Designing Robust Trend-following System: Behind the Scenes of Trend-following

Abstract

Trend-following has actively been on investors’ radar for the last few decades. The J.P. Morgan primer on momentum strategies (Kolanovic and Wei, 2015) provides an extensive review of the momentum strategies. The current paper focuses on a concrete trend-following solution and analyzes its properties alongside the practical implementation.
More concretely, the goal of the current paper is threefold:

• First, a trend-following signal based on statistical theory is proposed and we analytically investigate its properties. We reconcile the theoretical results with stylized facts about trend-following investing – ‘CTA smile’, the link to straddles and the better performance of so-called ‘slower’ signals.

• Second, based on the theoretical results we propose a prototype trend-following solution that uses a unified approach across assets and diversifies across time-frames. Its performance versus benchmarks and diversification properties for long-only portfolios are highlighted within simulation examples.

• Third, we elaborate on the portfolio and risk management of the trend-following strategy. We illustrate how the risk-budgeting and the Hierarchical Risk Parity (HRP) approaches can be adapted to the trend-following framework. Various methods to manage the transaction costs aspects of the strategy have also been discussed. In particular, we show how to limit the downside in the case of trendless market and how to take into account the implications of the carry component in many futures and FX forwards.

Keywords: trend-following, time-series momentum, CTA, AR(1)