Python based Quant Finance Models, Tools and Algorithmic Decision Making

My personal work on the numerical projects of a book called "A First Course in Stochastic Calculus".

Credit portfolio studio: amortization cashflows : PD/LGD/EAD/EL, stress (rate/unemp/collateral), CECL (PV), covenants, pricing — Streamlit

Aplikasi analisis probabilitas trading berbasis Dash Plotly yang mengubah data historis trading menjadi insight probabilistik untuk pengambilan keputusan yang lebih baik.

A modular Python framework for researching and backtesting multi-factor equity strategies using classical factors (Value, Momentum, Size), Fama–MacBeth regressions, IC/IR analysis, and long–short portfolio evaluation.

Designed a two-stage, end-to-end differentiable trading system in TensorFlow that generates and refines daily portfolio weights across ~800 assets using technical indicators. A simulated trading loop feeds back KPIs, enabling direct optimization of equity and Sharpe ratio via gradient-based training. It runs on Quantiacs.

Quant Finance portfolio

Trend analysis using candlestick & time series charts

Inspired by *Managing real-time risks and returns: The Thomson Reuters NewsScope Event Indices*