
A seminar on applying statistical-arbitrage methods in derivative markets and developing systematic trading perspectives beyond directional market forecasts.
Nov 21, 2026

A Trade Talk episode on volatility-arbitrage methods within statistical-arbitrage strategies for derivative markets.
Sep 23, 2026

A short segment from The Trading Lab EP.14 on using AI agents in quantitative trading, within a broader discussion of statistical arbitrage, mathematical modeling, and the trading process.
Aug 22, 2026

A full-length discussion of statistical arbitrage and the quantitative trading process, including hedging ratios, asset selection, correlation and cointegration, value at risk, mean reversion, cash-and-carry arbitrage, position sizing, and applications of machine learning and AI.
Aug 19, 2026

A seminar on profit opportunities across COMEX and TFEX Gold Futures, covering the gold-market outlook, statistical-arbitrage strategies, practical implementation, and risk management.
Aug 2, 2026

A Trade Talk discussion on quantitative-trading strategies for Thailand Futures Exchange markets and the role of systematic methods in derivatives trading.
Jul 31, 2026

An advanced seminar on quantitative trading and statistical arbitrage, covering core concepts, systematic strategy construction, and practical implementation.
Mar 28, 2026

A seminar on statistical-arbitrage strategies that combine quantitative models and value investing, including pair trading, carry trade, practical futures implementation, and risk management.
Oct 11, 2025

A Trade Talk episode on using options strategies in TFEX markets and incorporating derivatives into systematic trading and risk-management decisions.
Jul 25, 2025

The Quantitative Trading Workshop is an educational event focused on algorithmic trading strategies, statistical methods, and financial data analysis. It covers topics such as market dynamics, risk management, machine learning in trading, and backtesting strategies. Participants gain hands-on experience with coding (Python/R) and quantitative models, making it ideal for finance professionals, researchers, and students interested in systematic trading.
Feb 15, 2025