Застосування теорії арбітражного ціноутворення на основі Гаусівського часово-факторного аналізу (ЧФА) для прогнозування цін на криптовалюти
Анотація
У дослідженні продемонстровано, як модель Гаусівського TFA може бути застосована для прогнозування цін на криптовалюти. Розглянуто чотири підходи Розширеної Нормалізованої Радіальної Базисної Функції (ENRBF): N-адаптивна ENRBF, S-адаптивна ENRBF, ICA-ENRBF та ENRBF на основі APT-TFA, які використовуються для одночасового прогнозування ціни закриття чотирьох криптовалют (BTC, ETH, XRP і SOL) на фінансових ринках. Ми оцінили й порівняли ефективність запропонованих моделей, використовуючи звичайну середньоквадратичну помилку (RMSE) на щоденних даних за період з 1 січня 2020 року по 31 грудня 2024 року. Результати показали, що метод APT-TFA-ENRBF стабільно перевершував інші моделі, демонструючи найвищу точність прогнозування у зворотних і прямих інтервалах за найменшою RMSE. Це вказує на послідовну перевагу підходу APT-TFA-ENRBF над трьома іншими традиційними методами. Крім того, було встановлено, що метод ICA-ENRBF показав другий найкращий результат, тоді як N-ENRBF виявився найгіршим за ефективністю. Через те, що дослідження не враховує вплив інших чинників, які можуть суттєво впливати на прогнозування цін, ми рекомендуємо, аби майбутні дослідження зосередилися на глибшому вивченні гібридних методів, які дозволяють аналізувати ці чинники.
Завантаження
Посилання
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