PT101 Practical Python for Finance & Trading Masterclass

Name: PT101 Practical Python for Finance & Trading Masterclass
Brand: BUDGET FOREX
Price: 22.0 USD
Availability: InStock

Original website: https://course.algotrading101.com/p/courses?fpr=ddinvest&fp_sid=ddims

Course syllabus: https://algotrading101.com/learn/course-syllabus/

Content: full PT101 Practical Python for Finance & Trading Masterclass

Please note: The vendor’s AlgoTrading101 bundle consists of 2 main courses:

AT101 focuses on the fundamentals of trading strategy design, testing and execution. PT101 focuses on modern and more advanced strategies.

This is the PT101 Practical Quantitative Trading with Python Masterclass.

I also have the AT101 Algorithmic Trading Immersive Course here: https://budgetforex.com/shop/at101/

PT101: Practical Quantitative Trading with Python Masterclass

PT101 focuses on modern advanced strategies such as:

Practical Strategies for Modern Markets

Basic Python and Test Strategies

Just enough Python to get you started (we will learn more advanced Python techniques in the later part of the course)
Designing a simple pair trading test strategy to whet your appetite and give you an rough sense of what to expect

Cointegration (Mean reversion: When A and B moves apart, we bet they will revert) (WE ARE HERE NOW)

(Concept) Synthetic assets (ranging assets that are made by combining different assets)
(Strategy) Bond futures calendar spreads and structures (creating ranging assets using bond futures)
(Strategy) Market making using a proxy asset (entering and exit trades at the bid and ask prices)
(Strategy) Statistical Arbitrage. Trading hundreds of stocks in a mean reversion manner.

Sentiment Analysis and Web API (Collect data from websites via special “links”)

(Concept) Use Web API to collect data (eg. Google trends to analyse search traffic)
(Strategy) Scour tons of stocks to see which stocks have sudden increase in search traffic volume

Alternative Data (Non-price data like Credit card, Location data etc)

(Strategy) Use paid alternative data from vendors to analyse stocks
(Strategy) Create your own special index by combining different alternative data (eg. combine retail receipts + foot traffic + search traffic to create a special index to predict retail stock prices. Live eg: MongoDB tracker, Crypto Tracker)
(Strategy) Creatively find data on websites and scrape them to predict market moves

Correlation (If A moves, trade B)

(Concept) Understand the statistical methods to test correlations
(Strategy) Use Google search data, job listings and other scrapped data to predict stock and spread movements
(Strategy) Use synthetic assets to predict other synthetic assets

Sentiment and Text analysis (Machine Learning)

(Concept) Evaluate the sentiment of a particular phrase, sentence, paragraph or article
(Strategy) Analyse tons of news articles in different language to find out the market sentiment towards an asset