Abstract
Portfolio analytics is critical for identifying investment opportunities, keeping portfolios aligned with investment objectives, and monitoring portfolio risk and performance. Analytics-based portfolio management lets investment managers filter information quickly, take advantage of statistical arbitrage opportunities, and deal with inefficiencies, such as transaction costs incurred during trading and tax consequences of investment decisions. This article reviews some widely used approaches to portfolio analytics, discussing new trends in metrics, modeling approaches, and portfolio analytics system design. Topics include stock screening, text analytics, traditional and new uses for factor models, investment methodologies of recent interest (such as smart beta), new visualization and analytics features available from vendors and open source software, and cloud-based solutions for data management and analysis.
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