Tactical Investment Algorithms

11 Pages Posted: 30 Sep 2019 Last revised: 1 Oct 2019

See all articles by Marcos Lopez de Prado

Marcos Lopez de Prado

Cornell University - Operations Research & Industrial Engineering; True Positive Technologies

Date Written: September 26, 2019

Abstract

There are three fundamental ways of testing the validity of an investment algorithm against historical evidence: a) the walk-forward method; b) the resampling method; and c) the Monte Carlo method. By far the most common approach followed among academics and practitioners is the walk-forward method. Implicit in that choice is the assumption that a given investment algorithm should be deployed throughout all market regimes. We denote such assumption the “all-weather” hypothesis, and the algorithms based on that hypothesis “strategic investment algorithms” (or “investment strategies”).

The all-weather hypothesis is not necessarily true, as demonstrated by the fact that many investment strategies have floundered in a zero-rate environment. This motivates the problem of identifying investment algorithms that are optimal for specific market regimes, denoted “tactical investment algorithms.” This paper argues that backtesting against synthetic datasets should be the preferred approach for developing tactical investment algorithms. A new organizational structure for asset managers is proposed, as a tactical algorithmic factory, consistent with the Monte Carlo backtesting paradigm.

Keywords: Backtest overfitting, selection bias, multiple testing, quantitative investments, machine learning, all-weather hypothesis, strategic investment algorithm, tactical investment algorithm.

JEL Classification: G0, G1, G2, G15, G24, E44

Suggested Citation

López de Prado, Marcos, Tactical Investment Algorithms (September 26, 2019). Available at SSRN: https://ssrn.com/abstract=3459866 or http://dx.doi.org/10.2139/ssrn.3459866

Marcos López de Prado (Contact Author)

Cornell University - Operations Research & Industrial Engineering ( email )

237 Rhodes Hall
Ithaca, NY 14853
United States

HOME PAGE: http://www.orie.cornell.edu

True Positive Technologies ( email )

NY
United States

HOME PAGE: http://www.truepositive.com

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