December 2019
Crypto-currencies and other innovative asset classes present a fundamental challenge for quantitative asset-allocation. Because the track record of innovative assets is by definition short, it is difficult to form reliable estimates of expected returns and covariance matrices needed as inputs for standard portfolio optimization. Even if such estimates are available, they may be useless to investors if the behavior of underlying assets changes over time. Building on the MinMax Drawdown Control framework of Chassang (2018), this paper proposes a conceptually attractive and empirically successful approach to build benchmark portfolios of crypto-currencies and other innovative assets.