Trading: Improve execution of current market-making strategies. Research: Queue Priority and Theo research for market-making strategies. Developer: Meta-programming to apply C++ strategies for different exchanges.

There are several projects I did: Multiperiod Corporate Default Prediction • Provide a consistent term structure of cumulative default probabilities by a carefully designed neural network. • Tailor neural networks by economic domain knowledge to prevent our model from overfitting. • Outperform the state-of-art statistical model on AR(10%) and RMSE (20%) for US public companies from 1990-2017. • Publication: Wei-Lun Luo, Yu-Ming Lu, Jheng-Hong Yang, Jin-Chung Duan, Chuan-Ju Wang. ”Multiperiod Corporate Default Prediction Through Neural Parametric Family Learning.” Proceedings of the 2022 SIAM International Conference on Data Mining (SDM). Importance Sampling in Reinforcement Learning • Implement Approximate Bayesian Computation(ABC) algorithm on Multi Armed Bandits (MAB) problems for faster computation. Team leader, Recommendation Algorithms for KKStream • Collaborate with team members and others from KKStream to con- struct a knowledge graph for items to improve performance.

• Developed a trading platform with functions of optimization algorithms. • Implemented reinforcement learning to solve backward stochastic differential equations. • Designed an introduction lecture of reinforcement learning for a research group in the company (about 15 persons). • Applied machine learning approaches to Forex forecasting.

• Developed trading strategies on cryptocurrency markets. • Crawled cryptocurrency markets data from different exchanges. • Developed a part of trading API.

Developed over 30 rule-based trading strategies on TX and Forex and evaluated each strategy by return over maximum drawdown.