Fixed income investors favor higher yields with lower risk. Our objective in this paper is to outline an active fixed income strategy that maximizes yield and is protected against major risk factors affecting fixed income securities. In particular, we look at interest rate risk, credit risk,...

This paper proposes a machine learning approach to building investment strategies that addresses several drawbacks of a classic approach. To demonstrate our approach, we use a logistic regression algorithm to build a time-series dual momentum trading strategy on the S&P 500 Index. Our algorithm...

Continuously rebalanced long-short trades are similar to highly levered trades in that their PNL profile depends not only on the final distribution of return, but also on the realized co-variance structure of the asset pair. It's easily possible for both orientations of a rebalanced long-short...

While machine learning and its many variants are becoming established tools in quantitative finance, their application in a risk measurement context is less developed. This paper uses a scheme from probability theory and statistics – Gaussian Processes – and applies the corresponding...

We show how one can use deep neural networks with macro-economic data in conjunction with price-volume data in a walk-forward setting to do tactical asset allocation. Low cost publicly traded ETFs corresponding to major asset classes (equities, fixed income, real estate) and geographies (US,...

We improve on our Vigilant Asset Allocation (VAA) by the introduction of a separate “canary” universe for signaling the need for crash protection, using the concept of breadth momentum. The amount of cash is now governed by the number of canary assets with bad (non-positive) momentum. The...

The paper proposes a new approach to model risk measurement based on the Wasserstein distance between two probability measures. It formulates the theoretical motivation resulting from the interpretation of fictitious adversary of robust risk management. The proposed approach accounts for all...

In this work, we have found a risk model that improves the performance of Risk Targeting. Risk Targeting in portfolio construction is implemented to improve capital utilization in growing markets and systematically step away from risk scenarios. However, the performance of risk targeting varies...

We present a portfolio construction methodology for futures strategies that incorporates active trading and also borrows salient features from the risk-parity methodology. We document the evolution of expected risk and return based portfolio construction methodologies and propose a new...