Academy notes
Articles and updates from SoloQuant Academy.
Tag: python
Feng, Giglio & Xiu (2020) tame the factor zoo with double-selection LASSO: does your new factor add incremental information? Plain-language intro. Not investment advice.
Tan, Roberts & Zohren (2023) study spatio-temporal momentum—combining time and cross-asset structure. Plain-language intro. Not investment advice.
Wood, Roberts & Zohren (2021) explore slow momentum with fast reversion—multi-horizon trend vs mean-reversion features. Plain-language intro. Not investment advice.
Jegadeesh & Titman (1993) document cross-sectional momentum: buy recent winners, sell losers over 3–12 month horizons. Plain-language intro. Not investment advice.
Asness, Frazzini & Pedersen (2018) build a Quality-Minus-Junk (QMJ) factor from profitability, growth, and safety. Plain-language intro. Not investment advice.
Clone NVIDIA NOOA labs, run one class-as-agent sample, and study object-oriented agent design after work—carefully, as a lab.
Install DSPy, define a tiny typed module, run one predict/optimize loop—less hand-tuned prompting for after-work Python.
Install Haystack, wire a tiny Agent or pipeline with one tool, and learn production-minded NLP agents after work.
Install LlamaIndex, run a tiny Workflow (or agent) over one local doc, and learn event-driven RAG agents after work.
Install Hugging Face smolagents, run a tiny code-agent with one tool, and learn tool-calling without a heavyweight stack.
Semantic Kernel is converging into Microsoft Agent Framework—learn the migration path with one tiny agent tonight.
AutoGen is in maintenance—start with AG2 or Microsoft Agent Framework tonight; use AutoGen only as a migration contrast.
