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The link between DFA portfolio performance, AI financial management, GDP, government bonds growth and DFA trade volumes

Author

Listed:
  • Alexey Mikhaylov

    (Financial University under the Government of the Russian Federation)

  • Muhammad Ishaq M. Bhatti

    (Universiti Brunei Darussalam School of Business and Economics
    SP Jain School of Global Management - Sydney Campus)

Abstract

The intention of the article is to delve into digital financial assets (DFA) portfolio price growth, financial management based on artificial intelligence (AI), GDP, government bonds growth (GBG) and DFA trade volumes within the highly dynamic market environment of Russia. This study aims to make a significant contribution by providing methods (statistical methods and fuzzy logic) for investors to identify and select the most optimal long-term portfolio from the pool of 218 digital financial assets which is available in the Russian market. It is important to acknowledge the fact that companies listed as digital financial asset operators often offer multiple classes of these assets for trading, and as such, investors are only able to trade the floating digital financial assets. Nevertheless, owing to the relatively short history of digital financial assets and the presence of significant standard deviations in DFA returns within the market, there still exists a level of uncertainty regarding the sustainability of the price premium. In actuality, considering the impact of volatility, it becomes evident that the price premium did not exhibit statistical significance throughout the sample period. So, the novelty of study is creation new effective tools for researching the effectiveness of portfolio management for time series includes 416 daily observations for the period March, 2022 - October, 2023.

Suggested Citation

  • Alexey Mikhaylov & Muhammad Ishaq M. Bhatti, 2025. "The link between DFA portfolio performance, AI financial management, GDP, government bonds growth and DFA trade volumes," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(1), pages 339-356, February.
    • Handle: RePEc:spr:qualqt:v:59:y:2025:i:1:d:10.1007_s11135-024-01940-8
    DOI: 10.1007/s11135-024-01940-8
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