Description
Course overview
Recommended for portfolio managers and quants who wish to construct their portfolio quantitatively, generate returns and manage risks effectively. In this course, you will learn different portfolio management techniques such as Factor Investing, Risk Parity and Kelly Portfolio, and Modern Portfolio Theory.
Live Trading
- Code and backtest multi-factor portfolio strategy.
- Calculate the expected returns of an asset.
- Allocate capital using Kelly criterion, modern portfolio theory, and risk parity.
- Explain the CAPM and the Fama-french framework.
- Define different factors such as momentum, value, size and quality.
- Evaluate portfolio performance using Sharpe ratio, maximum drawdown and monthly performance.
- Paper trade and analyze the strategies and apply in live markets without any installations or downloads
Skills Required To Learn Quantitative Portfolio Management
Portfolio Management
- Multi-Factor Strategy
- Kelly Criterion
- Risk Parity
- Fama-French Three-Factor Model
- Modern Portfolio Theory
Underlying Math
- Linear Regression, Maximum
- Drawdown
- Annualised Volatility
- Covariance, Beta
- Skewness, Kurtosis
- Treynor Ratio, Information Ratio
Computation Skills
- Pandas, NumPy, Math
- OLS
- CVXPY
- Data lImporting
- Data Visualisation
Learning Track 7
This course is a part of the Learning Track: Portfolio Management and Position Sizing using Quantitative Methods. Enroll to the entire track to enable 10% discount.
Prerequisites
It is expected that you have some trading experience and understand basic financial markets terminology like ‘going long and short’. 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
Introduction
Basics of Portfolio Construction
Modern Portfolio Theory
Kelly Criterion
Live Trading on Blueshift
Live Trading Template
Risk Parity
Beta
Capital Asset Pricing Model (CAPM)
Fama-French Three- Factor Model
Fama-French Five-Factor Model
Factor Investing
Multi Factor Model
Portfolio Performance Analysis
Run Codes Locally on Your Machine
Capstone Project
Summary
About Author
Quantlnsti is the world’s leading algorithmic and quantitative trading research & training institute with registered users in 190+ countries and territories. An initiative by founders of iRage, one of India’s top HFT firms, Quantlnsti has been helping its users grow in this domain throupgh its learning & financial applications based ecosystem
for 10+ years.
Why Quantra ?
- Gain more in less time
- Get taught by practitioners
- Learn at your own pace
- Get data & strategy models to practice on your own
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