Optimal portfolios with minimum capital requirements

Journal of Banking and Finance

Volumn 36, Issue 7, 2012, Pages 1928-1942

  Santos, André A P ^a   Nogales, Francisco J ^b   Ruiz, Esther ^b   Dijk, Dick Van ^c  

^a FEDERAL UNIVERSITY OF SANTA CATARINA   (Brazil)

^b UNIVERSIDAD CARLOS III DE MADRID   (Spain)

^c Erasmus University Rotterdam   (Netherlands)

Author keywords

Convex optimization; Multivariate GARCH; Out of sample evaluation; Stress testing

Indexed keywords

EID: 84860887972     PISSN: 03784266     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jbankfin.2012.03.001     Document Type: Article

References (47)

1. Aguilar O., West M. Bayesian dynamic factor models and portfolio allocation. Journal of Business and Economic Statistics 2000, 18:338-357.
2. Alexander C. Market Risk Analysis: Volume IV: Value at Risk Models 2009, Wiley.
3. Alexander G., Baptista A. Economic implications of using a mean-VaR model for portfolio selection: a comparison with mean-variance analysis. Journal of Economic Dynamics and Control 2002, 26:1159-1193.
4. Alexander G., Baptista A., Yan S. Mean-variance portfolio selection with value-at-risk constraints and discrete distributions. Journal of Banking and Finance 2007, 31:3761-3781.
5. Bank for International Settlements, 2006. International Convergence of Capital Measurement and Capital Standards. Basel Committee Publications, Bank For International Settlements.
6. Bank for International Settlements, 2009. Revisions to the Basel II Market Risk Framework. Basel Committee Publications, Bank For International Settlements.
7. Barndorff-Nielsen, O., Hansen, P., Lunde, A., Shephard, N., 2008. Multivariate Realised Kernels: Consistent Positive Semi-definite Estimators of the Covariation of Equity Prices with Noise and Non-synchronous Trading. Working Paper.
8. Bauwens L., Laurent S., Rombouts J. Multivariate GARCH models: a survey. Journal of Applied Econometrics 2006, 21:79-109.
9. Berkowitz J., O'Brien J. How accurate are value-at-risk models at commercial banks?. Journal of Finance 2002, 57:1093-1111.
10. Boyd S., Vandenbergue L. Convex Optimization 2004, Cambridge University Press, Cambridge.
11. Carriero A., Kapetanios G., Marcellino M. Forecasting exchange rates with a large Bayesian VAR. International Journal of Forecasting 2009, 25:400-417.
12. Chib S., Omori Y., Asai M. Multivariate stochastic volatility. Handbook of Financial Time Series 2009, 365-402. Springer Verlag, Berlin. T. Andersen, R. Davis, J.P. Kreiss, T. Mikosch (Eds.).
13. Christoffersen P. Value-at-risk models. Handbook of Financial Time Series 2009, 753-766. Springer Verlag, Berlin. T. Andersen, R. Davis, J.P. Kreiss, T. Mikosch (Eds.).
14. Committee of European Banking Supervisors, 2010. Aggregate Outcome of the 2010 EU Wide Stress Test Exercise Coordinated by CEBS in Cooperation with the ECB.
15. Cornuejols G., Tütüncü R. Optimization Methods in Finance 2007, Cambridge University Press, Cambridge.
16. Cuoco D., Liu H. An analysis of VaR-based capital requirements. Journal of Financial Intermediation 2006, 15:362-394.
17. Danielsson J., Zigrand J. On time-scaling of risk and the square-root-of-time rule. Journal of Banking and Finance 2006, 30:2701-2713.
18. DeMiguel V., Garlappi L., Nogales F., Uppal R. A generalized approach to portfolio optimization: improving performance by constraining portfolio norms. Management Science 2009, 55:798-812.
19. DeMiguel V., Garlappi L., Uppal R. Optimal versus naive diversification: how inefficient is the 1/N portfolio strategy?. Review of Financial Studies 2009, 22:1915-1953.
20. DeMiguel, V., Nogales, F.J., Uppal, R., 2010. Stock Return Serial Dependence and out-of-sample portfolio performance. Working Paper, London Business School.
21. De Pooter M., Martens M., van Dijk D. Predicting the daily covariance matrix for S&P 100 stocks using intraday data-but which frequency to use?. Econometric Reviews 2008, 27:199-229.
