| The impacts of asymmetry on modeling and forecasting realized volatility in Japanese stock markets |
2020 |
volatility, research_methods |
| Volatility Information Trading in the Option Market |
2008 |
volatility, microstructure |
| Volatility Disagreement in the Options Market |
2026 |
option_returns, volatility, financial_ml |
| Implied volatility surface predictability: the case of commodity markets |
2019 |
volatility, research_methods |
| Volatility Forecasting with Machine Learning and Intraday Commonality |
2023 |
volatility, financial_ml, research_methods |
| Volatility Forecasting and Return Prediction under Market Regimes: Evidence from High-Frequency Chinese Equity Data |
2026 |
volatility, research_methods |
| Incorporating prior financial domain knowledge into neural networks for implied volatility surface prediction |
2021 |
volatility, financial_ml |
| Whack-a-mole Online Learning: Physics-Informed Neural Network for Intraday Implied Volatility Surface |
2024 |
volatility, financial_ml |
| Finance-Informed Neural Network: Learning the Geometry of Option Pricing |
2026 |
volatility, financial_ml, research_methods |
| A Geometry-Aware Residual Correction of Hagan's SABR Implied Volatility Formula |
2026 |
volatility, financial_ml, research_methods |
| Continuous-time Modeling of Bid-Ask Spread and Price Dynamics in Limit Order Books |
2013 |
microstructure, execution_costs |
| HARNet: A Convolutional Neural Network for Realized Volatility Forecasting |
2022 |
volatility, financial_ml |
| Deep Learning Option Pricing with Market Implied Volatility Surfaces |
2025 |
volatility, financial_ml |
| THE NORMALIZING TRANSFORMATION OF THE IMPLIED VOLATILITY SMILE |
2011 |
volatility |
| Synthetic American Option Pricing via Jump-HMM-Driven Heston Implied Volatility |
2026 |
volatility, research_methods |
| Jump risk premia in the presence of clustered jumps |
2025 |
option_returns, volatility |
| Online Adaptive Machine Learning Based Algorithm for Implied Volatility Surface Modeling |
2018 |
volatility, financial_ml |
| Quantum Reservoir Computing for Realized Volatility Forecasting |
2026 |
volatility, financial_ml |
| From GARCH to Neural Network for Volatility Forecast |
2024 |
volatility, financial_ml |
| On Calibration Neural Networks for extracting implied information from American options |
2020 |
volatility, financial_ml |
| Pricing VIX Futures and Options With Good and Bad Volatility of Volatility |
2024 |
volatility, research_methods |
| Modeling and Forecasting Persistent Financial Durations |
2013 |
volatility, research_methods |
| MVA Transfer Pricing |
2016 |
microstructure, execution_costs |
| Machine learning for option pricing: an empirical investigation of network architectures |
2026 |
volatility, financial_ml |
| The Privacy Subsidy in Glosten-Milgrom: Bid-Ask Spread and Welfare under Flip-Noise Direction Observation |
2026 |
microstructure, execution_costs, research_methods |
| Option market making with hedging-induced market impact |
2026 |
microstructure, execution_costs |
| Multivariate Realized Volatility Forecasting with Graph Neural Network |
2021 |
volatility, financial_ml, microstructure |
| Axiomatic Market Making |
2026 |
microstructure |
| Forecasting Implied Volatility Smile Surface via Deep Learning and Attention Mechanism |
2019 |
volatility, financial_ml |
| Option Pricing with State-dependent Pricing Kernel |
2022 |
volatility, research_methods |
| "Market making" behaviour in an order book model and its impact on the bid-ask spread |
2010 |
microstructure, execution_costs |
| Dynamics of Bid-ask Spread Return and Volatility of the Chinese Stock Market |
2011 |
microstructure, execution_costs |
| Operator Deep Smoothing for Implied Volatility |
2025 |
volatility, financial_ml |
| The self-exciting nature of the bid-ask spread dynamics |
2023 |
microstructure, execution_costs |
| Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints |
2026 |
volatility, financial_ml |