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Tag: portfolio

pythonportfoliooptimizationcvxpyafter-work

Top 5 Python portfolio optimization packages after work

Five optimization/allocation libraries for after-work notebooks — skfolio 1.0.3, PyPortfolioOpt 1.6.0, Riskfolio-Lib 7.3.0, CVXPY 1.9.2, cvxportfolio 1.5.1. Separate from risk/vol metrics listicle. Not a fake ranking. Not investment advice.

pythonportfolio

risk

volatility

after-work

Top 5 Python packages for portfolio risk and volatility after work

A weeknight listicle: Riskfolio-Lib 7.3.0 (31 May 2026, Entropy Pooling + MVSK), PyPortfolioOpt risk_models, arch GARCH, cvxpy, and statsmodels/scipy. pip plus a CVaR / HRP / vol sketch. Not FinRL, not vectorbt/Nautilus/Lean, not a ranking contest. Not investment advice.

pythonpaperreinforcement-learningportfolioafter-work

Introducing A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem for after-work quants

Jiang, Xu & Liang (2017) map portfolio weights with EIIE nets, a Portfolio-Vector Memory for costs, and an explicit log-return reward on Poloniex 30-minute crypto. The FinRL-era template. Plain-language intro. Not investment advice.

pythonpaperreinforcement-learningportfolioafter-work

Introducing A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem for after-work quants

Jiang, Xu & Liang (2017) propose EIIE + Portfolio-Vector Memory + online batch learning: model-free RL that outputs portfolio weights on Poloniex. Not investment advice.

pythonpapercovarianceshrinkageportfolioafter-work

Introducing Honey, I Shrunk the Sample Covariance Matrix for after-work quants

Ledoit & Wolf (2004) shrink the noisy sample covariance toward a structured target so Markowitz weights stop exploding. Plain-language intro. Not investment advice.

pythonpaperreinforcement-learningportfolioafter-work

Introducing A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem for after-work quants

Jiang, Xu & Liang (2017) propose EIIE + Portfolio-Vector Memory + online batch learning: model-free RL that outputs portfolio weights on Poloniex. Not investment advice.

pythonpaperreinforcement-learningportfolioafter-work

Introducing A Deep Reinforcement Learning Framework for the Financial Portfolio Management Problem for after-work quants

Jiang, Xu & Liang (2017) propose EIIE + Portfolio-Vector Memory + online batch learning: model-free RL that outputs portfolio weights on Poloniex. Not investment advice.

pythonpaperportfoliohrpafter-work

Introducing MVO vs HRP vs RL Portfolio Comparison for after-work quants

Sen et al. (2023) compare mean-variance, hierarchical risk parity, and deep Q-learning portfolios on NIFTY50 and Indian sector stocks. Plain-language intro. Not investment advice.

pythonpaperensembleportfolioafter-work

Introducing Expert Aggregation for Financial Forecasting for after-work quants

Remlinger, Alasseur, Brière & Mikael (2021) mix thirteen Gu–Kelly–Xiu-style experts with Bernstein Online Aggregation so long-short books adapt when models rotate. Not investment advice.

pythonpapertransformerportfolioafter-work

Introducing Portfolio Transformer for Attention-Based Asset Allocation for after-work quants

Kisiel & Gorse (2022) train a Transformer to output portfolio weights that maximise cost-adjusted Sharpe—no separate return forecast step. Plain-language intro. Not investment advice.

pythonpaperportfolioautoencoderafter-work

Introducing Deep Portfolio Theory for after-work quants

Heaton, Polson & Witte (2016) propose Deep Portfolio Theory: encode–calibrate–validate hierarchical nets as a bridge from Markowitz. Plain-language intro. Not investment advice.