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Dynamic Portfolio Diversification
Dynamically quantify and monitor portfolio diversification with 3D model.
Breakthrough in risk management with lower maximum drawdown and volatility.
Next-generation Financial Engineering
Extend the traditional mean-variance framework using advanced financial engineering techniques 5.13%[1] higher annualized return than Private Client Indices (PCI)
[1] 2002-2017 backtesting results, SmartGlobal 80-20 portfolio
Machine Learning and Statistical Model
Construct statistical models to achieve a winning ratio[2] over 62.7%
State-of-the-art machine learning techniques and robust optimization to avoid overfitting

[2] The probability that assets selected under this model yield higher returns than their respective industry medians.