Measuring of second–order stochastic dominance portfolio efficiency

Miloš Kopa

Kybernetika (2010)

  • Volume: 46, Issue: 3, page 488-500
  • ISSN: 0023-5954

Abstract

top
In this paper, we deal with second-order stochastic dominance (SSD) portfolio efficiency with respect to all portfolios that can be created from a considered set of assets. Assuming scenario approach for distribution of returns several SSD portfolio efficiency tests were proposed. We introduce a δ -SSD portfolio efficiency approach and we analyze the stability of SSD portfolio efficiency and δ -SSD portfolio efficiency classification with respect to changes in scenarios of returns. We propose new SSD and δ -SSD portfolio efficiency measures as measures of the stability. We derive a non-linear and mixed-integer non-linear programs for evaluating these measures. Contrary to all existing SSD portfolio inefficiency measures, these new measures allow us to compare any two δ -SSD efficient or SSD efficient portfolios. Finally, using historical US stock market data, we compute δ -SSD and SSD portfolio efficiency measures of several SSD efficient portfolios.

How to cite

top

Kopa, Miloš. "Measuring of second–order stochastic dominance portfolio efficiency." Kybernetika 46.3 (2010): 488-500. <http://eudml.org/doc/196506>.

@article{Kopa2010,
abstract = {In this paper, we deal with second-order stochastic dominance (SSD) portfolio efficiency with respect to all portfolios that can be created from a considered set of assets. Assuming scenario approach for distribution of returns several SSD portfolio efficiency tests were proposed. We introduce a $\delta $-SSD portfolio efficiency approach and we analyze the stability of SSD portfolio efficiency and $\delta $-SSD portfolio efficiency classification with respect to changes in scenarios of returns. We propose new SSD and $\delta $-SSD portfolio efficiency measures as measures of the stability. We derive a non-linear and mixed-integer non-linear programs for evaluating these measures. Contrary to all existing SSD portfolio inefficiency measures, these new measures allow us to compare any two $\delta $-SSD efficient or SSD efficient portfolios. Finally, using historical US stock market data, we compute $\delta $-SSD and SSD portfolio efficiency measures of several SSD efficient portfolios.},
author = {Kopa, Miloš},
journal = {Kybernetika},
keywords = {stochastic dominance; stability; SSD portfolio efficiency measure; stability; stochastic dominance; SSD portfolio efficiency measure},
language = {eng},
number = {3},
pages = {488-500},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Measuring of second–order stochastic dominance portfolio efficiency},
url = {http://eudml.org/doc/196506},
volume = {46},
year = {2010},
}

TY - JOUR
AU - Kopa, Miloš
TI - Measuring of second–order stochastic dominance portfolio efficiency
JO - Kybernetika
PY - 2010
PB - Institute of Information Theory and Automation AS CR
VL - 46
IS - 3
SP - 488
EP - 500
AB - In this paper, we deal with second-order stochastic dominance (SSD) portfolio efficiency with respect to all portfolios that can be created from a considered set of assets. Assuming scenario approach for distribution of returns several SSD portfolio efficiency tests were proposed. We introduce a $\delta $-SSD portfolio efficiency approach and we analyze the stability of SSD portfolio efficiency and $\delta $-SSD portfolio efficiency classification with respect to changes in scenarios of returns. We propose new SSD and $\delta $-SSD portfolio efficiency measures as measures of the stability. We derive a non-linear and mixed-integer non-linear programs for evaluating these measures. Contrary to all existing SSD portfolio inefficiency measures, these new measures allow us to compare any two $\delta $-SSD efficient or SSD efficient portfolios. Finally, using historical US stock market data, we compute $\delta $-SSD and SSD portfolio efficiency measures of several SSD efficient portfolios.
LA - eng
KW - stochastic dominance; stability; SSD portfolio efficiency measure; stability; stochastic dominance; SSD portfolio efficiency measure
UR - http://eudml.org/doc/196506
ER -

