Mean variance and goal achieving portfolio for discrete-time market with currently observable source of correlations

Nikolai Dokuchaev

ESAIM: Control, Optimisation and Calculus of Variations (2010)

  • Volume: 16, Issue: 3, page 635-647
  • ISSN: 1292-8119

Abstract

top
The paper studies optimal portfolio selection for discrete time market models in mean-variance and goal achieving setting. The optimal strategies are obtained for models with an observed process that causes serial correlations of price changes. The optimal strategies are found to be myopic for the goal-achieving problem and quasi-myopic for the mean variance portfolio.

How to cite

top

Dokuchaev, Nikolai. "Mean variance and goal achieving portfolio for discrete-time market with currently observable source of correlations." ESAIM: Control, Optimisation and Calculus of Variations 16.3 (2010): 635-647. <http://eudml.org/doc/250718>.

@article{Dokuchaev2010,
abstract = { The paper studies optimal portfolio selection for discrete time market models in mean-variance and goal achieving setting. The optimal strategies are obtained for models with an observed process that causes serial correlations of price changes. The optimal strategies are found to be myopic for the goal-achieving problem and quasi-myopic for the mean variance portfolio. },
author = {Dokuchaev, Nikolai},
journal = {ESAIM: Control, Optimisation and Calculus of Variations},
keywords = {Discrete time market; multi-period market; myopic strategies; serial correlation; optimal portfolio; mean variance portfolio; goal achieving; discrete time market; optimal portfolio},
language = {eng},
month = {7},
number = {3},
pages = {635-647},
publisher = {EDP Sciences},
title = {Mean variance and goal achieving portfolio for discrete-time market with currently observable source of correlations},
url = {http://eudml.org/doc/250718},
volume = {16},
year = {2010},
}

TY - JOUR
AU - Dokuchaev, Nikolai
TI - Mean variance and goal achieving portfolio for discrete-time market with currently observable source of correlations
JO - ESAIM: Control, Optimisation and Calculus of Variations
DA - 2010/7//
PB - EDP Sciences
VL - 16
IS - 3
SP - 635
EP - 647
AB - The paper studies optimal portfolio selection for discrete time market models in mean-variance and goal achieving setting. The optimal strategies are obtained for models with an observed process that causes serial correlations of price changes. The optimal strategies are found to be myopic for the goal-achieving problem and quasi-myopic for the mean variance portfolio.
LA - eng
KW - Discrete time market; multi-period market; myopic strategies; serial correlation; optimal portfolio; mean variance portfolio; goal achieving; discrete time market; optimal portfolio
UR - http://eudml.org/doc/250718
ER -

References

top
  1. N.G. Dokuchaev, Dynamic portfolio strategies: quantitative methods and empirical rules for incomplete information. Kluwer, Boston (2002).  
  2. N. Dokuchaev, Saddle points for maximin investment problems with observable but non-predictable parameters: solution via heat equation. IMA J. Management Mathematics17 (2006) 257–276.  
  3. N. Dokuchaev, Discrete time market with serial correlations and optimal myopic strategies. European J. Oper. Res.177 (2007) 1090–1104.  
  4. N. Dokuchaev, Maximin investment problems for discounted and total wealth. IMA J. Management Mathematics19 (2008) 63–74.  
  5. N Dokuchaev, Optimality of myopic strategies for multi-stock discrete time market with management costs. European J. Oper. Res. (to appear).  
  6. N.G. Dokuchaev and U. Haussmann, Optimal portfolio selection and compression in an incomplete market. Quantitative Finance1 (2001) 336–345.  
  7. E. Dynkin and I. Evstigneev, Regular conditional expectations of correspondences. Theory Probab. Appl.21 (1976) 325–338.  
  8. D. Feldman, Incomplete information equilibria: separation theorem and other myths. Ann. Oper. Res.151 (2007) 119–149.  
  9. N.H. Hakansson, On optimal myopic portfolio policies, with and without serial correlation of yields. J. Bus.44 (1971) 324–334.  
  10. P. Henrotte, Dynamic mean variance analysis. Working paper, SSRN: (2002).  URIhttp://ssrn.com/abstract=323397
  11. C. Hipp and M. Taksar, Hedging general claims and optimal control. Working paper (2000).  
  12. H. Leland, Dynamic Portfolio Theory. Ph.D. Thesis, Harvard University, USA (1968).  
  13. D. Li and W.L. Ng, Optimal portfolio selection: multi-period mean-variance optimization. Math. Finance10 (2000) 387–406.  
  14. A. Lim, Quadratic hedging and mean-variance portfolio selection with random parameters in an incomplete market. Math. Oper. Res.29 (2004) 132–161.  
  15. A. Lim and X.Y. Zhou, Mean-variance portfolio selection with random parameters in a complete market. Math. Oper. Res.27 (2002) 101–120.  
  16. D.G. Luenberger, Optimization by Vector Space Methods. John Wiley, New York (1968).  
  17. H.M. Markowitz, Portfolio Selection: Efficient Diversification of Investment. New York: John Wiley & Sons (1959).  
  18. R. Merton, Lifetime portfolio selection under uncertainty: the continuous-time case. Rev. Economics Statistics51 (1969) 247–257.  
  19. J. Mossin, Optimal multi-period portfolio policies. J. Business41 (1968) 215–229.  
  20. S.R. Pliska, Introduction to mathematical finance: discrete time models. Blackwell Publishers (1997).  
  21. M. Schweizer, Variance-optimal hedging in discrete time. Math. Oper. Res.20 (1995) 1–32.  

NotesEmbed ?

top

You must be logged in to post comments.

To embed these notes on your page include the following JavaScript code on your page where you want the notes to appear.

Only the controls for the widget will be shown in your chosen language. Notes will be shown in their authored language.

Tells the widget how many notes to show per page. You can cycle through additional notes using the next and previous controls.

    
                

                
Note: Best practice suggests putting the JavaScript code just before the closing </body> tag.