR",
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"EVaR",
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"WR",
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"ADD",
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"UCI",
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"CDaR",
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"EDaR",
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"MDD",
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]
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RISK_PARITY_CHOICES = [
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"MV",
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"MAD",
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"MSV",
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"FLPM",
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"SLPM",
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"CVaR",
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"EVaR",
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"CDaR",
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"EDaR",
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"UCI",
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]
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REL_RISK_PARITY_CHOICES = [
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"A",
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"B",
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"C",
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]
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HCP_CHOICES = [
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"MV",
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"MAD",
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"GMD",
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"MSV",
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"VaR",
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"CVaR",
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"TG",
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"EVaR",
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"RG",
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"CVRG",
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"TGRG",
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"WR",
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"FLPM",
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"SLPM",
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"MDD",
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"ADD",
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"DaR",
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"CDaR",
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"EDaR",
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"UCI",
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"MDD_Rel",
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"ADD_Rel",
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"DaR_Rel",
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"CDaR_Rel",
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"EDaR_Rel",
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"UCI_Rel",
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]
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RISK_CHOICES = {
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"mv": "MV",
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"mad": "MAD",
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"gmd": "GMD",
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"msv": "MSV",
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"var": "VaR",
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"cvar": "CVaR",
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"tg": "TG",
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"evar": "EVaR",
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"rg": "RG",
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"cvrg": "CVRG",
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"tgrg": "TGRG",
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"wr": "WR",
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"flpm": "FLPM",
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"slpm": "SLPM",
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"mdd": "MDD",
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"add": "ADD",
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"dar": "DaR",
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"cdar": "CDaR",
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"edar": "EDaR",
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"uci": "UCI",
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"mdd_rel": "MDD_Rel",
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"add_rel": "ADD_Rel",
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"dar_rel": "DaR_Rel",
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"cdar_rel": "CDaR_Rel",
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"edar_rel": "EDaR_Rel",
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"uci_rel": "UCI_Rel",
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}
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MEAN_CHOICES = [
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"hist",
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"ewma1",
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"ewma2",
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]
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CODEPENDENCE_CHOICES = [
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"pearson",
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"spearman",
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"abs_pearson",
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"abs_spearman",
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"distance",
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"mutual_info",
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"tail",
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]
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COVARIANCE_CHOICES = [
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"hist",
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"ewma1",
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"ewma2",
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"ledoit",
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"oas",
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"shrunk",
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"gl",
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"jlogo",
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"fixed",
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"spectral",
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"shrink",
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]
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OBJECTIVE_CHOICES = [
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"MinRisk",
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"Utility",
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"Sharpe",
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"MaxRet",
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]
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NCO_OBJECTIVE_CHOICES = [
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"MinRisk",
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"Utility",
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"Sharpe",
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"ERC",
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]
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LINKAGE_CHOICES = [
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"single",
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"complete",
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"average",
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"weighted",
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"centroid",
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"median",
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"ward",
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"dbht",
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]
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BINS_CHOICES = [
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"KN",
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"FD",
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"SC",
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"HGR",
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]
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FREQ_CHOICES = [
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"d",
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"w",
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"m",
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]
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METHOD_CHOICES = [
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"linear",
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"time",
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"nearest",
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"zero",
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"slinear",
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"quadratic",
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"cubic",
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"barycentric",
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]
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TIME_FACTOR = {
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"D": 252.0,
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"W": 52.0,
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"M": 12.0,
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}
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RISK_NAMES = {
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"mv": "volatility",
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"mad": "mean absolute deviation",
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"gmd": "gini mean difference",
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"msv": "semi standard deviation",
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"var": "value at risk (VaR)",
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"cvar": "conditional value at risk (CVaR)",
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"tg": "tail gini",
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"evar": "entropic value at risk (EVaR)",
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"rg": "range",
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"cvrg": "CVaR range",
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"tgrg": "tail gini range",
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"wr": "worst realization",
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"flpm": "first lower partial moment",
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"slpm": "second lower partial moment",
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"mdd": "maximum drawdown uncompounded",
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"add": "average drawdown uncompounded",
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"dar": "drawdown at risk (DaR) uncompounded",
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"cdar": "conditional drawdown at risk (CDaR) uncompounded",
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"edar": "entropic drawdown at risk (EDaR) uncompounded",
