Laurent Bernut – QuantInsti – Systematic Short Selling Course

• Code and backtest long short portfolio strategy.
• Calculate the expected returns of an asset.
• Build a screener to monitor different stocks
• Explain the relative series and use it to compare different stocks
• Define different models such as momentum, breakout, swings and floor and ceiling.
• Evaluate portfolio performance using different metrics such as gain to pain ratio, Girt ratio etc.
• Paper trade and live trade your strategies without any installations or downloads

skills covered

learning track
Automated Trading in Equity Markets
FOUNDATION

Python For Trading!

BEGINNER

Quantitative Trading Strategies and Models
Day Trading Strategies for Beginners
Trading with Machine Learning: Regression

INTERMEDIATE

Short Selling in Trading
Automated Trading with IBridgePy using Interactive Brokers Platform

ADVANCED

Quantitative Portfolio Management

Course Fees
$399

Special Bundle Pricing

Enroll for all 7 courses and get additional 40% off

Course Features

Lifetime Access to the course

Faculty Support on Community

Sample Strategy for Live Trading

Hands-on guided learning

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Prerequisites

It is expected that you have some financial markets experience and understand terms like sell, buy, entry, exit positions etc. If you want to be able to code strategies in Python, then experience to store, visualise and manage data using Pandas and DataFrame is required. These skills are covered in our course ‘Python for Trading’.

syllabus

syllabus

Introduction

Short Selling
Relative Series
Stock Return Calculation
Regime Definition
Regime Change Detection
Floor and Ceiling
Regime Methods
Stock Classification
Strategy Creation
Live Trading on Blueshift
Live Trading Template
Stop Loss and Position Sizing
Python Installation
Course Summary

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