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Do Solana Exchange Flows Matter? Hypothesis-Driven Evidence from Short-Term SOL Direction Forecasting

Author

Listed:
  • Yan Egorov

    (Center of Econometrics and Business Analytics, St. Petersburg State University, 199034 St. Petersburg, Russia)

  • Dmitry Grigoriev

    (Center of Econometrics and Business Analytics, St. Petersburg State University, 199034 St. Petersburg, Russia)

  • Daniil Zharikov

    (Center of Econometrics and Business Analytics, St. Petersburg State University, 199034 St. Petersburg, Russia)

  • Anastasia Grigorieva

    (Center of Econometrics and Business Analytics, St. Petersburg State University, 199034 St. Petersburg, Russia)

Abstract

This study examines whether centralized-exchange flows improve one-day-ahead forecasts of SOL return direction. Daily on-chain analysis (OCA) predictors are constructed from more than 41 million transfers above 1 SOL involving 101 labeled centralized-exchange hot wallets. Seven feature sets are evaluated using CatBoost, XGBoost, Random Forest, LSTM, and BiLSTM across four expanding-origin holdouts, with Elastic Net Logistic Regression as a linear benchmark. Technical analysis (TA) achieves the strongest average classification and transaction-cost-adjusted trading performance. OCA performs weakly alone and provides no stable average improvement when added to Baseline or TA. Selected flow- and volume-related subblocks outperform unrestricted OCA on individual descriptive metrics, but none achieves positive average trading performance. Observable Solana exchange flows therefore provide no robust standalone or incremental forecasting advantage beyond conventional predictors.

Suggested Citation

  • Yan Egorov & Dmitry Grigoriev & Daniil Zharikov & Anastasia Grigorieva, 2026. "Do Solana Exchange Flows Matter? Hypothesis-Driven Evidence from Short-Term SOL Direction Forecasting," Forecasting, MDPI, vol. 8(4), pages 1-27, July.
    • Handle: RePEc:gam:jforec:v:8:y:2026:i:4:p:65-:d:2003794
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