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Crypto – Equity Market Interdependence Analysis
HSE Economic Journal. 2025. Vol. 29. No. 3. P. 383–406.
Buchko A., Peresetsky A.
In recent years cryptocurrencies have gained popularity: institutional and retail investors as well as different trading companies started positively looking at crypto assets. As a result, the convergence level between cryptocurrencies and the traditional markets has changed a lot. Stocks deserve close attention because they are a key asset for many investors. This article explores the evolving relationship between crypto assets and the US stock market by focusing on the four largest cryptocurrencies: Bitcoin (BTCUSDT), Ethereum (ETHUSDT), Ripple (XRPUSDT), Binance Coin (BNBUSDT), and the US stock index (S&P500). Utilizing correlation analyses of returns and volatilities alongside Granger causality tests, the study reveals how these markets affect each other. To implement the analysis, 1-minute and 5-minute data for 4.5 years, from 2019 to mid-2024, was used. Employing intraday granular data distinguishes this study from earlier ones that used daily data, and also identifies conclusions that may be more interesting to market participants such as scalper traders. The results indicate that cryptocurrencies become more integrated with traditional financial markets during periods of global economic instability, such as COVID-19 in 2020 and geopolitical tensions in 2022. Moreover, according to Granger causality tests, connections become bidirectional in stressed years, indicating the mutual influence between stocks and cryptocurrencies. On the other hand, in quieter times, the level of interconnection is significantly reduced in terms of correlations. Granger causality results reveal mostly unidirectional relationships (the impact of the US stock market on all 4 cryptocurrencies) during calm periods.
М.: Московский Политех, 2026.
Основной целью конференции является освещение проблем, связанных с внедрением технологий искусственного интеллекта в управление городским хозяйством города Москвы. Участниками были представлены инновационные решения для оптимизации использования ресурсов и городской инфраструктуры. Особое внимание было уделено решению задач прогнозирования и аналитического моделирования для повышения эффективности работы городских систем.
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