No arbitrage and a linear portfolio selection model
We propose a linear bi-objective optimization approach to the problem of finding a portfolio that maximizes average excess return with respect to a benchmark index while minimizing underperformance over a learning period. We establish some theoretical results linking classical No Arbitrage conditions to the existence of a feasible portfolio for our model that strictly outperforms the index. Empirical analyses on publicly available real-world financial datasets show the effectiveness of the model and confirm the described theoretical results.
Volume (Year): 33 (2013)
Issue (Month): 2 ()
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- Andrea Scozzari & Fabio Tardella & Sandra Paterlini & Thiemo Krink, 2012.
"Exact and heuristic approaches for the index tracking problem with UCITS constraints,"
Center for Economic Research (RECent)
081, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
- Andrea Scozzari & Fabio Tardella & Sandra Paterlini & Thiemo Krink, 2012. "Exact and Heuristic Approaches for the Index Tracking Problem with UCITS Constraints," Department of Economics 0685, University of Modena and Reggio E., Faculty of Economics "Marco Biagi".
- Carol Alexander & Anca Dimitriu, 2005. "Indexing, cointegration and equity market regimes," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(3), pages 213-231.
- Renato Bruni & Francesco Cesarone & Andrea Scozzari & Fabio Tardella, 2012. "A new stochastic dominance approach to enhanced index tracking problems," Economics Bulletin, AccessEcon, vol. 32(4), pages 3460-3470.
- Beasley, J. E. & Meade, N. & Chang, T. -J., 2003. "An evolutionary heuristic for the index tracking problem," European Journal of Operational Research, Elsevier, vol. 148(3), pages 621-643, August.
- Dose, Christian & Cincotti, Silvano, 2005. "Clustering of financial time series with application to index and enhanced index tracking portfolio," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 145-151.
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