Asset Rotation

This dataset provides historical and forecasted risk-parity asset allocation data for investors for five asset classes.

Monthly allocation estimates for five assets.

Dataset contains five asset series, available from 1959-06-30 onwards.

Tutorials are the best documentation — Asset Rotation Tutorial Tutorial

Input Datasets

Hundreds of economic indicators

Models Used

Imputation Models, Machine Learning

Model Outputs

Optimal Allocations

Description

This dataset provides historical and forecasted risk-parity asset allocation data for five major asset classes: bonds, equities, commodities, dollar, and real estate.

It offers monthly allocation estimates and return predictions, both historical and 8 years into the future, based on hundreds of economic indicators.

The data and accompanying visualization tools enable investors to analyze optimal allocations and asset rotation strategies over time.The data is presented in a monthly frequency, starting from November 1959.

Data Access

Returns All

Return predictions, historically and 8-years in the future.

import sovai as sov 
df_returns = sov.data("allocation/returns")

Allocation All

Historical allocations and future risk-parity allocations

import sovai as sov 
df_allocate = sov.data("allocation/all")

Data Dictionary

Column	Type	Description
date	date	Month end date
segment	string	past or future
bonds_w	float	Bonds allocation (0–1)
equities_w	float	Equities allocation (0–1)
commodities_w	float	Commodities allocation (0–1)
dollar_w	float	USD allocation (0–1)
real_estate_w	float	Real estate allocation (0–1)

Plot Access

Line Plot

Looking at the future and past prescribed allocations over-time

import sovai as sov 
sov.plot("allocation", "line")

Stacked Plot

Looking at the future and past prescribed allocations over-time

import sovai as sov 
sov.plot("allocation", "stacked")

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