Daily Volume Forecasting using High Frequency Predictors
By Leandro G. M. Alvim, C. N. D. Santos, Ruy Luiz Milidiu. 2010
16 citations recorded by the source corpus.
Subfields: Finance, Management Science and Operations Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Finance
- Alexandros Iosifidis
- Moncef Gabbouj
- Adamantios Ntakaris
- Dat Thanh Tran
- Juho Kanniainen
- Martin Magris
- Weiwei Jiang
In Management Science and Operations Research
- Adamantios Ntakaris
- Dat Thanh Tran
- Juho Kanniainen
- Alexandros Iosifidis
- Martin Magris
- Moncef Gabbouj
- M. Ugur Gudelek
- Omer Berat Sezer
Citations in the corpus
- Tensor representation in high-frequency financial data for price change prediction (2017, methodology): “Popular machine learning methods in HFT include regression analysis [1], [2], [3], [4], [5], multilayer feed forward network [6], [7], [8], convolutional neural network [9] , recurrent neural network [10], [11], [12].”
- Benchmark Dataset for Mid-Price Prediction of Limit Order Book data (2017, methodology): “[3] use Support Vector Regression (SVR) and Partial Least Squares (PLS) for trading volume forecasting for ten stocks of Bovespa.”