22. Diebold F., Hickman A., Inoue A., Schuermann T. Converting 1-day volatility to h-day volatility: scaling by is worse than you think. Risk 1998, 11:104-107.
23. Efron B., Gong G. A leisurely look at the bootstrap, the jackknife, and cross-validation. The American Statistician 1983, 37:36-48.
24. Engle R. Dynamic conditional correlation: a simple class of multivariate generalized autoregressive conditional heteroskedasticity models. Journal of Business & Economic Statistics 2002, 20:339-350.
25. Engle, R., Sheppard, K., 2001. Theoretical and Empirical Properties of Dynamic Conditional Correlation Multivariate GARCH. NBER Working Paper No. 8554.
26. Engle, R., Shephard, N., Sheppard, K., 2008. Fitting Vast Dimensional Time-Varying Covariance Models. Discussion Paper Series No. 403, Department of Economics, University of Oxford.
27. Grant, M., Boyd, S., 2008. Cvx: Matlab Software for Disciplined Convex Programming (Web Page and Software). http://stanford.edu/boyd/cvx.
28. Han Y. Asset allocation with a high dimensional latent factor stochastic volatility model. Review of Financial Studies 2006, 19:237-271.
29. Harvey A., Ruiz E., Shephard N. Multivariate stochastic variance models. Review of Economic Studies 1994, 61:247-264.
30. Hendricks D., Hirtle B. Bank capital requirements for market risk: the internal models approach. Economic Policy Review 1997, 3:1-12.
31. Jagannathan R., Ma T. Risk reduction in large portfolios: why imposing the wrong constraints helps. Journal of Finance 2003, 58:1651-1684.
32. Jorion P. How informative are value-at-risk disclosures?. Accounting Review 2002, 911-931.
33. Ledoit O., Wolf M. Improved estimation of the covariance matrix of stock returns with an application to portfolio selection. Journal of Empirical Finance 2003, 10:603-621.
34. Ledoit O., Wolf M. Honey, I shrunk the sample covariance matrix. Journal of Portfolio Management 2004, 30:110-119.
35. Ledoit O., Wolf M. Robust performance hypothesis testing with the sharpe ratio. Journal of Empirical Finance 2008, 15:850-859.
36. McAleer M., Amaral T.P., Jiménez-Martin J.A. A decision rule to minimize daily capital charges in forecasting value-at-risk. Journal of Forecasting 2010, 29:617-634.
37. Nocedal J., Wright S. Numerical Optimization 1999, Springer Verlag, Berlin.
38. Pérignon C., Deng Z., Wang Z. Do banks overstate their value-at-risk?. Journal of Banking & Finance 2008, 32:783-794.
39. Pesaran M., Schuermann T., Smith L. Forecasting economic and financial variables with global VARs. International Journal of Forecasting 2009, 25:642-675.
40. Politis D., Romano J. The stationary bootstrap. Journal of the American Statistical Association 1994, 89:1303-1313.
41. PTrignon C., Smith D. Diversification and value-at-risk. Journal of Banking & Finance 2010, 34:55-66.
42. Qi H., Sun D. Correlation stress testing for value-at-risk: an unconstrained convex optimization approach. Computational Optimization and Applications 2010, 45:427-462.
43. Santos, A.A.P., Nogales, F., Ruiz, E., 2009. Comparing Univariate and Multivariate Models to Forecast Portfolio Value-at-Risk. Working Paper 09-72, Department of Statistics, Universidad Carlos III de Madrid.
44. Sentana E. Mean-variance portfolio allocation with a value at risk constraint. Revista de Economfa Financiera 2003, 1:4-14.
45. Sharpe W. A simplified model for portfolio analysis. Management Science 1963, 9:277-293.
46. Sheppard, K., 2003. Multi-step estimation of multivariate GARCH models. In: Proceedings of the International ICSC. Symposium: Advanced Computing in Financial Markets.
47. Silvennoinen A., TerSsvirta T. Multivariate GARCH models. Handbook of Financial Time Series 2009, 201-229. Springer Verlag, Berlin. T. Andersen, R. Davis, J.P. Kreiss, T. Mikosch (Eds.).