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"uci": "ulcer index uncompounded",
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"mdd_rel": "maximum drawdown compounded",
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"add_rel": "average drawdown compounded",
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"dar_rel": "drawdown at risk (DaR) compounded",
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"cdar_rel": "conditional drawdown at risk (CDaR) compounded",
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"edar_rel": "entropic drawdown at risk (EDaR) compounded",
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"uci_rel": "ulcer index compounded",
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}
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DRAWDOWNS = [
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"MDD",
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"ADD",
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"DaR",
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"CDaR",
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"EDaR",
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"UCI",
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"MDD_Rel",
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"ADD_Rel",
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"DaR_Rel",
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"CDaR_Rel",
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"EDaR_Rel",
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"UCI_Rel",
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]
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NAN_FILL_METHOD_CHOICES = [
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"linear",
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"time",
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"nearest",
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"zero",
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"slinear",
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"quadratic",
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"cubic",
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"barycentric",
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]
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TECHNIQUE_CHOICES = [
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"maxsharpe",
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"minrisk",
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"maxutil",
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"maxret",
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"maxdiv",
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"maxdecorr",
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"ef",
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"equal",
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"mktcap",
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"dividend",
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"blacklitterman",
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"riskparity",
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"relriskparity",
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"hrp",
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"herc",
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"nco",
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]
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# Parameter template files
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OPTIMIZATION_PARAMETERS = {
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"historic_period": Parameter(
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name="historic_period",
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type_=str,
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default="3y",
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choices=PERIOD_CHOICES,
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),
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"start_period": Parameter(
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name="start_period",
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type_=str,
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default="",
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),
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"end_period": Parameter(
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name="end_period",
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type_=str,
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default="",
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),
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"log_returns": Parameter(
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name="log_returns",
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type_=bool,
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default=False,
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),
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"return_frequency": Parameter(
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name="return_frequency",
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type_=str,
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default="d",
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choices=FREQ_CHOICES,
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),
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"max_nan": Parameter(
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name="max_nan",
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type_=float,
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default=0.05,
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),
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"threshold_value": Parameter(
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name="threshold_value",
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type_=float,
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default=0.3,
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),
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"nan_fill_method": Parameter(
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name="nan_fill_method",
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type_=str,
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default="time",
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choices=NAN_FILL_METHOD_CHOICES,
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),
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"risk_free": Parameter(
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name="risk_free",
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type_=float,
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default=get_rf(),
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),
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"significance_level": Parameter(
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name="significance_level",
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type_=float,
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default=0.05,
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),
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"technique": Parameter(
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name="technique",
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type_=str,
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default="maxsharpe",
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choices=TECHNIQUE_CHOICES,
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),
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"risk_measure": Parameter(
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name="risk_measure",
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type_=str,
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default="MV",
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choices=MEAN_RISK_CHOICES + RISK_PARITY_CHOICES + HCP_CHOICES,
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),
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"target_return": Parameter(
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name="target_return",
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type_=float,
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default=-1.0,
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),
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"target_risk": Parameter(
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name="target_risk",
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type_=float,
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default=-1.0,
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),
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"expected_return": Parameter(
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name="expected_return",
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type_=str,
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default="hist",
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choices=MEAN_CHOICES,
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),
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"covariance": Parameter(
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name="covariance",
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type_=str,
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default="hist",
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choices=COVARIANCE_CHOICES,
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),
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"smoothing_factor_ewma": Parameter(
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name="smoothing_factor_ewma",
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type_=float,
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default=0.94,
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),
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"long_allocation": Parameter(
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name="long_allocation",
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type_=float,
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default=1.0,
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),
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"short_allocation": Parameter(
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name="short_allocation",
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type_=float,
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default=0.0,
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),
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"risk_aversion": Parameter(
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name="risk_aversion",
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type_=float,
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default=1.0,
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),
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"amount_portfolios": Parameter(
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name="amount_portfolios",
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type_=int,
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default=100,
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),
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"random_seed": Parameter(
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name="random_seed",
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type_=int,
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default=123,
