Universal portfolios with and without transaction costs

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Universal portfolios with and without transaction costs

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Annual Workshop on Computational Learning Theory archive
Proceedings of the tenth annual conference on Computational learning theory table of contents

Nashville, Tennessee, United States

Pages: 309 - 313

Year of Publication: 1997

ISBN:0-89791-891-6

Authors

Avrim Blum	School of Computer Science, Carnegie Mellon University, Pittsburgh, PA
Adam Kalai	School of Computer Science, Carnegie Mellon University, Pittsburgh, PA

Sponsors

AT&T Labs :
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGART: ACM Special Interest Group on Artificial Intelligence
Vanderbilt University : Vanderbilt University

Publisher

ACM New York, NY, USA

Bibliometrics

Downloads (6 Weeks): 22, Downloads (12 Months): 44, Citation Count: 5

Additional Information:

references cited by index terms collaborative colleagues

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Nicolò Cesa-Bianchi , Yoav Freund , David P. Helmbold , David Haussler , Robert E. Schapire , Manfred K. Warmuth, How to use expert advice, Proceedings of the twenty-fifth annual ACM symposium on Theory of computing, p.382-391, May 16-18, 1993, San Diego, California, United States [doi>10.1145/167088.167198]
	2	T.M. Cover. Universal portfolios. Math. Finance, 1(1):1-29. January 1991.
	3	T.M. Cover and E. Ordentlich. Universal portfolios with side information. IEEE Transactions on Information Theory, 42(2), March 1996.
	4	T.M. Cover and E. Ordentlich. The Cost of Achieving the Best Portfolio in Hindsight. Department of Statistics Technical Report NSF-90, Stanford University, 1996.
	5	T. M. Cover, Universal data compression and portfolio selection, Proceedings of the 37th Annual Symposium on Foundations of Computer Science, p.534, October 14-16, 1996
	6	M. H.A. Davis , A. R. Norman, Portfolio selection with transaction costs, Mathematics of Operations Research, v.15 n.4, p.676-713, Nov. 1990 [doi>10.1287/moor.15.4.676]
	7	A. DeSantis, G. Markowsky, and M. Wegman. Learning probabilistic prediction functions. In Proceedings of the 29th IEEE Symposium on Foundations of Computer Science, pages 110-119,Oct 1988.
	8	Dean P. Foster , Rakesh V. Vohra, A randomization rule for selecting forecasts, Operations Research, v.41 n.4, p.704-709, July–Aug. 1993 [doi>10.1287/opre.41.4.704]
	9	David Haussler , Jyrki Kivinen , Manfred Warmuth, TIGHT WORST-CASE LOSS BOUNDS FOR PREDICTING WITH EXPERT ADVICE, University of California at Santa Cruz, Santa Cruz, CA, 1994
	10	D. Helmbold, R. Schapire, Y. Singer, and M. Warmuth. On-line portfolio selection using multiplicative updates. Machine Learning: Proceedings of the Thirteenth International Conference, 1996.
	11	David P. Helmbold , Yoram Singer , Robert E. Schapire , Manfred K. Warmuth, A comparison of new and old algorithms for a mixture estimation problem, Proceedings of the eighth annual conference on Computational learning theory, p.69-78, July 05-08, 1995, Santa Cruz, California, United States [doi>10.1145/225298.225306]
	12	Jyrki Kivinen , Manfred Warmuth, EXPONENTIATED GRADIENT VERSUS GRADIENT DESCENT FOR LINEAR PREDICTORS, University of California at Santa Cruz, Santa Cruz, CA, 1994
	13	Erik Ordentlich , Thomas M. Cover, On-line portfolio selection, Proceedings of the ninth annual conference on Computational learning theory, p.310-313, June 28-July 01, 1996, Desenzano del Garda, Italy [doi>10.1145/238061.238161]
	14	Volodimir G. Vovk, Aggregating strategies, Proceedings of the third annual workshop on Computational learning theory, p.371-386, August 06-08, 1990, Rochester, New York, United States
	15	V. G. Vovk, A game of prediction with expert advice, Proceedings of the eighth annual conference on Computational learning theory, p.51-60, July 05-08, 1995, Santa Cruz, California, United States [doi>10.1145/225298.225304]

CITED BY 5

	Ran El-Yaniv, Competitive solutions for online financial problems, ACM Computing Surveys (CSUR), v.30 n.1, p.28-69, March 1998
	Lan-Jun Lao, An additive on-line portfolio selection algorithm, Systems Analysis Modelling Simulation, v.42 n.6, p.939-958, June 2002
	V. Vovk , C. Watkins, Universal portfolio selection, Proceedings of the eleventh annual conference on Computational learning theory, p.12-23, July 24-26, 1998, Madison, Wisconsin, United States
	Elad Hazan , Amit Agarwal , Satyen Kale, Logarithmic regret algorithms for online convex optimization, Machine Learning, v.69 n.2-3, p.169-192, December 2007
	Peter DeMarzo , Ilan Kremer , Yishay Mansour, Online trading algorithms and robust option pricing, Proceedings of the thirty-eighth annual ACM symposium on Theory of computing, May 21-23, 2006, Seattle, WA, USA