We test the out-of-sample trading performance of model-free reinforcement learning (RL) agents and compare them with the performance of equally-weighted portfolios and traditional mean-variance (MV) optimization benchmarks. By dividing European and U.S. indices constituents into factor datasets,...

With the advent of Big Data, managing large-scale portfolios of thousands of securities is one of the most challenging tasks in the asset management industry. This study uses an evolutionary multi objective technique to solve large-scale portfolio optimisation problems with both long-term listed...

Robust pricing models often suffer from being overly conservative. This is due to lack of asymmetry information within the set of possible valuation distributions. However, even when information on asymmetry is available incorporating it within pricing models makes the characterization of...

This study examines whether the current discourses and debates at international level are aligned with Sustainable Development Goal (SDG) 7 for i) affordable energy and ii) clean energy. Guided by the overarching vision of SDG7, this study assumes that both "affordably energy" and "clean energy"...

We investigate if green bonds can act as a safe-haven asset for equity investors by analysing their relationship with stocks and other alternative safe havens, namely sovereign bonds and gold. Safe havens are defined as assets that exhibit zero or negative comovement with equity during a stock...

Robust pricing models often suffer from being overly conservative. This is due to lack of asymmetry information within the set of possible valuation distributions. However, even when information on asymmetry is available incorporating it within pricing models makes the characterization of...

This study examines whether the current discourses and debates at international level are aligned with Sustainable Development Goal (SDG) 7 for i) affordable energy and ii) clean energy. Guided by the overarching vision of SDG7, this study assumes that both "affordably energy" and "clean energy"...

With the advent of Big Data, managing large-scale portfolios of thousands of securities is one of the most challenging tasks in the asset management industry. This study uses an evolutionary multi objective technique to solve large-scale portfolio optimisation problems with both long-term listed...

We test the out-of-sample trading performance of model-free reinforcement learning (RL) agents and compare them with the performance of equally-weighted portfolios and traditional mean-variance (MV) optimization benchmarks. By dividing European and U.S. indices constituents into factor datasets,...

Agency problems in firms are known to influence suboptimal capital investment decisions. Using panel data of publicly listed firms in India, we find evidence that increased insider ownership is associated with lower investment efficiency, i.e. as insider ownership increases, firms show tendency...