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Title:	An empirical comparison between kelly criterion and vince`s optimal F
Authors:	左瑞麟 Wu, M.-E. Wang, C.-H. Chung, W.-H. Tso, Raylin Yang, I.-H.
Contributors:	資訊科學系
Keywords:	Big data;Commerce;Backtesting;Empirical - comparisons;Financial transactions;Kelly criterion;Numerical experiments;Odds;Profit and loss;Trading strategies;Distributed computer systems
Date:	2015-12
Issue Date:	2017-08-09 17:27:25 (UTC+8)
Abstract:	In this paper, we compare the differences between traditional Kelly Criterion and Vince`s optimal f through backtesting actual financial transaction data. We apply a momentum trading strategy to the Taiwan Weighted Index Futures, and analyze its profit-and-loss vectors of Kelly Criterion and Vince`s optimal f, respectively. Our numerical experiments demonstrate that there is nearly 90% chance that the difference gap between the bet ratio recommended by Kelly criterion and and Vince`s optimal f lies within 2%. Therefore, in the actual transaction, the values from Kelly Criterion could be taken directly as the optimal bet ratio for funds control. © 2015 IEEE.
Relation:	Proceedings - 2015 IEEE International Conference on Smart City, SmartCity 2015, Held Jointly with 8th IEEE International Conference on Social Computing and Networking, SocialCom 2015, 5th IEEE International Conference on Sustainable Computing and Communications, SustainCom 2015, 2015 International Conference on Big Data Intelligence and Computing, DataCom 2015, 5th International Symposium on Cloud and Service Computing, SC2 2015, 806-810
Data Type:	conference
DOI link:	http://dx.doi.org/10.1109/SmartCity.2015.166
DOI:	10.1109/SmartCity.2015.166
Appears in Collections:	[Department of Computer Science ] Proceedings

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