Natural Language Processing on Stocks' Earnings Call Transcripts: An Investment Strategy Backtest Based on S&P Global Papers.

This repository contains a collection of functions to evaluate investment strategies regarding multiple testing concerns.

Replication data and code for "Strategic Asset Allocation Revisited" published on Substack: https://policytensor.substack.com/p/strategic-asset-allocation-revisited.

Quantitative platform for investment strategies with real-time data integration, supporting flexible portfolio management via UI/GUI

Portfolio Analyzer is a modular toolkit for advanced portfolio construction, optimization, and risk analytics. It features Black-Litterman blending, robust statistical estimation, Monte Carlo simulation, and interactive Jupyter workflows for quantitative investment research.

Implementation of financial optimization models and efficient frontiers

Autonomous multi-agent system for Private Equity due diligence. Scrapes, analyses, and synthesises investment memos using LangGraph and Python.

Time series modeling and comparative forecasting of AAPL and HON stock prices using regression, smoothing, and moving averages in R.

Conducted a case study to develop an investment strategy for car companies, leveraging technical analysis and machine learning for market insights

A new package designed to help users navigate the volatile memory market by providing structured, long-term investment strategies. Users input their current financial situation, risk tolerance, and in

📈 Optimize portfolio risk management and options pricing with a high-performance platform featuring Python bindings and an interactive web dashboard.

This project constructs an optimized portfolio for trading stocks using Capital Assets Pricing Model. Build by Quadratic Programming Techniques and apply constraints using Shape Ratio.

This project uses stochastic approximation algorithms to optimize investment strategies and queueing systems. Techniques include the Simultaneous Perturbation Stochastic Approximation (SPSA) for maximizing the Sharpe ratio and Stochastic Approximation (SA) for minimizing waiting times in a GI/GI/1 queue.

This project addresses the real-world portfolio optimization problem, going beyond classical mean-variance models. Actual portfolio construction involves discrete investment decisions, transaction costs, and monitoring constraints, making the problem a Mixed-Integer Optimization (MIO) challenge that is computationally intractable at scale

🔍 Analyze financial data seamlessly with the AutoGen Financial Analysis System, offering risk assessment and quantitative insights through a multi-Agent framework.

S&P 500 Recovery Pattern Analysis (1998-99 vs 2025-26): Comparative analysis of S&P 500 recovery patterns: 1998 Crisis vs 2025 Market Drop. Includes visualizations, statistical analysis, and trading strategies based on historical patterns.

Smarter investing made simple — an AI-driven portfolio analyzer that blends finance, data science, and intuition.

This project looks at the performance of the stock market Tech sector on the Nasdaq index, analyzing the relationship between Operating Cash Flow and Capex, and it’s effect on overall returns.

Analyzing seasonal performance trends across financial market sectors using Python and historical Yahoo Finance data.