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Matt Dancho – Backtesting Algorithmic Trading Strategies with Python

Description Matt Dancho – Backtesting Algorithmic Trading Strategies with Python Build and Backtest Algorithmic Trading Portfolios with Python …So You Can Grow Your Investments responsibly WITHOUT Risky Single-Stock Strategies Or...

Description

Matt Dancho – Backtesting Algorithmic Trading Strategies with Python

Matt Dancho - Backtesting Algorithmic Trading Strategies with Python

Build and Backtest Algorithmic Trading Portfolios with Python

…So You Can Grow Your Investments responsibly WITHOUT Risky Single-Stock Strategies Or Algorithmic Trading Experience

How Matt Grew His Portfolio to ,674,854 (using the skills covered in this course) 👇👇👇

You Can Grow Your Investment Portfolio When You Implement The Professional-Grade 3-Step Process We Give You In The Course

You will…

  • Set up an trading portfolio project and Quant Lab software and get started (even if you’re a beginner with no prior algorithmic trading experience)
  • Get 4 algorithmic portfolio trading strategies. Plan your way to success, minimize risk, and protect your money (using volatility targeting, portfolio construction optimization, and setting minimum return thresholds so your portfolio grows in a risk-managed way).
  • Professionally backtest your portfolio trading strategy so you can test how your strategy would have performed under different market conditions.
  • Make trading for growing your investment portfolio a reality without losing money, sleep, or your mind!

THE FASTEST WAY TO…

Build And Backtest A Profitable Investment Portfolio Responsibly WITHOUT Risky Single-Stock Strategies Or Algorithmic Trading Experience.

Step 1: Trading Project and Python Quant Lab Setup (0 Value)

  • Get the Quant Stack Python Software installed
  • Set up your algorithmic trading project
  • Create your Python environment
  • Everything you need to begin building and backtesting portfolio trading strategies

Step 2: How to Create a Profitable Algorithmic Portfolio Trading Strategy (,500 Value)

  • Get our top portfolio-based trading strategy: Volatility targeting with auto-rebalancing ($2,500 Value)
  • Get our code template for how to construct a risk-managed portfolio with the Riskfolio-Lib Python library
  • Discover how to increase returns using the “Ray Dalio Bridgewater Cheat Code”

Step 3: Learn how to Backtest the right way (,500 Value)

  • Detailed walkthrough of event-based backtesting ($2,500 Value)
  • Backtested portfolio strategies with Zipline Reloaded
  • How to avoid mistakes in backtesting portfolios
  • How to include rebalancing, slippage, and trading commissions

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