Bryan T. Kelly
Finance · 2011–2021
A researcher in the Science corpus: 18 papers; trusts 194 researchers and is trusted by 60 researchers here, as inferred from the citation graph.
Subfields
- Finance — 301 citations into it; #981 of 10,518 by trust here, #392 by citations
- Economics and Econometrics — 265 citations into it; #2,410 of 23,481 by trust here, #1,257 by citations
- Accounting — 120 citations into it; #4,640 of 8,970 by trust here, #2,278 by citations
- Statistics and Probability — 71 citations into it; #10,879 of 12,932 by trust here, #10,855 by citations
- Artificial Intelligence — 58 citations into it; #17,884 of 35,345 by trust here, #21,316 by citations
- Management Science and Operations Research — 54 citations into it; #3,397 of 11,946 by trust here, #2,355 by citations
- Strategy and Management — 43 citations into it
- Optimization & Training — 20 citations into it
Whom Bryan T. Kelly trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Jushan Bai
- Robert J. Barro
- Jun Pan
- Y. Amihud
- Tim Bollerslev
- Serena Ng
- James H. Stock
- Eugene F. Fama
- Eric R. Ziegel
- Martin Lettau
Who trusts Bryan T. Kelly overall
- Tim Bollerslev
- Turan G. Bali
- Shihao Gu
- Lawrence D. W. Schmidt
- Tao Chen
- Bruno Feunou
- Dashan Huang
- Linda Allen
- Jón Dańıelsson
- M. Forni
Papers from Bryan T. Kelly's perspective
Ordered by how strongly the researchers Bryan T. Kelly trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- The Three-Pass Regression Filter: A New Approach to Forecasting Using Many Predictors (2015) — 353 citations
- Tail Risk and Asset Prices (2014) — 749 citations
- Text as Data (2017) — 1,062 citations
- The Common Factor in Idiosyncratic Volatility: Quantitative Asset Pricing Implications (2014) — 341 citations
- Market Expectations in the Cross Section of Present Values (2012) — 473 citations
- Firm Volatility in Granular Networks (2013) — 150 citations
- Empirical Asset Pricing via Machine Learning (2018) — 2,086 citations
- Hedging Climate Change News (2019) — 1,044 citations
- Measuring Technological Innovation over the Long Run (2018) — 355 citations
- The Price of Political Uncertainty: Theory and Evidence from the Option Market (2014) — 702 citations
- Systemic Risk and the Macroeconomy: An Empirical Evaluation (2016) — 542 citations
- Testing Asymmetric-Information Asset Pricing Models (2011) — 565 citations
- Understanding momentum and reversal (2021) — 76 citations
- Is There A Replication Crisis In Finance? (2021) — 320 citations
- Autoencoder asset pricing models (2020) — 364 citations
- Intermediary Asset Pricing: New Evidence from Many Asset Classes (2017) — 553 citations
- Too-Systemic-To-Fail: What Option Markets Imply About Sector-Wide Government Guarantees (2016) — 236 citations
- Shaping Liquidity: On the Causal Effects of Voluntary Disclosure (2013) — 482 citations