[HTML][HTML] A high-frequency trading volume prediction model using neural networks
X Xu, Y Zhang - Decision Analytics Journal, 2023 - Elsevier
It is an important task to make predictions of trading volumes of financial indices to market
participants. In the present study, we focus on this issue for the Chinese Stock Index 300 …
participants. In the present study, we focus on this issue for the Chinese Stock Index 300 …
High-frequency csi300 futures trading volume predicting through the neural network
X Xu, Y Zhang - Asian Journal of Economics and Banking, 2023 - emerald.com
Purpose For policymakers and participants of financial markets, predictions of trading
volumes of financial indices are important issues. This study aims to address such a …
volumes of financial indices are important issues. This study aims to address such a …
Neural network predictions of the high-frequency CSI300 first distant futures trading volume
X Xu, Y Zhang - Financial Markets and Portfolio Management, 2023 - Springer
Predictions of financial index trading volumes represent an essential issue to market
participants and policy makers. We investigate this problem for the high-frequency one …
participants and policy makers. We investigate this problem for the high-frequency one …
[HTML][HTML] Fisher dispersion index for multivariate count distributions: A review and a new proposal
CC Kokonendji, P Puig - Journal of Multivariate Analysis, 2018 - Elsevier
The Fisher dispersion index is very widely used to measure the departure of any univariate
count distribution from the equidispersed Poisson model. A multivariate extension has not …
count distribution from the equidispersed Poisson model. A multivariate extension has not …
[PDF][PDF] Forecasting the total market value of a shares traded in the Shenzhen stock exchange via the neural network
X Xu, Y Zhang - Economics Bulletin, 2022 - researchgate.net
Stock total market value forecasting is a significant issue for policy makers and investors.
This study explores usefulness of the nonlinear autoregressive neural network for this …
This study explores usefulness of the nonlinear autoregressive neural network for this …
[BOOK][B] Algorithmic trading and quantitative strategies
R Velu - 2020 - taylorfrancis.com
Algorithmic Trading and Quantitative Strategies provides an in-depth overview of this
growing field with a unique mix of quantitative rigor and practitioner's hands-on experience …
growing field with a unique mix of quantitative rigor and practitioner's hands-on experience …
[HTML][HTML] Temporal mixture ensemble models for probabilistic forecasting of intraday cryptocurrency volume
We study the problem of the intraday short-term volume forecasting in cryptocurrency multi-
markets. The predictions are built by using transaction and order book data from different …
markets. The predictions are built by using transaction and order book data from different …
Forecasting intraday trading volume: a kalman filter approach
An accurate forecast of intraday volume is a key aspect of algorithmic trading. This
manuscript proposes a state-space model to forecast intraday trading volume via the …
manuscript proposes a state-space model to forecast intraday trading volume via the …
Intraday volume percentages forecasting using a dynamic SVM-based approach
X Liu, KK Lai - Journal of Systems Science and Complexity, 2017 - Springer
This paper proposes a dynamic model to forecast intraday volume percentages by
decomposing the trade volume into two parts: The average part as the intraday volume …
decomposing the trade volume into two parts: The average part as the intraday volume …
Principal Trading Arrangements: When Are Common Contracts Optimal?
Many financial arrangements reference market prices that are yet to be realized at the time
of contracting and consequently susceptible to manipulation. Two of the most common such …
of contracting and consequently susceptible to manipulation. Two of the most common such …