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Prognostic modeling of predictive maintenance with survival analysis for mobile work equipment

Scientific reports, 2022-05, Vol.12 (1), p.8529-8529, Article 8529

2022

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Mid-price prediction based on machine learning methods with technical and quantitative indicators

PloS one, 2020-06, Vol.15 (6), p.e0234107-e0234107

2020

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Dynamics of investor spanning trees around dot-com bubble

PloS one, 2018-06, Vol.13 (6), p.e0198807-e0198807

2018

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Feature Engineering for Mid-Price Prediction With Deep Learning

IEEE access, 2019, Vol.7, p.82390-82412

2019

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Forecasting Financial Time Series Using Robust Deep Adaptive Input Normalization

Journal of signal processing systems, 2021-10, Vol.93 (10), p.1235-1251

2021

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Structure of Investor Networks and Financial Crises

Entropy (Basel, Switzerland), 2021-03, Vol.23 (4), p.381

2021

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Trade synchronization and social ties in stock markets

EPJ data science, 2022-11, Vol.11 (1), p.1-27, Article 54

2022

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Investigating Adoption of Free Beta Applications in a Platform-Based Business Ecosystem

The Journal of product innovation management, 2014-05, Vol.31 (3), p.451-465

2014

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Machine Learning for Forecasting Mid-Price Movements Using Limit Order Book Data

IEEE access, 2019, Vol.7, p.64722-64736

2019

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High-Performance Computing in Finance: Problems, Methods, and Solutions

1, 2018

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Deep Adaptive Input Normalization for Time Series Forecasting

IEEE transaction on neural networks and learning systems, 2020-09, Vol.31 (9), p.3760-3765

2020

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Temporal Attention-Augmented Bilinear Network for Financial Time-Series Data Analysis

IEEE transaction on neural networks and learning systems, 2019-05, Vol.30 (5), p.1407-1418

2019

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Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks

2017 IEEE 19th Conference on Business Informatics (CBI), 2017, Vol.1, p.7-12

2017

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Benchmark dataset for mid‐price forecasting of limit order book data with machine learning methods

Journal of forecasting, 2018-12, Vol.37 (8), p.852-866

2018

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Jump and Volatility Dynamics for the S&P 500: Evidence for Infinite-Activity Jumps with Non-Affine Volatility Dynamics from Stock and Option Markets

Review of Finance, 2017-03, Vol.21 (2), p.811-844

2017

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Valuation of option price in commodity markets described by a Markov-switching model: A case study of WTI crude oil market

Mathematics and computers in simulation, 2024-01, Vol.215, p.228-269

2024

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Augmented bilinear network for incremental multi-stock time-series classification

Pattern recognition, 2023-09, Vol.141, p.109604, Article 109604

2023

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Estimating and using GARCH models with VIX data for option valuation

Journal of banking & finance, 2014-06, Vol.43, p.200-211

2014

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Using Deep Learning for price prediction by exploiting stationary limit order book features

Applied soft computing, 2020-08, Vol.93, p.106401, Article 106401

2020

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Empirical deep hedging

Quantitative finance, 2023, Vol.23 (1), p.111-122

2023

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Temporal logistic neural Bag-of-Features for financial time series forecasting leveraging limit order book data

Pattern recognition letters, 2020-08, Vol.136, p.183-189

2020

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Forecasting jump arrivals in stock prices: new attention-based network architecture using limit order book data

Quantitative finance, 2019-12, Vol.19 (12), p.2033-2050

2019

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Coverage bias in business news: evidence and methodological implications

Management research review, 2018-04, Vol.41 (4), p.487-503

2018

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What drives the sensitivity of limit order books to company announcement arrivals?

Economics letters, 2017-10, Vol.159, p.65-68

2017

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Predicting the trading behavior of socially connected investors: Graph neural network approach with implications to market surveillance

Expert systems with applications, 2023-10, Vol.228, p.120285, Article 120285

2023

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Prognostic modeling of predictive maintenance with survival analysis for mobile work equipment

Mid-price prediction based on machine learning methods with technical and quantitative indicators

Dynamics of investor spanning trees around dot-com bubble

Feature Engineering for Mid-Price Prediction With Deep Learning

Forecasting Financial Time Series Using Robust Deep Adaptive Input Normalization

Structure of Investor Networks and Financial Crises

Trade synchronization and social ties in stock markets

Investigating Adoption of Free Beta Applications in a Platform-Based Business Ecosystem

Machine Learning for Forecasting Mid-Price Movements Using Limit Order Book Data

High-Performance Computing in Finance: Problems, Methods, and Solutions

Deep Adaptive Input Normalization for Time Series Forecasting

Temporal Attention-Augmented Bilinear Network for Financial Time-Series Data Analysis

Forecasting Stock Prices from the Limit Order Book Using Convolutional Neural Networks

Benchmark dataset for mid‐price forecasting of limit order book data with machine learning methods

Jump and Volatility Dynamics for the S&P 500: Evidence for Infinite-Activity Jumps with Non-Affine Volatility Dynamics from Stock and Option Markets

Valuation of option price in commodity markets described by a Markov-switching model: A case study of WTI crude oil market

Augmented bilinear network for incremental multi-stock time-series classification

Estimating and using GARCH models with VIX data for option valuation

Using Deep Learning for price prediction by exploiting stationary limit order book features

Empirical deep hedging

Temporal logistic neural Bag-of-Features for financial time series forecasting leveraging limit order book data

Forecasting jump arrivals in stock prices: new attention-based network architecture using limit order book data

Coverage bias in business news: evidence and methodological implications

What drives the sensitivity of limit order books to company announcement arrivals?

Predicting the trading behavior of socially connected investors: Graph neural network approach with implications to market surveillance

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