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...

Starting from well-known empirical stylised facts of financial time series, we develop dynamic portfolio protection trading strategies based on econometric methods. As a criterion for riskiness we consider the evolution of the value-at-risk spread from a GARCH model with normal innovations...

This paper introduces a new approach to constructing optimal mean-variance portfolios. The approach relies on a novel unconstrained regression representation of the mean-variance optimization problem combined with high-dimensional sparse-regression methods. Our estimated portfolio, under a mild...

Retirement income stream products are difficult for consumers to choose because of their high perceived risk, irreversibility, and high expenditure; little opportunity for social learning; and distant consequences. Yet many countries have shifted more responsibility for these choices to...

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...