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Optimal Investment Portfolios for Internet Money Funds Based on LSTM and La-VaR: Evidence from China

Author

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  • Hanxiao Wang

    (College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, China)

  • Huizi Ma

    (College of Mathematics and Systems Science, Shandong University of Science and Technology, Qingdao 266590, China)

Abstract

The rapid development of Internet finance has impacted traditional investment patterns, and Internet money funds (IMFs) are involved extensively in finance. This research constructed a long short-term memory (LSTM) neural network model to predict the return rates of IMFs and utilized the value-at-risk (VaR) and liquidity-adjusted VaR (La-VaR) methods to measure the IMFs’ risk. Then, an objective programming model based on prediction and risk assessment was established to design optimal portfolios. The results indicate the following: (1) The LSTM model results show that the forecast curves are consistent with the actual curves, and the root-mean-squared error (RMSE) result is mere 0.009, indicating that the model is suitable for forecasting data with reliable time-periodic characteristics. (2) With unit liquidity cost, the La-VaR results match the actuality better than the VaR as they demonstrate that the fund-based IMFs (FUND) have the most significant risk, the bank-based IMFs (BANK) rank 2nd, and the third-party-based IMFs (THIRD) rank 3rd. (3) The programming model based on LSTM and the La-VaR can meet different investors’ preferences by adjusting the objectives and constraints. It shows that the designed models have more practical significance than the traditional investment strategies.

Suggested Citation

  • Hanxiao Wang & Huizi Ma, 2022. "Optimal Investment Portfolios for Internet Money Funds Based on LSTM and La-VaR: Evidence from China," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:16:p:2864-:d:885619
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    References listed on IDEAS

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    1. Jui-Cheng Hung & Jung-Bin Su & Matthew C. Chang & Yi-Hsien Wang, 2020. "The impact of liquidity on portfolio value-at-risk forecasts," Applied Economics, Taylor & Francis Journals, vol. 52(3), pages 242-259, January.
    2. Luya Li & Hongxun Li & Wei Wang, 2021. "Analysis of Financing Risk and Innovation Motivation Mechanism of Financial Service Industry Based on Internet of Things," Complexity, Hindawi, vol. 2021, pages 1-9, April.
    3. Febi, Wulandari & Schäfer, Dorothea & Stephan, Andreas & Sun, Chen, 2018. "The impact of liquidity risk on the yield spread of green bonds," Finance Research Letters, Elsevier, vol. 27(C), pages 53-59.
    4. Prasenjit Chakrabarti & Sudipta Sen, 2021. "Transmission of funding liquidity shocks in the options market: evidence from India," Applied Economics Letters, Taylor & Francis Journals, vol. 28(18), pages 1566-1570, October.
    5. Meryem Masmoudi & Fouad Ben Abdelaziz, 2018. "Portfolio selection problem: a review of deterministic and stochastic multiple objective programming models," Annals of Operations Research, Springer, vol. 267(1), pages 335-352, August.
    6. Benito Muela, Sonia & López Martín, Carmen & Arguedas Sanz, Raquel, 2017. "An Application Of Extreme Value Theory In Estimating Liquidity Risk," European Research on Management and Business Economics (ERMBE), Academia Europea de Dirección y Economía de la Empresa (AEDEM), vol. 23(3), pages 157-164.
    7. Huizi Ma & Lin Lin & Han Sun & Yue Qu & Lei Xie, 2021. "Research on the Dependence Structure and Risk Spillover of Internet Money Funds Based on C-Vine Copula and Time-Varying t-Copula," Complexity, Hindawi, vol. 2021, pages 1-11, August.
    8. Meryem Masmoudi & Fouad Ben Abdelaziz, 2017. "A chance constrained recourse approach for the portfolio selection problem," Annals of Operations Research, Springer, vol. 251(1), pages 243-254, April.
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