AINumeric: Intelligent Investment Consulting

ainumeric quant trading

AINumeric is a Shanghai/Toronto based independent and privately owned consulting technology company founded in 2020. We specialize in asset allocation solution, machine learning and data science solutions for investment research and analytics, portfolio construction and financial planning. Our goal is to empower the investors and investment managers with advanced quantitative tools for better investment decision and business decision. Besides consulting services we also provide customized machine learning and data science training. You can contact us directly with inquiries regarding our custom solutions or training sessions.

Solutions

We architect and deliver solutions ranging from advanced portfolio construction tools to novel systematic trading approaches. We have experience with machine learning applications in hedge fund trading strategies and asset allocation in hundred-billion asset management firms.

Consulting

We perform research using our toolkits and partner with domain experts in machine learning, data science and investment to provide targeted research, proofs of concepts and advisory around trading strategy, portfolio construciton, risk analytics, scenario analyses and asset management. We bring miltifaced and creative approaches to exploring research topics ranging from cutting edge machine learning models to alpha factor construction.
Training

We provide training for quantitative investment firms, asset management companies and individual investors. The training courses include quantitative trading strategy, strategic and dynamic asset allocation strategy, machine learning applications in investment, and traditional and alternative data analysis.

Background

Machine learning and AI help spot nolinear patterns and test potential scenarios agaist massive data. AI is one of the most transformative technologies of our time and has the potential to help solve many of the world's most pressing challenges. In addition, machine learning allows computers to take a more free-form approach, aiming to indentify patterns in massive data without being given specific guidance about underlying relationships. This is significant departure from traditional quantitative investment.