Solutions to Daily Coding Problem questions

MLP approach to predict real-time financial market data and select the right trades to execute.

Algorithmic trading client and strategies for a Jane Street–style electronic exchange: pennying market-making, micro-MACD, bond maker, ETF/ADR arbitrage.

A gamified learning platform to help BSc Math students become top 1% Quant Researchers with Ben 10 theme

An example of web application written in OCAML

My answers to problem sets for Aizu, AdventofCode, Janestreet Puzzles, CodeChef, Codeforces, CSES, Deep-ML, DMOJ, EOlymp, HackerRank, Kattis, KiloNova, Leetcode, LibreOJ, Perl Weekly Review, Project Euler, SPOJ and Timus judges.

Jane Street Real-Time Market Data Forecasting 2025: https://www.kaggle.com/competitions/jane-street-real-time-market-data-forecasting

📉Market Forecasting 🧠ML for Trading 📊Time Series 🧮Ensemble Learning

My attempt at Jane Street's puzzles

A hardware-first exploration of Advent of Code 2025, implementing each puzzle as a cycle-accurate FPGA design in Hardcaml, using streaming UART I/O, explicit memory pipelines, and finite-state schedulers instead of software control flow.

Solutions to Jane Street Monthly Puzzles

🚀 Implement algorithmic trading strategies for a Jane Street-style exchange, featuring market-making, arbitrage, and momentum signals.

Solves a machine learning problem using three different models (XGBoost, Neural Network, Logistic Regression)

A statistics display for the Jane Street trading game, Figgie.

Spring Insight participant Jane Street. Software Engineering Department. Ocaml workshop

Solution to Jane Street puzzle Knight Moves 6

HDL implementation of Advent of Code 2025 puzzles for Jane Street Advent of FPGA Challenge

Fun solutions to Jane Street Puzzles!

Solved monthly puzzles from Jane Street.

These are my solutions to Jane Street puzzles! Puzzle archives found here: https://www.janestreet.com/puzzles/archive/