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The innovation of our curriculum depends on consultation from academics and industry professionals.

1.1     Asset Classes and Instruments
1.2    Orders and the Limit Order Book
1.3    What is a Quant? Day in the life 
1.4    The Quantitative Approach
1.5    The Big Picture  

2.1     Python and QuantConnect
2.2    Performant Programming and Clean Code 
2.3    Order Execution 
2.4    Models: Zero Intelligence vs Agent Based
2.5    Automation and the Meta-Strategy Paradigm  

3.1     What is a Time Series
3.2    Rolling Operations
3.3    Standard Metrics of Forecasting
3.4    Stationarity and Differencing
3.5    Forecasting Models (GARCH and ARIMA)  
3.5    CAPM and Log Prices

4.1     Issues with Data Mining and Pattern Matching
4.2    Target Series, Supporting Series and Redundant Features
4.3    Feature Analysis
4.4    Feature Selection and Feature Compression
4.5    Discrete Optimization

5.1     Univariate Data
5.2    Multivariate Data
5.3    Parametric Regression
5.4    Nonparametric Regression
5.5    Residual Analysis
5.5    Certainty and Overfitting

6.1     Defining an Investment Universe
6.2    Covariance Matrices
6.3    Defining Risk
6.4    Portfolios as Graphs and Hierarchies
6.5    Mean-Variance Analysis

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