This article develops a model that takes into account skewness risk in risk parity portfolios. In this framework, asset returns are viewed as stochastic processes with jumps or random variables generated by a Gaussian mixture distribution. This dual representation allows us to show that skewness...

In this paper, we apply the principle of Equal Risk Contribution (ERC) to a corporate bond index, an asset class so far left behind in this literature. Specifically, we rely on the Duration Times Spread (DTS) and demonstrate that it is a coherent metric for bond risk. We construct indexes based...

Volatility is usually considered as a synonym for risk. Mainstream financial theory states that higher portfolio volatility is translated into higher expected returns while diversification helps eliminate idiosyncratic risks. This leaves us with an apparent anomaly as low-risk (low-beta) stocks...

The concept of alternative risk premia is an extension of the factor investing approach. Factor investing consists in building long-only equity portfolios, which are directly exposed to common risk factors like size, value or momentum. Alternative risk premia designate non-traditional risk...

The concept of alternative risk premia can be viewed as an extension of the factor investing approach. Factor investing is a term that is generally dedicated to long-only equity risk factors. A typical example is the value equity strategy. Alternative risk premia designate non-traditional risk...

The capital asset pricing model (CAPM) developed by Sharpe (1964) is the starting point for the arbitrage pricing theory (APT). It uses a single risk factor to model the risk premium of an asset class. However, the CAPM has been the subject of important research, which has highlighted numerous...

In this article, we show how to take into account skewness risk in portfolio allocation. Until recently, this issue has been seen as a purely statistical problem, since skewness corresponds to the third statistical moment of a probability distribution. However, in finance, the concept of...

Classical quantitative finance models such as the Geometric Brownian Motion or its later extensions such as local or stochastic volatility models do not make sense when seen from a physics-based perspective, as they are all equivalent to a negative mass oscillator with a noise. This paper...

In this paper, we propose a new way to predict market returns for multi-assets (equity, fixed-income and commodity) by extracting features from macroeconomic data and performing machine learning algorithms for both regression and classification. Our approach aims to select robust models to build...

In this paper, we try to identify the relationship between the ESG scores and stocks' performance and risk measures. Using the ESG database of MSCI, we split the global investment universe into three regions: Europe, North America and Asia-Pacific. The investment universe of each region is...