Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2014, Article ID 618706, 8 pages
http://dx.doi.org/10.1155/2014/618706
Research Article

Performance Evaluation of Portfolios with Margin Requirements

1School of Business Administration, Hunan University, Changsha 410082, China
2Kent Business School, University of Kent, Canterbury CT2 7PE, UK

Received 6 January 2014; Accepted 7 February 2014; Published 12 March 2014

Academic Editor: Fenghua Wen

Copyright © 2014 Hui Ding et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J. Lintner, “The effect of short selling and margin requirements in perfect capital markets,” Journal of Financial and Quantitative Analysis, vol. 6, no. 5, pp. 1173–1195, 1971. View at Publisher · View at Google Scholar
  2. G. W. Schwert, “Margin requirements and stock volatility,” Journal of Financial Services Research, vol. 3, no. 2-3, pp. 153–164, 1989. View at Publisher · View at Google Scholar · View at Scopus
  3. G. A. Hardouvelis, “Margin requirements, volatility, and the transitory component of stock prices,” The American Economic Review, vol. 80, no. 4, pp. 736–762, 1990. View at Google Scholar
  4. D. A. Hsieh and M. H. Miller, “Margin regulation and stock market volatility,” The Journal of Finance, vol. 45, no. 1, pp. 3–29, 1990. View at Google Scholar
  5. P. J. Seguin, “Stock volatility and margin trading,” Journal of Monetary Economics, vol. 26, no. 1, pp. 101–121, 1990. View at Publisher · View at Google Scholar · View at Scopus
  6. P. H. Kupiec and S. A. Sharpe, “Animal spirits, margin requirements, and stock price volatility,” The Journal of Finance, vol. 46, no. 2, pp. 717–731, 1991. View at Publisher · View at Google Scholar
  7. P. J. Seguin and G. A. Jarrell, “The irrelevance of margin: evidence from the crash of '87,” The Journal of Finance, vol. 48, no. 4, pp. 1457–1473, 1993. View at Google Scholar
  8. T. Watanabe, “Margin requirements, positive feedback trading, and stock return autocorrelations: the case of Japan,” Applied Financial Economics, vol. 12, no. 6, pp. 395–403, 2002. View at Publisher · View at Google Scholar · View at Scopus
  9. T. Hirose, H. K. Kato, and M. Bremer, “Can margin traders predict future stock returns in Japan?” Pacific Basin Finance Journal, vol. 17, no. 1, pp. 41–57, 2009. View at Publisher · View at Google Scholar · View at Scopus
  10. H. Markowitz, “Portfolio selection,” Journal of Finance, vol. 7, pp. 77–91, 1952. View at Google Scholar
  11. M. Branda, “Reformulations of input-output oriented DEA tests with diversification,” Operations Research Letters, vol. 41, no. 5, pp. 516–520, 2013. View at Publisher · View at Google Scholar
  12. F. Wen and Z. Dai, “Modified Yabe-Takano nonlinear conjugate gradient method,” Pacific Journal of Optimization, vol. 8, no. 2, pp. 347–360, 2012. View at Google Scholar · View at Zentralblatt MATH
  13. C. Huang, H. Kuang, X. Chen, and F. Wen, “An LMI approach for dynamics of switched cellular neural networks with mixed delays,” Abstract and Applied Analysis, vol. 2013, Article ID 870486, 8 pages, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  14. F. Wen, Z. Li, C. Xie, and D. Shaw, “Study on the fractal and chaotic features of the Shanghai composite index,” Fractals-Complex Geometry Patterns and Scaling in Nature and Society, vol. 20, no. 2, pp. 133–140, 2012. View at Google Scholar · View at Zentralblatt MATH
  15. G. Qin, C. Huang, Y. Xie, and F. Wen, “Asymptotic behavior for third-order quasi-linear differential equations,” Advances in Differential Equations, vol. 2013, article 305, 2013. View at Publisher · View at Google Scholar
  16. C. Huang, G. Xu, X. Chen, and F. Wen, “Measuring and forecasting volatility in Chinese stock market using HAR-CJ-M model,” Abstract and Applied Analysis, vol. 2013, Article ID 143194, 13 pages, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  17. D. C. Heath and R. A. Jarrow, “Arbitrage, continuous trading, and margin requirements,” The Journal of Finance, vol. 42, no. 5, pp. 1129–1142, 1987. View at Publisher · View at Google Scholar
  18. D. Cuoco and H. Liu, “A martingale characterization of consumption choices and hedging costs with margin requirements,” Mathematical Finance, vol. 10, no. 3, pp. 355–385, 2000. View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  19. J. Liu and F. A. Longstaff, “Losing money on arbitrage: optimal dynamic portfolio choice in markets with arbitrage opportunities,” Review of Financial Studies, vol. 17, no. 3, pp. 611–641, 2004. View at Publisher · View at Google Scholar · View at Scopus
  20. G. Deng, T. Dulaney, and C. McCann, “Optimizing Portfolio Liquidation under risk-based margin requirements,” Journal of Finance and Investment Analysis, vol. 2, no. 1, pp. 121–153, 2013. View at Google Scholar