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),
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"tangency": Parameter(
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name="tangency",
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type_=bool,
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default=False,
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),
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"risk_contribution": Parameter(
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name="risk_contribution",
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type_=Optional[List[str]],
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default=None,
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),
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"risk_parity_model": Parameter(
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name="risk_parity_model",
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type_=str,
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default="A",
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choices=REL_RISK_PARITY_CHOICES,
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),
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"penal_factor": Parameter(
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name="penal_factor",
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type_=float,
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default=1.0,
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),
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"p_views": Parameter(
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name="p_views",
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type_=Optional[List[List[float]]],
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default=None,
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),
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"q_views": Parameter(
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name="q_views",
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type_=Optional[List[List[float]]],
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default=None,
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),
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"delta": Parameter(
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name="delta",
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type_=Optional[float],
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default=None,
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),
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"equilibrium": Parameter(
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name="equilibrium",
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type_=bool,
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default=True,
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),
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"optimize": Parameter(
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name="optimize",
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type_=bool,
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default=True,
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),
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"co_dependence": Parameter(
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name="co_dependence",
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type_=str,
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default="pearson",
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choices=CODEPENDENCE_CHOICES,
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),
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"cvar_simulations_losses": Parameter(
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name="cvar_simulations_losses",
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type_=int,
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default=100,
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),
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"cvar_simulations_gains": Parameter(
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name="cvar_simulations_gains",
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type_=Optional[int],
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default=None,
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),
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"cvar_significance": Parameter(
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name="cvar_significance",
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type_=Optional[float],
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default=None,
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),
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"linkage": Parameter(
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name="linkage",
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type_=str,
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default="single",
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choices=LINKAGE_CHOICES,
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),
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"amount_clusters": Parameter(
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name="amount_clusters",
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type_=Optional[int],
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default=None,
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),
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"max_clusters": Parameter(
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name="max_clusters",
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type_=int,
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default=10,
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),
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"amount_bins": Parameter(
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name="amount_bins",
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type_=str,
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default="KN",
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choices=BINS_CHOICES,
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),
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"alpha_tail": Parameter(
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name="alpha_tail",
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type_=float,
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default=0.05,
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),
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"leaf_order": Parameter(
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name="leaf_order",
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type_=bool,
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default=True,
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),
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"objective": Parameter(
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name="objective",
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type_=str,
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default="MinRisk",
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choices=OBJECTIVE_CHOICES + NCO_OBJECTIVE_CHOICES,
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),
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}
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# Model functions
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# TODO: The dictionary below should not be needed, we can input defaults in the Parameter directly
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# But since template variable names are different from functions argument variable names
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# we need to map them before removing this dictionary. When we standardize the names, we can remove this.
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TERMINAL_TEMPLATE_MAP = {
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"a_sim": "cvar_simulations_losses",
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"alpha": "significance_level",
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"alpha_tail": "alpha_tail",
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"n_portfolios": "amount_portfolios",
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"b_sim": "cvar_simulations_gains",
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"beta": "cvar_significance",
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"bins_info": "amount_bins",
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"codependence": "co_dependence",
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"covariance": "covariance",
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"d_ewma": "smoothing_factor_ewma",
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"delta": "delta",
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"end_date": "end_period",
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"equilibrium": "equilibrium",
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"freq": "return_frequency",
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"interval": "historic_period",
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"k": "amount_clusters",
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"leaf_order": "leaf_order",
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"linkage": "linkage",
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"log_returns": "log_returns",
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"max_k": "max_clusters",
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"maxnan": "max_nan",
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"mean": "expected_return",
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"method": "nan_fill_method",
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"objective": "objective",
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"optimize": "optimize",
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"p_views": "p_views",
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"penal_factor": "penal_factor",
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"q_views": "q_views",
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"seed": "random_seed",
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"risk_aversion": "risk_aversion",
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"risk_cont": "risk_contribution",
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"risk_free_rate": "risk_free",
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"risk_measure": "risk_measure",
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"version": "risk_parity_model",
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"start_date": "start_period",
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"tangency": "tangency",
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"target_return": "target_return",
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"target_risk": "target_risk",
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"technique": "technique",
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"threshold": "threshold_value",
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"value": "long_allocation",
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"value_short": "short_allocation",
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}
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