Production-grade statistical arbitrage terminal using Google's TimesFM 2.5 and Kalman Filters for dynamic hedge ratio adaptation. Features a high-contrast Bloomberg-style dashboard, vectorized backtesting, and real-time news sentiment analysis.

Zero-shot TSFM forecasts (Chronos-2, TimesFM) meet constrained Markowitz optimization for dynamic equity portfolios. ー S&P 500 forecasting & portfolio optimization.

Advanced Hybrid AI expert system for NASDAQ & Oil (WTI) ETF trading. Merges Quantitative ML, LLMs (Gemma 4), TimesFM 2.5, Visual Chart Analysis, and EIA Fundamentals for high-accuracy signals. Features dual-ticker strategy and Trading 212 execution.

A stock prediction application that uses Google's TimesFM (Time Series Foundation Model) to forecast stock prices from Yahoo Finance, with FastAPI serving as the backend API.

Time series forecasting models review and comparison using real estate data. The result are presented in the medium article. Link below

Forecasting monthly sales using Google's TimesFM model.

In this project, I explore the use of Large Language Models (LLMs) for time series forecasting, focusing on the task of stock market prediction.

Benchmarking zero-shot and fine-tuned time series foundation models for process model forecasting on directly-follows time series from event logs.

Benchmarking SOTA Time Series Foundation Models (Chronos-2, TimesFM 2.5, FlowState) on US Equities

Next year forecasts of Eurostat Economic and Tourism indicators per NUTS 2.

USD/KZT exchange rate forecasting using Google TimesFM foundation model