  21. Y. Zhou and Z. Wu, “Mean-variance portfolio selection with margin requirements,” Journal of Mathematics, vol. 2013, Article ID 726297, 9 pages, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  22. A. Charnes, W. W. Cooper, and E. Rhodes, “Measuring the efficiency of decision making units,” European Journal of Operational Research, vol. 2, no. 6, pp. 429–444, 1978. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  23. B. P. S. Murthi, Y. K. Choi, and P. Desai, “Efficiency of mutual funds and portfolio performance measurement: a non-parametric approach,” European Journal of Operational Research, vol. 98, no. 2, pp. 408–418, 1997. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  24. A. Basso and S. Funari, “A data envelopment analysis approach to measure the mutual fund performance,” European Journal of Operational Research, vol. 135, no. 3, pp. 477–492, 2001. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  25. A. Basso and S. Funari, “A generalized performance attribution technique for mutual funds,” University of Venice Working Paper, vol. 8, no. 2, pp. 10–28, 2001. View at Google Scholar
  26. K.-P. Chang, “Evaluating mutual fund performance: an application of minimum convex input requirement set approach,” Computers and Operations Research, vol. 31, no. 6, pp. 929–940, 2004. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  27. T. Joro and P. Na, “Portfolio performance evaluation in a mean-variance-skewness framework,” European Journal of Operational Research, vol. 175, no. 1, pp. 446–461, 2006. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  28. J. D. Lamb and K.-H. Tee, “Data envelopment analysis models of investment funds,” European Journal of Operational Research, vol. 216, no. 3, pp. 687–696, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  29. S. Lozano and E. Gutiérrez, “Data envelopment analysis of mutual funds based on second-order stochastic dominance,” European Journal of Operational Research, vol. 189, no. 1, pp. 230–244, 2008. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  30. W. Liu, J. Sharp, and Z. Wu, “Preference, production and performance in data envelopment analysis,” Annals of Operations Research, vol. 145, no. 1, pp. 105–127, 2006. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  31. R. D. Banker, A. Charnes, and W. W. Cooper, “Some models for estimating technical and scale efficiencies in data envelopment analysis,” Management Science, vol. 30, no. 9, pp. 1078–1092, 1984. View at Publisher · View at Google Scholar · View at Scopus
  32. M. J. Farrell, “The measurement of production efficiency,” Journal of Royal Statistical Society A, vol. 120, no. 3, pp. 253–290, 1957. View at Publisher · View at Google Scholar
  33. H. Leibenstein, “Allocative efficiency vs ‘X-efficiency’,” American Economic Review, vol. 56, pp. 392–415, 1966. View at Google Scholar
  34. W. B. Liu, W. Meng, X. X. Li, and D. Q. Zhang, “DEA models with undesirable inputs and outputs,” Annals of Operations Research, vol. 173, no. 1, pp. 177–194, 2010. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  35. Z. Zhou, S. Lui, C. Ma, D. Liu, and W. Liu, “Fuzzy data envelopment analysis models with assurance regions: a note,” Expert Systems with Applications, vol. 39, no. 2, pp. 2227–2231, 2012. View at Publisher · View at Google Scholar · View at Scopus
  36. Z. Zhou, L. Sun, W. Yang, W. Liu, and C. Ma, “A bargaining game model for efficiency decomposition in the centralized model of two-stage systems,” Computers & Industrial Engineering, vol. 64, no. 1, pp. 103–108, 2013. View at Publisher · View at Google Scholar
  37. Z. Zhou, M. Wang, H. Ding, C. Ma, and W. Liu, “Further study of production possibility set and performance evaluation model in supply chain DEA,” Annals of Operations Research, vol. 206, no. 1, pp. 585–592, 2013. View at Publisher · View at Google Scholar · View at Zentralblatt MATH
  38. Z. Zhou, W. Yang, C. Ma, and W. Liu, “A comment on “A comment on 'A fuzzy DEA/AR approach to the selection of flexible manufacturing systems” and ‘A fuzzy DEA/AR approach to the selection of flexible manufacturing systems’,” Computers & Industrial Engineering, vol. 59, no. 4, pp. 1019–1021, 2010. View at Publisher · View at Google Scholar · View at Scopus
  39. Z. Zhou, L. Zhao, S. Lui, and C. Ma, “A generalized fuzzy DEA/AR performance assessment model,” Mathematical and Computer Modelling, vol. 55, no. 11-12, pp. 2117–2128, 2012. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus
  40. K. Tone, “Slacks-based measure of efficiency in data envelopment analysis,” European Journal of Operational Research, vol. 130, no. 3, pp. 498–509, 2001. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at Scopus