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 $5,674,854 (using the skills covered in this course) 👇👇👇

Why beginners fail at growing their investments…

Don’t Know How to Get Started

Are you overwhelmed with the number of strategies out there for algorithmic trading?

Losing Money With Risky Single-Stock Strategies

Are you losing money on your first trades, do you feel uneasy with your single-stock risk, or are your trades underwater?

Lack of Financial Domain Experience

Do you find yourself struggling to gain confidence, understand financial jargon, and make sense of it all?

If that’s you…

Then keep reading, my friend, because what happens in the next few minutes could decide if you stay stuck for another year or gain the knowledge that will help you grow your investment portfolio responsibly.

Trust us, we know what it’s like…

Trying single-stock moving average crossover strategies (and “bleeding red”)
Spending money on courses that do NOT work
To feel like I could be growing my investments more (but not knowing how)
To feel like I’m taking on too much risk
To try every YouTube trading strategy there is, and still lose money

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!

These outcomes are totally within reach for you and your investment goals (even if you’re starting from scratch or have traded before).

This is Matt’s $5.6 million portfolio that he used to battle-test the algorithmic trading strategies used in this program.

Matt’s portfolio grew at 70% for the 2-years that the trading strategies in the course were tested. The results below are provided to demonstrate what can happen with a professional-grade portfolio and trading strategy. Your results may differ. Trading involves a high level of risk.

Build Confidence in Your Trading

“This gives me the confidence that I’m able to do better.” — Adam

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 ($500 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 ($2,500 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 ($2,500 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

LISTEN, WE REALIZE THAT:

1. You need professional market data for high-quality backtests

2. You need free market data for when you are first beginning to backtest non-professionally

3. You need more portfolio trading strategies for different market conditions

SO, WE’VE POURED 250 HOURS INTO OUR PROGRAM TO SOLVE THESE TOP PROBLEMS.

(Read On To Learn More…)

THIS COURSE IS EVERYTHING WE WISH WE KNEW BEFORE WE STARTED ALGORITHMIC TRADING

We will share the exact same trading strategies that helped us grow 6-figure and 7-figure investment portfolios.

Get on board and start on your journey to responsible investment growth!

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Matt Dancho – Backtesting Algorithmic Trading Strategies with Python

Build and Backtest Algorithmic Trading Portfolios with Python

How Matt Grew His Portfolio to $5,674,854 (using the skills covered in this course) 👇👇👇