Alternative Risk Premia investment products have attracted substantial interest of institutional investors in the recent decade, as they are supposed to provide risk premia other than traditional equity and bond premia in which investors already have exposure to. This article reviews the...

This study aims at analyzing the ability of managers of Alternative Risk Premia (ARP) portfolios to outperform benchmarks and to deliver alphas. Using a sample of more than 200 ARP indices, we first distinguish performance between allocation strategy and picking ability. Our first results show...

Alternative Risk Premia (ARP) are rule-based strategies. They should reward investors exposed to non-traditional systematic risk factors. Yet, allocation to ARP is not straightforward. First, there are many ARP indices proposed by different providers that claim to capture the same underlying...

In this paper, we focus on forward-looking Conditional Value at Risk measures (CVaR). We test two methodologies, namely, the method proposed by Barone-Adesi (2016) and the mixture distribution of Huggenberger, Zhang and Zhou (2018). Both allow the extraction of forward-looking risk measures...

Since the Markowitz mean-variance framework of 1952 and the subsequent discoveries of the CAPM and the APT, finance researchers have always strived to produce a reference performance measure adjusted for risk. With such a measure, any supplemental return would be denominated as “alpha”. But...

The problem we address here is the replication of a bond benchmark when only a fraction of the portfolio is invested for the replication. Our methodology is based on a minimization of the tracking error subject to a set of constraints, namely (1) the fraction invested for the replication, (2) a...

This paper proposes a Stochastic Programming (SP) approach for the calculation of the liquidity-adjusted Value-at-Risk (LVaR). The model presented in this paper offers an alternative to Almgren and Chriss’s mean-variance approach (1999 and 2000). In this research, a two-stage stochastic...