Academy notes
Articles and updates from SoloQuant Academy.
Tag: python
Abergel and Jedidi (2010) treat the limit order book as a Markov chain with Poisson arrivals, proving stationarity ideas and Brownian-like midprice scaling. Plain-language intro. Not investment advice.
Q Developer new signups are blocked; IDE plugins EOS 30 Apr 2027 per AWS. Start Kiro tonight on a tiny Python lab and review every change.
Kirtac and Germano (2024) compare OPT, BERT, FinBERT, and a classic finance dictionary on U.S. news sentiment and next-day returns—after costs in spirit for careful readers. Not investment advice.
Tetlock’s classic result: pessimism in a major WSJ column lines up with temporary downward pressure and higher trading volume—foundational alt-data intuition before modern transformers.
Yang, UY & Huang’s HKUST FinBERT is pretrained on financial communications—an alternative NLP backbone for filings and earnings text, distinct from Araci’s sentiment FinBERT.
Ke, Kelly, and Xiu (2019) show a supervised way to turn news text into return-prediction signals with careful screening. Plain-language intro for after-work Python NLP learners. Not investment advice.
Feng et al. add intentional perturbations during training so stock-movement models generalise better under noisy price features—a robustness habit you can borrow for NLP signals too.
Araci’s FinBERT fine-tunes BERT for financial sentiment so domain jargon scores more sensibly—then you can wire a Hugging Face checkpoint into a tiny daily-news feature pipeline.
Install Goose (Block/AAIF local agent), configure one LLM provider, and complete one after-work Python edit—MCP extensions optional on night one.
Install OpenCode’s TUI agent, connect a provider, and complete one reviewable after-work Python edit using Plan/Build and /undo.
Install Kiro CLI, sign in, and complete one small after-work Python edit—plus a short note on ACP for JetBrains/Zed when you are ready.
Install JetBrains AI Assistant in PyCharm or IntelliJ, open a tiny Python lab, run one Agents-mode task, and review every change—built for after-work evenings.
