Easy Way to Merge Return Forecasts across Securities and Horizons

2 Pages Posted: 4 Oct 2019 Last revised: 24 Mar 2020

See all articles by Anish Shah

Anish Shah

Investment Grade Modeling; Brown University - Division of Applied Mathematics

Date Written: September 24, 2019

Abstract

This is a way to merge the collective information of a set of return forecasts on securities and portfolios of different horizons into forecasts on security-horizon pairs, a form that can be used for investment decisions. Similar to Black-Litterman, the method unifies predictions via Kalman filter and yields the posterior mean and covariance of returns given the information. The inputs required are minimal: a vector of forecasts, vector of horizons, matrix of linear combinations (portfolios) being forecasted, covariance of noise in the forecasts, and mean and covariance of one period returns.

Keywords: forecasting, combining forecasts

JEL Classification: C58, G11

Suggested Citation

Shah, Anish, Easy Way to Merge Return Forecasts across Securities and Horizons (September 24, 2019). Available at SSRN: https://ssrn.com/abstract=3459184 or http://dx.doi.org/10.2139/ssrn.3459184

Anish Shah (Contact Author)

Investment Grade Modeling ( email )

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Cambridge, MA 02139
United States

HOME PAGE: http://www.linkedin.com/in/anishrshah

Brown University - Division of Applied Mathematics

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Providence, RI 02912
United States

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