Phân tích tư tưởng của nhân dân qua đoạn thơ: Những người vợ nhớ chồng… Những cuộc đời đã hóa sông núi ta trong Đất nước của Nguyễn Khoa Điềm
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This study builds a series of models to predict trading volume in European markets using different statistical methods. The analysis considers a number of aspects, such as special events (e.g. MSCI rebalances, futures expiries, or cross-market holidays), day-of-the-week effects, and the volume-price relation asymmetry, in order to perform contextual one-step ahead prediction. We investigate the prediction error for each calendar circumstance to infer a cross-stock event-oriented switching model for volume prediction. The study concludes by proposing a stock-specific out-of-sample meta model that is fit by selecting an initial stock-specific model yielding the best performance for the most recent observations.
Nội dung trích xuất từ tài liệu:
Developing a volume forecasting model
