In this work, we propose an ARMA(1,1)-GARCH(1,1) model with standard classical tempered stable (CTS) innovations for historical daily returns of 29 selected stocks. The non-Gaussian nature of the innovations captures the fat-tail property observed in data. The dependency between different assets...

Risk parity is a portfolio construction technique that scales sections of a portfolio—e.g., stocks, bonds, currencies, commodities—so that forecasted contributions to net portfolio risk match the budget. Because risks are measured from a point-estimate of covariance, the method is subject to...

Among professionals and academics alike, it is well known that active portfolio management is unable to provide additional risk-adjusted returns relative to their benchmarks. For this reason, passive wealth management has emerged in recent decades to offer returns close to benchmarks at a lower...

Transaction cost variance introduces a risk often neglected in portfolio optimization. We define a mean-variance portfolio optimization problem and show that including a transaction cost variance term significantly impacts the performance of these portfolios. Transaction cost variance is...

Inter-temporal risk parity is a strategy that rebalances risky assets and cash in order to target a constant level of ex-ante risk over time. When applied to equities and compared to a buy-and-hold portfolio it is known to improve the Sharpe ratio and reduce drawdowns. We apply inter-temporal...

This paper proposes a novel methodology to construct optimal portfolios that incorporates the occurrence of systemic events. Investors maximize a modified Sharpe ratio conditional on a systemic event. We solve the portfolio allocation problem analytically under the absence of short-selling...

This paper is about the issue of input parameter uncertainty in portfolio optimization in a discrete setting with finite states (such as the case in a world with different macroeconomic regimes). In such a setting, being unable to assign reliable point estimates to the probabilities (or...

We propose a new model formulation for a three-echelon supply network design problem incorporating the concept of relocatable modular capacities. A robust supply network configuration must be determined based on uncertain demand. Furthermore, by incorporating the conditional value at risk...

We examine the problem of decision making using a probabilistic model when there is material uncertainty concerning the accuracy of the model coupled with limited information about it. Such conditions could hold, for example, for the user of a complex commercial model of natural catastrophe...