Harnessing advanced research and machine learning for the future of trading.
A variety of deep learning models, including LSTM, LLM, Transformer, Mixture of Experts, and Random Forest models capture any patterns in our data.
We use data from the Bloomberg Terminal, Compustat, Wharton Research Data Services, CRSP, Factiva, and many more
Our team analyzes market conditions and performs research to explore hypotheses with our models.
W&L's first quant fund
For R&D and future trading
Unique situation-specific models
Testable trading patterns
First-year students from various places and majors
Our models, strategies, and unique advantages.
We employ cutting-edge models to identify market opportunities. We then capitalize off these oppurtunities by using a short term swing trading approach.
Our models are rigorously tested for accuracy and dependability before deployment. This ensures that our investors capital is well protected and experiences higher risk-adjusted returns.
We gather insights from Bloomberg, FactSet, and alternative data. This data is then compiled and incorporated into our models.
Smaller stocks have less liquidity, more adaptability, and slower price discovery. By focusing on smaller stocks, we can take advantage of an underutilized section of the market due to strict regulations on larger Hedge Funds.
Small firm with a personal focus on investors. Diversifies people's portfolios, as it acts as a completely different asset class.
We aim to be trading profitably for 2 years at this point. We will be diversified across multiple asset classes and invested in international markets. Strategy will be continuously adapted and changed over time to adjust for changes in the market and to yield higher returns.
