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pythonpaperdeep-learningfactor-modelsafter-work

Introducing Deep Factor Model for after-work quants

Nakagawa, Uchida & Aoshima (2018) explore deep neural nets for factor-style return modelling from characteristics. Plain-language intro. Not investment advice.

pythonpaperipcafactor-modelsafter-work

Introducing Characteristics Are Covariances (IPCA) for after-work quants

Kelly, Pruitt & Su (2019) introduce Instrumented PCA (IPCA): firm characteristics instrument latent factor loadings. Plain-language intro. Not investment advice.

pythonpaperfactor-modelsrisk-premiaafter-work

Introducing Asset Pricing with Omitted Factors for after-work quants

Giglio & Xiu show how to recover risk premia even when some true factors are missing from the model. Plain-language intro for after-work Python learners. Not investment advice.