Multi-Strategy Quant Systems in Python

1. 10: LBMOM Strategy; Vol Targeting and Voting Systems
2. 11,12: Calculating PnL, Strat Vol and Debugging (CHECKPOINT 2)
1. 13: Integrating with Oanda. Writing Wrapper Classes for the Oanda REST API
2. 14: Implementing the Wrapper Functions and Getting Oanda OHLCV (CHECKPOINT 3)
3. 15: Writing Oanda Config Files
4. 16: Implementing the Oanda Database Pipeline (CHECKPOINT 4)
1. 17: Adding FX Information to Data
2. 18: Writing a Master Config File
3. 19: Implementing an FX Calculator (CHECKPOINT 5)
1. 20: Integration, Refactoring and Debugging
2. 21: Implementing the LSMOM Strategy (CHECKPOINT 6)
3. 22 Implementing Diagnostic Tools
4. 23: Debugging (CHECKPOINT 7)
5. 24: Implementing the SKPRM Strategy (CHECKPOINT 8)
1. 25: Combining Alpha Signals for Portfolio Allocation
2. 26: Controlling Nominal Exposure in a Vol Target Framework (CHECKPOINT 9)
1. 27: Writing a Service Class API for Oanda
2. 28: Implementing the Service Class API and Writing an Order Config
3. 29: Getting Live Optimal Allocations and Integration with the Brokerage
4. 30: Implementing Internal Order Logic and Utilities (CHECKPOINT 10)
5. 31: Completing Order Logic and Considerations for Other Brokerages
1. 32: Setting Up With Darwinex - MQL and Python Scripts
2. 33: Obtaining Data Through a TCP Socket Connection with an Open MT4 Terminal
3. 34: Writing Client-Server Scripts In Python and MQL (CHECKPOINT 11)
4. 35: Scraping the Darwinex Website for Contracts
5. 36: Writing the Darwinex Wrapper API and Configs (CHECKPOINT 12)
6. 37: Implementing the Darwinex Service Client
7. 38: Implementing the Darwinex Trade Client
1. 39: Integrating Another Brokerage - Darwinex - with a Master Switch (CHECKPOINT 13)
2. 40: Getting the Darwinex Dataset
3. 41: Integrating the Darwinex Data Pipeline (CHECKPOINT 14)
4. 42: Integrating Darwinex Strategy Configs
1. 43: Market Order FOK - Oanda
2. 44: Data Cleaning and Rerunning Tests
3. 45: End-to-End Testing of Order Logic and Concluding Oanda (CHECKPOINT 15)
4. 46: Writing the Trader Order Logic in Darwinex Trade Client
5. 47: Min Heap Data Structure for Open Trades
6. 48: Implementing the Darwinex Trade Order Logic - Smallest In First Out
7. 49: Fixing Config Files, Resetting the Database and Testing Orders
8. 50: End to End Testing on Darwinex Trades and Conclusion (CHECKPOINT FINALE)

About this course

$253.00
49 lessons
9.5 hours of video content

Multi-Strategy Quant Systems in Python from Scratch - A First Course in Algorithmic Trading by HangukQuant

Course curriculum - 50 Lectures

Chapter 1: Introduction

Chapter 2: Designing Flexible and Robust Quantitative Systems

Chapter 3: Strategy Implementation; Getting Alpha Signals

Chapter 4: Brokerage Implementation; Oanda

Chapter 5: Working with FX and Non-USD Contracts

Chapter 6: Adding Multi Strategies

Chapter 7: Portfolio Allocations with Strategy Signals

Chapter 8: Integrating Order Logic with a Brokerage - Oanda

Chapter 9: Dual Brokerages - Integrating with Darwinex

Chapter 10: Multiple Brokerage and Brokerage Switching

Chapter 11: Trade Order Submission and Obtaining Optimal Allocations

About this course

Data Alpha Execute