On the quasi-sure superhedging duality with frictions

We prove the superhedging duality for a discrete-time financial market with proportional transaction costs under model uncertainty. Frictions are modelled through solvency cones as in the original model of Kabanov (Finance Stoch. 3:237–248, 1999) adapted to the quasi-sure setup of Bouchard and Nutz (Ann. Appl. Probab. 25:823–859, 2015). Our approach allows removing the restrictive assumption of no arbitrage of the second kind considered in Bouchard et al. (Math. Finance 29:837–860, 2019) and showing the duality under the more natural condition of strict no arbitrage. In addition, we extend the results to models with portfolio constraints.

Multi-Period Investment Strategies under Cumulative Prospect Theory

In this article, inspired by Shi et al., we investigate the optimal portfolio selection with one risk-free asset and one risky asset in a multiple period setting under the cumulative prospect theory (CPT) risk criterion. Compared with their study, our novelty is that we consider a stochastic benchmark and portfolio constraints. By performing a numerical analysis, we test the sensitivity of the optimal CPT investment strategies to different model parameters.

An Examination of the Benefits of Factor Investing in U.K. Stock Returns

This study uses the Bayesian approach of Wang (1998) to examine the benefits of factor investing in U.K. stock returns in the presence of market frictions. My study finds that factor investing provides significant performance benefits when the benchmark investment universe is the market index, even in the presence of market frictions such as portfolio constraints and trading costs. However when the benchmark investment universe includes industry portfolios, market frictions, such as no short selling constraints and trading costs, tends to eliminate the benefits of factor investing. Imposing less restrictive portfolio constraints, factor investing can generate significant performance for investors with higher risk aversion levels.