使用GARCH模型预测股票波动率实战指南:Python量化投资技巧
from arch import arch_model am = arch_model(returns, vol='GARCH', dist='skewt') res = am.fit(update_freq=5) forecasts = res.forecast(horizon=10)
class VolatilityDataset(Dataset):
def __init__(self, features, targets, window=60):
self.x = [features[i-window:i] for i in range(window, len(features))]
self.y = targets[window:]
train_loader = DataLoader(VolatilityDataset(train_x, train_y), batch_size=64)