2026 Q2 季度研究归档¶
本页是自动生成的书目与原始链接归档；自动筛选不等于编辑认可，也不评价作者结论或构成投资建议。
- 覆盖期间：2026-04-01 至 2026-06-30
- 原始收录：736
- 自动筛选记录：18
- 筛选来源：6
- 经审计来源归档：4
- 归档来源：4
主题分布¶
- 波动率与隐含波动率曲面：14
- 研究方法与稳健性：8
- 金融机器学习：6
- 执行与交易成本：4
- 期权市场微观结构：2
- 期权收益与横截面预测：1
自动筛选记录¶
- 2026-06-23 — How to Intraday Backtest Double Calendars | Driven By Data Ep. 137 · ORATS Video · 执行与交易成本、研究方法与稳健性
- 2026-06-18 — How Chicago Became the World’s Options, Vol, and Derivatives Capital (with Cboe’s Rob Hocking & Mandy Xu) · The Derivative by RCM Alternatives · 波动率与隐含波动率曲面、期权市场微观结构
- 2026-06-18 — Reciprocal Return Risk Premium and Option Returns · Journal of Futures Markets · 期权收益与横截面预测、波动率与隐含波动率曲面
- 2026-06-09 — Signs of a Market Top from the Options Market | Driven By Data Ep. 135 · ORATS Video · 波动率与隐含波动率曲面
- 2026-06-08 — Volatility Forecasting and Return Prediction under Market Regimes: Evidence from High-Frequency Chinese Equity Data · 原始来源 · arXiv Quantitative Finance History · 波动率与隐含波动率曲面、研究方法与稳健性
- 2026-06-02 — The Breakthrough Intraday Backtester for All Symbols | Driven By Data Ep. 134 · ORATS Video · 执行与交易成本
- 2026-05-29 — Inspectable Neural Markov Models for Non-Stationary Time Series · arXiv Quantitative Finance History · 波动率与隐含波动率曲面、金融机器学习
- 2026-05-27 — Using AI + ORATS CLI to Build an Options Research Agent | Driven By Data Ep. 133 · ORATS Video · 波动率与隐含波动率曲面
- 2026-05-26 — Using AI and the ORATS CLI to Build an Options Research Agent | Driven By Data Ep. 133 · ORATS Video · 波动率与隐含波动率曲面
- 2026-05-22 — Memory, Roughness, and Information Persistence in Financial Markets: A Structural Approach to Volatility Forecasting · arXiv Quantitative Finance History · 波动率与隐含波动率曲面、研究方法与稳健性
- 2026-05-20 — Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints · 原始来源 · arXiv Quantitative Finance History · 波动率与隐含波动率曲面、金融机器学习
- 2026-05-13 — Synthetic American Option Pricing via Jump-HMM-Driven Heston Implied Volatility · 原始来源 · arXiv Quantitative Finance History · 波动率与隐含波动率曲面、研究方法与稳健性
- 2026-05-09 — Robust financial calibration: a Bayesian approach for neural SDEs · arXiv Quantitative Finance History · 波动率与隐含波动率曲面、金融机器学习
- 2026-05-07 — A Geometry-Aware Residual Correction of Hagan's SABR Implied Volatility Formula · 原始来源 · arXiv Quantitative Finance History · 波动率与隐含波动率曲面、金融机器学习、研究方法与稳健性
- 2026-04-29 — Option market making with hedging-induced market impact · 原始来源 · arXiv Quantitative Finance History · 期权市场微观结构、执行与交易成本
- 2026-04-21 — End-to-End Large Portfolio Optimization for Variance Minimization with Neural Networks through Covariance Cleaning · arXiv Quantitative Finance History · 波动率与隐含波动率曲面、金融机器学习、执行与交易成本、研究方法与稳健性
- 2026-04-13 — Realised Volatility Forecasting: Machine Learning via Financial Word Embedding · arXiv Quantitative Finance History · 金融机器学习、研究方法与稳健性
- 2026-04-01 — Do Prediction Markets Forecast Cryptocurrency Volatility? Evidence from Kalshi Macro Contracts · arXiv Quantitative Finance History · 波动率与隐含波动率曲面、研究方法与稳健性
经审计来源归档¶
本节完整列出配置为季度归档的已审计来源；仅表示元数据与原始链接已接入，不代表内容质量或策略有效性背书。
- 2026-04-21 — Machine Forecast Disagreement · AQR-affiliated Crossref metadata
- 2026-04-10 — Effectiveness of Trading Pauses: Evidence from the Tokyo Stock Exchange · JPX official working-paper index
- 2026-04-07 — The subtle interplay between square-root impact, order imbalance & volatility: a unifying framework · CFM-affiliated Crossref metadata
- 2026-04 — T ail -GAN: Learning to Simulate Tail Risk Scenarios · Oxford-Man-affiliated Crossref metadata