Laurent Bernut – QuantInsti – Systematic Short Selling Course

• Coding and backtesting a long-term short portfolio strategy
• Calculate the expected return on an asset
• To monitor stocks, create a screener
• Use it to compare stocks by explaining the relative series
• Different models like momentum, breakout swings, floor and ceiling can be defined.
• Different metrics can be used to evaluate portfolio performance, such as the gain-to-pain ratio and Girt ratio.
• Live trade and paper trade your strategies without any installation or downloads

Skills covered

Learning track
Automated Trading in Equity Markets
FOUNDATION

Python for Trading

BEGINNER

Models and Quantitative Trading Strategies
Day Trading Strategies For Beginners
Machine Learning in Trading

INTERMEDIATE

Short Selling In Trading
Automated trading with IBridgePy via Interactive Brokers Platform

ADVANCED

Quantitative Portfolio Management

Course Fees
$399

Special Bundle Pricing

Get an additional 40% discount when you enroll for all seven courses

Course Features

Get lifetime access to the course

Faculty Support for the Community

Live Trading Strategy Sample

Hands-Guided learning

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Prerequisites

You should have experience in financial markets and be able to understand terms such as buy, sell, enter, exit, etc. To be able code strategies in Python you will need to know how to store, visualise and manipulate data using Pandas or DataFrame. These skills can be learned in our course, Python for Trading.

syllabus

syllabus

Introduction

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

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