References

top
  1. Dentcheva, D., Henrion, R., Ruszczyński, A., 10.1137/060650118, SIAM J. Optim. 18 (2007), 322–333. MR2299687DOI10.1137/060650118
  2. Dentcheva, D., Ruszczyński, A., 10.1137/S1052623402420528, SIAM J. Optim. 14 (2003), 548–566. MR2048155DOI10.1137/S1052623402420528
  3. Dentcheva, D., Ruszczyński, A., 10.1007/s10107-003-0453-z, Math. Programming 99 (2004), 329–350. MR2039044DOI10.1007/s10107-003-0453-z
  4. Dentcheva, D., Ruszczyński, A., 10.1016/j.jbankfin.2005.04.024, J. Banking and Finance 30 (2006), 2, 433–451. DOI10.1016/j.jbankfin.2005.04.024
  5. Rudolf, G., Ruszczyński, A., 10.1137/070702473, SIAM J. Optim. 19 (2008), 3, 1326–1343. MR2460744DOI10.1137/070702473
  6. Hadar, J., Russell, W. R., Rules for ordering uncertain prospects, Amer. Econom. Rev. 59 (1969), 1, 25–34. 
  7. Hanoch, G., Levy, H., 10.2307/2296431, Rev. Econom. Stud. 36 (1969), 335–346. Zbl0184.45202DOI10.2307/2296431
  8. Hardy, G. H., Littlewood, J. E., Polya, G., Inequalities, Cambridge University Press, Cambridge 1934. Zbl0634.26008
  9. Kopa, M., Chovanec, P., A second-order stochastic dominance portfolio efficiency measure, Kybernetika 44 (2008), 2, 243–258. Zbl1154.91456MR2428222
  10. Kopa, M., Post, T., 10.1017/S0022109009990251, J. Financial and Quantitative Analysis 44 (2009), 5, 1103–1124. DOI10.1017/S0022109009990251
  11. Kopa, M., An efficient LP test for SSD portfolio efficiency, Working paper, available at: http://ssrn.com/abstract=1340863. 
  12. Kuosmanen, T., 10.1287/mnsc.1040.0284, Management Sci. 50 (2004), 10, 1390–1406. DOI10.1287/mnsc.1040.0284
  13. Levy, H., Stochastic Dominance: Investment Decision Making Under Uncertainty, Second edition. Springer Science, New York 2006. Zbl1109.91037MR2239375
  14. Luedtke, J., 10.1137/070707956, SIAM J. Optim. 19 (2008), 3, 1433–1450. Zbl1180.90215MR2466178DOI10.1137/070707956
  15. Ogryczak, W., Ruszczyński, A., 10.1137/S1052623400375075, SIAM J. Optim. 13 (2002), 60–78. MR1922754DOI10.1137/S1052623400375075
  16. Pflug, G. Ch., Some remarks on the value-at-risk and the conditional value-at-risk, In: Probabilistic Constrained Optimization: Methodology and Applications (S. Uryasev, ed.), Kluwer Academic Publishers, Norwell MA 2000, pp. 278–287. Zbl0994.91031MR1819417
  17. Post, T., 10.1111/1540-6261.00592, J. Finance 58 (2003), 1905–1932. DOI10.1111/1540-6261.00592
  18. Roman, D., Darby-Dowman, K., Mitra, G., 10.1007/s10107-006-0722-8, Math. Programming, Series B 108 (2006), 541–569. Zbl1138.91476MR2238714DOI10.1007/s10107-006-0722-8
  19. Römisch, W., Stability of stochastic programming problems, In: Stochastic Programming. Handbooks in Operations Research and Management Science 10 (A. Ruszczyński and A. Shapiro, eds.), Elsevier, Amsterdam 2003, pp. 483–554. MR2052760
  20. Rothschild, M., Stiglitz, J. E., Rules for ordering uncertain prospects, J. Economic Theory 2 (1969), 225–243. 
  21. Ruszczyński, A., Vanderbei, R. J., 10.1111/1468-0262.t01-1-00448, Econometrica 71 (2003), 4, 1287–1297. MR1995832DOI10.1111/1468-0262.t01-1-00448
  22. Uryasev, S., Rockafellar, R. T., 10.1016/S0378-4266(02)00271-6, J. Banking and Finance 26 (2002), 1443–1471. DOI10.1016/S0378-4266(02)00271-6
  23. Whitmore, G. A., Third degree stochastic dominance, Amer. Econom. Rev. 60 (1970), 457–459. 

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.