Financial Engineering and Artificial Intelligence in Python

Welcome 5 Topics

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Introduction and Outline

Where to get the code

Scope of the course

How to Pratice

Warmup (Optional)

Financial Basics 31 Topics

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Financial Basics Section Introduction

Getting Financial Data

Getting Financial Data (Code)

Understanding Financial Data

Understanding Financial Data (Code)

Dealing with Missing Data

Dealing with Missing Data (Code)

Returns

Adjusted Close, Stock Splits, and Dividends

Adjusted Close (Code)

Back to Returns (Code)

QQ-Plots

QQ-Plots (Code)

The t-Distribution

The t-Distribution (Code)

Skewness and Kurtosis

Confidence Intervals

Confidence Intervals (Code)

Statistical Testing

Statistical Testing (Code)

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Time Series Analysis 31 Topics

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Time Series Analysis Section Introduction

Efficient Market Hypothesis

Random Walk Hypothesis

The Naive Forecast

Simple Moving Average (Theory)

Simple Moving Average (Code)

Exponentially-Weighted Moving Average (Theory)

Exponentially-Weighted Moving Average (Code)

Simple Exponential Smoothing for Forecasting (Theory)

Simple Exponential Smoothing for Forecasting (Code)

Holt’s Linear Trend Model (Theory)

Holt’s Linear Trend Model (Code)

Holt-Winters (Theory)

Holt-Winters (Code)

Autoregressive Models – AR(p)

Moving Average Models – MA(q)

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Portfolio Optimization and CAPM 22 Topics

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Portfolio Optimization Section Introduction

The S&P500

What is Risk?

Why Diversify?

Describing a Portfolio (pt 1)

Describing a Portfolio (pt 2)

Visualizing Random Portfolios and Monte Carlo Simulation (pt 1)

Visualizing Random Portfolios and Monte Carlo Simulation (pt 2)

Maximum and Minimum Portfolio Return

Maximum and Minimum Portfolio Return in Code

Mean-Variance Optimization

The Efficient Frontier

Mean-Variance Optimization And The Efficient Frontier in Code

Global Minimum Variance (GMV) Portfolio

Global Minimum Variance (GMV) Portfolio in Code

Sharpe Ratio

Maximum Sharpe Ratio in Code

Portfolio with a Risk-Free Asset and Tangency Portfolio

Risk-Free Asset and Tangency Portfolio in Code

Capital Asset Pricing Model (CAPM)

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Algorithmic Trading 9 Topics

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Algorithmic Trading Section Introduction

Trend-Following Strategy

Trend-Following Strategy in Code (pt 1)

Trend-Following Strategy in Code (pt 2)

Machine Learning-Based Trading Strategy

Machine Learning-Based Trading Strategy in Code

Classification-Based Trading Strategy in Code

Using a Random Forest Classifier for Machine Learning-Based Trading

Algorithmic Trading Section Summary

The Basics of Reinforcement Learning 12 Topics

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Reinforcement Learning Section Introduction

Elements of a Reinforcement Learning Problem

States, Actions, Rewards, Policies

Markov Decision Processes (MDPs)

The Return

Value Functions and the Bellman Equation

What does it mean to “learn”?

Solving the Bellman Equation with Reinforcement Learning (pt 1)

Solving the Bellman Equation with Reinforcement Learning (pt 2)

Epsilon-Greedy

Q-Learning

How to Learn Reinforcement Learning

Reinforcement Learning for Algorithmic Trading 5 Topics

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Trend-Following Strategy with Reinforcement Learning API

Trend-Following Strategy Revisited (Code)

Q-Learning in an Algorithmic Trading Context

Representing States

Q-Learning for Algorithmic Trading in Code

Statistical Factor Models and Unsupervised Machine Learning 4 Topics

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Statistical Factor Models (Beginner)

Statistical Factor Models (Intermediate)

Statistical Factor Models (Advanced)

Statistical Factor Models (Code)

Regime Detection and Sequence Modeling with Hidden Markov Models 5 Topics

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Why Sequence Models? (pt 1)

Why Sequence Models? (pt 2)

HMM Parameters

HMM Tasks and the Viterbi Algorithm

HMM for Modeling Volatility Clustering in Code

Course Summary and Common Questions 2 Topics

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Trading APIs and Deploying Your Strategy in the Real World

High Frequency Trading (HFT)

Financial Engineering and Artificial Intelligence in Python

Course Content

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