Making Leveraged Exchange-Traded Funds Work for your Portfolio
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- S. G. Kou, 2002. "A Jump-Diffusion Model for Option Pricing," Management Science, INFORMS, vol. 48(8), pages 1086-1101, August.
- Bansal, Vipul K. & Marshall, John F., 2015. "A tracking error approach to leveraged ETFs: Are they really that bad?," Global Finance Journal, Elsevier, vol. 26(C), pages 47-63.
- Dang, D.M. & Forsyth, P.A., 2016. "Better than pre-commitment mean-variance portfolio allocation strategies: A semi-self-financing Hamilton–Jacobi–Bellman equation approach," European Journal of Operational Research, Elsevier, vol. 250(3), pages 827-841.
- Hubert Dichtl & Wolfgang Drobetz & Martin Wambach, 2016. "Testing rebalancing strategies for stock-bond portfolios across different asset allocations," Applied Economics, Taylor & Francis Journals, vol. 48(9), pages 772-788, February.
- Tim Leung & Ronnie Sircar, 2015. "Implied Volatility of Leveraged ETF Options," Applied Mathematical Finance, Taylor & Francis Journals, vol. 22(2), pages 162-188, April.
- Paolo Guasoni & Eberhard Mayerhofer, 2023. "Leveraged funds: robust replication and performance evaluation," Quantitative Finance, Taylor & Francis Journals, vol. 23(7-8), pages 1155-1176, August.
- Philippe Cogneau & Valeri Zakamouline, 2013. "Block bootstrap methods and the choice of stocks for the long run," Quantitative Finance, Taylor & Francis Journals, vol. 13(9), pages 1443-1457, September.
- Tim Leung & Matthew Lorig & Andrea Pascucci, 2014. "Leveraged {ETF} implied volatilities from {ETF} dynamics," Papers 1404.6792, arXiv.org, revised Apr 2015.
- Li, Yuying & Forsyth, Peter A., 2019. "A data-driven neural network approach to optimal asset allocation for target based defined contribution pension plans," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 189-204.
- Anarkulova, Aizhan & Cederburg, Scott & O’Doherty, Michael S., 2022. "Stocks for the long run? Evidence from a broad sample of developed markets," Journal of Financial Economics, Elsevier, vol. 143(1), pages 409-433.
- Pieter van Staden & Peter Forsyth & Yuying Li, 2024. "Smart leverage? Rethinking the role of Leveraged Exchange Traded Funds in constructing portfolios to beat a benchmark," Papers 2412.05431, arXiv.org, revised Mar 2025.
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This paper has been announced in the following NEP Reports:- NEP-RMG-2025-09-22 (Risk Management)
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