15 research outputs found

    Fund Management and Systemic Risk - Lessons from the Global Financial Crisis

    Get PDF
    Fund managers play an important role in increasing efficiency and stability in financial markets. But research also indicates that fund management in certain circumstances may contribute to the buildup of systemic risk and severity of financial crises. The global financial crisis provided a number of new experiences on the contribution of fund managers to systemic risk. In this article, we focus on these lessons from the crisis. We distinguish between three sources of systemic risk in the financial system that may arise from fund management: insufficient credit risk transfer to fund managers; runs on funds that cause sudden reductions in funding to banks and other financial entities; and contagion through business ties between fund managers and their sponsors. Our discussion relates to the current intense debate on the role the so-called shadow banking system played in the global financial crisis. Several regulatory initiatives have been launched or suggested to reduce the systemic risk arising from non-bank financial entities, and we briefly discuss the likely impact of these on the sources of systemic risk outlined in the article

    A Generalized Approach to Portfolio Optimization: Improving Performance by Constraining Portfolio Norms

    No full text
    We provide a general framework for finding portfolios that perform well out-of-sample in the presence of estimation error. This framework relies on solving the traditional minimum-variance problem but subject to the additional constraint that the norm of the portfolio-weight vector be smaller than a given threshold. We show that our framework nests as special cases the shrinkage approaches of Jagannathan and Ma (Jagannathan, R., T. Ma. 2003. Risk reduction in large portfolios: Why imposing the wrong constraints helps. J. Finance 58 1651-1684) and Ledoit and Wolf (Ledoit, O., M. Wolf. 2003. Improved estimation of the covariance matrix of stock returns with an application to portfolio selection. J. Empirical Finance 10 603-621, and Ledoit, O., M. Wolf. 2004. A well-conditioned estimator for large-dimensional covariance matrices. J. Multivariate Anal. 88 365-411) and the 1/N portfolio studied in DeMiguel et al. (DeMiguel, V., L. Garlappi, R. Uppal. 2009. Optimal versus naive diversification: How inefficient is the 1/N portfolio strategy? Rev. Financial Stud. 22 1915-1953). We also use our framework to propose several new portfolio strategies. For the proposed portfolios, we provide a moment-shrinkage interpretation and a Bayesian interpretation where the investor has a prior belief on portfolio weights rather than on moments of asset returns. Finally, we compare empirically the out-of-sample performance of the new portfolios we propose to 10 strategies in the literature across five data sets. We find that the norm-constrained portfolios often have a higher Sharpe ratio than the portfolio strategies in Jagannathan and Ma (2003), Ledoit and Wolf (2003, 2004), the 1/N portfolio, and other strategies in the literature, such as factor portfolios.portfolio choice, covariance matrix estimation, estimation error, shrinkage estimator, norm constraints
    corecore