Lecture 1 Introduction to Research
Lecture 2 Introduction to Python
Lecture 3 Introduction to NumPy
Lecture 4 Introduction to pandas
Lecture 9 Linear Correlation Analysis
Lecture 10 Instability of Estimates
Lecture 13 Maximum Likelihood Estimation
Lecture 14 Regression Model Instability
Lecture 15 Multiple Linear Regression
Lecture 16 Violations of Regression Models
Lecture 17 Model Misspecification
Lecture 19 The Dangers of Overfitting
Lecture 21 Confidence Intervals
Lecture 22 p-Hacking and Multiple Comparisons Bias
Lecture 23 Spearman Rank Correlation
Lecture 25 Position Concentration Risk
Lecture 26 Estimating Covariance Matrices
Lecture 27 Introduction to Volume, Slippage, and Liquidity
Lecture 28 Market Impact Models
Lecture 30 The Capital Asset Pricing Model and Arbitrage Pricing Theory
Lecture 32 Fundamental Factor Models
Lecture 34 Factor Risk Exposure
Lecture 35 Risk-Constrained Portfolio Optimization
Lecture 36 Principal Component Analysis
Lecture 38 Example: Long-Short Equity Algorithm
Lecture 39 Factor Analysis with Alphalens
Lecture 40 Why You Should Hedge Beta and Sector Exposures (Part I)
Lecture 41 Why You Should Hedge Beta and Sector Exposures (Part II)
Lecture 43 Integration, Cointegration, and Stationarity
Lecture 44 Introduction to Pairs Trading
Lecture 45 Example: Basic Pairs Trading Algorithm
Lecture 46 Example: Pairs Trading Algorithm
Lecture 47 Autocorrelation and AR Models
Lecture 48 ARCH, GARCH, and GMM
Lecture 50 Example: Kalman Filter Pairs Trade
Lecture 51 Introduction to Futures
Lecture 52 Futures Trading Considerations
Lecture 53 Mean Reversion on Futures
Lecture 54 Example: Pairs Trading on Futures