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طراحی سبد بهینه پویای سرمایه گذاری با حداقل ریسک: شواهدی جدید از الگوی خودرگرسیون برداری متغیر در زمان
[Dynamic Optimal Portfolio Design with Minimum Risk: New Evidence from the Time Varying Parameter Vector Autoregression Model]

Author

Listed:
  • Farahanifard, Saeed
  • Rahimi Kahkashi, Sanaz
  • Roudari, Soheil

Abstract

This study aims to design an optimal investment portfolio in order to reduce risk and enhance returns. To this end, daily data of 10 companies listed on the Tehran Stock Exchange over the period from 08/08/2016 to 02/01/2024 were analyzed. The research methodology is based on the Time Varying Parameter Vector Autoregression (TVP VAR) model and employs the Minimum Variance Portfolio (MVP), Minimum Correlation Portfolio (MCP), and Minimum Connectedness Portfolio (MCoP) approaches for portfolio construction. The findings indicate that the portfolio with the minimum variance strategy yields the highest cumulative return. Under normal market conditions, the highest optimal weights are allocated to Damavand (19%), TAPICO (18%), and Seshahed (15%), whereas under bullish and bearish market conditions, the asset composition changes significantly. The analysis of dynamic optimal weights shows that some firms, such as Shetran and TAPICO, play a key role in risk hedging during specific periods. The results emphasize that the use of dynamic and time varying models enhances analytical accuracy and better reflects market realities. Accordingly, training investors in dynamic portfolio management and the use of advanced tools for portfolio adjustment is recommended. The findings have important implications for policymakers and market participants and highlight the necessity of designing flexible investment policies.

Suggested Citation

  • Farahanifard, Saeed & Rahimi Kahkashi, Sanaz & Roudari, Soheil, 2024. "طراحی سبد بهینه پویای سرمایه گذاری با حداقل ریسک: شواهدی جدید از الگوی خودرگرسیون برداری متغیر در زمان [Dynamic Optimal Portfolio Design with Minimum Risk: New Evidence from the Time Varying Parame," MPRA Paper 127332, University Library of Munich, Germany, revised 16 Feb 2025.
    • Handle: RePEc:pra:mprapa:127332
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    References listed on IDEAS

    as
    1. El Hedi Arouri, Mohamed & Jouini, Jamel & Nguyen, Duc Khuong, 2011. "Volatility spillovers between oil prices and stock sector returns: Implications for portfolio management," Journal of International Money and Finance, Elsevier, vol. 30(7), pages 1387-1405.
    2. Nikolaos Antonakakis & Ioannis Chatziantoniou & David Gabauer, 2020. "Refined Measures of Dynamic Connectedness based on Time-Varying Parameter Vector Autoregressions," JRFM, MDPI, vol. 13(4), pages 1-23, April.
    3. Bai, Lan & Wei, Yu & Zhang, Jiahao & Wang, Yizhi & Lucey, Brian M., 2023. "Diversification effects of China's carbon neutral bond on renewable energy stock markets: A minimum connectedness portfolio approach," Energy Economics, Elsevier, vol. 123(C).
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    Keywords

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions

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