The Quant Trading Division
The Quantitative Finance industry is hard to break into. At SGC we give our members the best knowledge and expertise to help them achieve their goals. We leverage Quantitative Finance research to acquire a strong knowledge foundation. We specialize in data science techniques, time series analysis, machine learning, mathematical programming, stochastic programming and algorithmic trading.
Specializing in Optimization
Our members have advanced experience with portfolio optimization techniques. We use these techniques to determine the ideal weightings of our portfolio. We pay attention to recent developments in portfolio optimization fields to capitalize on alpha that has not been arbitraged out.
Machine Learning
Machine learning is becoming essential for Quantitative Finance. It is at the heart of the work we do at SGC We try to find new ways of using machine learning that has not been used before in Quantitative Finance.
Time Series Analysis
Stock data is effectively time series data. We try to analyze time series data in creative and quantitative ways to do more than just technical analysis. Our time series analysis approaches have been guided by creative research that involves machine learning approaches and math/probability.
Creative Data Science
It is well known that having the best features creates the best performance. We strive to think outside the box on new creative ways to capture alpha. We utilize Traditional Side research, machine learning, stochastic calculus and the latest research to find new data sources for our quantitative algorithms.
Topics of some of our favourite research papers:
Risk measures of asset price bubbles
Portfolio Optimization with Investors Views and Regime Switching
Deep Reinforcement Learning for Algo Trading
Volatility Driven Algo-Alpha Trading Strategies
Past/Current Projects
NOTE: Non-Exhaustive