Portfolio risk management in a data-rich environment

被引：2
作者：
Bouaddi M. [1 ]
Taamouti A. [2 ]
机构：
[1] Economics Department, American University in Cairo, New Cairo, 11835, AUC Avenue
[2] Departamento de Economía, Universidad Carlos III de Madrid, 28903 Getafe (Madrid)
来源：
Financial Markets and Portfolio Management | 2012年 / 26卷 / 4期
关键词：
Downside probability; Expected shortfall; Factor analysis; Portfolio performance; Portfolio weights modeling; Principal components; Value-at-risk;
D O I：
10.1007/s11408-012-0199-9
中图分类号：
学科分类号：
摘要：
We study risk assessment using an optimal portfolio in which the weights are functions of latent factors and firm-specific characteristics (hereafter, diffusion index portfolio). The factors are used to summarize the information contained in a large set of economic data and thus reflect the state of the economy. First, we evaluate the performance of the diffusion index portfolio and compare it to both that of a portfolio in which the weights depend only on firm-specific characteristics and an equally weighted portfolio. We then use value-at-risk, expected shortfall, and downside probability to investigate whether the weights-modeling approach, which is based on factor analysis, helps reduce market risk. Our empirical results clearly indicate that using economic factors together with firm-specific characteristics helps protect investors against market risk. © 2012 Swiss Society for Financial Market Research.
引用
收藏
页码：469 / 494
页数：25
相关论文
共 31 条
  • [1] Amemiya Y., Instrumental variable estimation for nonlinear factor analysis, Multivariate Analysis: Future Directions, 2, pp. 113-129, (1993)
  • [2] Amemiya Y., On nonlinear factor analysis, Proc Soc Stat Sect Annu Meet Am Stat Assoc, 92-96, pp. 290-294, (1993)
  • [3] Amemiya Y., Yalcin I., Nonlinear factor analysis as a statistical method, Stat Sci, 16, pp. 275-294, (2001)
  • [4] Bai J., Ng S., Determining the number of factors in approximate factor models, Econometrica, 70, pp. 191-221, (2002)
  • [5] Bai J., Ng S., Confidence intervals for diffusion index forecasts and inference for factor-augmented regressions, Econometrica, 74, pp. 1133-1150, (2006)
  • [6] Benzoni L., Collin-Dufresne P., Goldstein R.S., Portfolio choice over the life-cycle when the stock and labor markets are cointegrated, J Finance, 62, pp. 2123-2167, (2007)
  • [7] Bernanke B., Kuttner K., What explains the stock market's reaction to Federal Reserve policy, J Finance, 60, pp. 1221-1257, (2005)
  • [8] Bouaddi M., Taamouti A., Portfolio selection in a data-rich environment, (2011)
  • [9] Brandt M.W., Santa-Clara P., Dynamic portfolio selection by augmenting the asset space, J Finance, 61, pp. 2187-2217, (2006)
  • [10] Brandt M.W., Santa-Clara P., Valkanov R., Parametric portfolio policies: exploiting characteristics in the cross section of equity returns, Rev Financial Stud, 22, pp. 3411-3447, (2009)
1234