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Alternative Prices Under Markowitz’s Portfolio Model for FOREX Transactions

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  • Krzysztof Bednarz

Abstract

Purpose: In Markowitz’s traditional portfolio analysis, only the close price is used to build an investment portfolio. This type of price is commonly regarded as an axiom. As such, this article aims to prove that the close price is not the best type of price. Using the close price means that a portfolio which appears optimal is far from it. Under certain assumptions, it can be demonstrated that the close price should not be used. Design/Methodology/Approach: For the purposes of this study, 20 currency pairs were selected for analysis, from which portfolios of two assets were created. However, the best portfolios were additionally selected based on three “research spaces”, five moving average lengths, and seven types of prices (including the close price). A total of 13,300 different portfolios of two assets were created. All portfolios were calculated using real Forex data. The author created an original subroutine for the MetaTrader4 trading platform to build this enormous number of portfolios. It enabled online data collection and calculation of the entire portfolio population. A time frame of 15 minutes (M15) was used for this purpose. Findings: Thanks to such a large research sample, it was proven that the close price is not the best for building an investment portfolio. Within six hours, one of the prices gave an actual result that was 11,133.3% higher than that for the portfolio with the close price. This study proved the following hypotheses: “Selecting an optimal portfolio (in the traditional sense) using the close price is not an optimal solution”, and “The close price is not the best price for building an investment portfolio.” Practical Implications: Empirically verified knowledge about the use of different types of prices may prove useful for all (investment companies, investors, researchers, students) who have so far only used the close price. Originality/Value: No one has yet combined statistical knowledge, portfolio analysis, and MetaTrader4 trading platform software with an M15 time frame. No other studies using portfolio analysis question the axiom of using the close price in any market (including the Forex market).

Suggested Citation

  • Krzysztof Bednarz, 2025. "Alternative Prices Under Markowitz’s Portfolio Model for FOREX Transactions," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 990-1003.
    • Handle: RePEc:ers:journl:v:xxviii:y:2025:i:2:p:990-1003
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    References listed on IDEAS

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    1. Fabio Maccheroni & Massimo Marinacci & Doriana Ruffino, 2013. "Alpha as Ambiguity: Robust Mean‐Variance Portfolio Analysis," Econometrica, Econometric Society, vol. 81(3), pages 1075-1113, May.
    2. Amita Sharma & Aparna Mehra, 2017. "Financial analysis based sectoral portfolio optimization under second order stochastic dominance," Annals of Operations Research, Springer, vol. 256(1), pages 171-197, September.
    3. Michael Ho & Zheng Sun & Jack Xin, 2015. "Weighted Elastic Net Penalized Mean-Variance Portfolio Design and Computation," Papers 1502.01658, arXiv.org, revised Oct 2015.
    4. Evangelos Ioannidis & Iordanis Sarikeisoglou & Georgios Angelidis, 2023. "Portfolio Construction: A Network Approach," Mathematics, MDPI, vol. 11(22), pages 1-24, November.
    5. Lyu, Benmeng & Wu, Boqian & Guo, Sini & Gu, Jia-Wen & Ching, Wai-Ki, 2024. "Robust online portfolio optimization with cash flows," Omega, Elsevier, vol. 129(C).
    6. Pascal Quiry & Fur Yann Le & Antonio Salvi & Maurizio Dallocchio, 2011. "Frequently Asked Questions in Corporate Finance," Post-Print hal-02298162, HAL.
    7. Krzysztof Bednarz, 2024. "Portfel Markowitza w transakcjach na rynku Forex," Bank i Kredyt, Narodowy Bank Polski, vol. 55(5), pages 603-622.
    8. Hui Zou & Trevor Hastie, 2005. "Addendum: Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(5), pages 768-768, November.
    9. Jianjun Gao & Duan Li, 2013. "Optimal Cardinality Constrained Portfolio Selection," Operations Research, INFORMS, vol. 61(3), pages 745-761, June.
    10. Hui Zou & Trevor Hastie, 2005. "Regularization and variable selection via the elastic net," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 67(2), pages 301-320, April.
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    JEL classification:

    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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