Build a trend-following trading bot in Python
Take one strategy from backtest to paper-trading bot. Collect market data, simulate positions, evaluate the results, and build the data and order-management code. Follow along with the complete source code.
$99 once. Some Python familiarity recommended. Start anytime.
ILLUSTRATIVE BOT WORKFLOW
trading_bot.py
symbol = "SPY"
price = get_latest_price(symbol)
signal = strategy(price)
if risk_check(signal):
broker.submit_order(signal)
- 08:55:00bot startedok
- 08:55:02SPY price loaded$645.22
- 08:55:03signal calculatedBUY
- 08:55:04paper order sentaccepted
From strategy to a working bot
“As a beginner in algorithmic trading, I was surprised how quickly it was possible to automatically backtest a trading strategy and to create a trading bot in Python, which implements this strategy. The bot already works and executes orders (on a demo account).”
Daniel
Python for Traders student
Put your Python to work
You know some Python. Now put it together in a trading project: collect prices, test a strategy, and build the code that manages data and orders.
Follow one focused project from strategy discussion to a working bot. Watch the lessons at your own pace and compare your work with the complete source code.
From backtest to bot
16 lessons, including 11 videos totaling about 80 minutes. Take as much time as you need to run the code and understand each part.
- Step 1
Choose the strategy
Start with the course overview and a discussion of the trend-following strategy.
A clear trading rule to implement.
- Step 2
Build the backtest
Collect market data, simulate positions, and evaluate the strategy's results.
A backtest you can inspect and change.
- Step 3
Read the results
Review the key metrics, equity curve, and monthly returns from the backtest.
A picture of how the example strategy behaved.
- Step 4
Build the bot
Work through the core utilities, bot class, data manager, and order manager.
The components that turn a strategy into a running bot.
- Step 5
Test and scale up
Test the components, follow the scaling lesson, and complete the final steps.
A trend-following bot you can run in a paper account.
- Step 6
Keep the complete code
Download the full project and use it alongside the lessons as you build.
The source code to study, modify, and reuse.
The tools you’ll use
Use Python and pandas to work with prices, yfinance to collect market data, and Alpaca to place orders in a paper account.
What you get
The challenge is for you if
- You know some Python and want a focused trading project
- You learn best by running code and changing it yourself
- You want to try the teaching approach before taking the full Masterclass
It is not for you if
- You want a profitable strategy or trade signals handed to you.
- You already build and deploy automated trading systems comfortably.
- You do not want to run or change any Python code yourself.
Frequently asked questions
- When does the challenge start?
- Whenever you are ready. Work through the lessons on your own schedule.
- Do I need to know Python?
- Some familiarity with Python is recommended. If you are starting from scratch, begin with the Masterclass's Python Foundations section.
- Is this a coached program?
- This is a self-guided course with lessons and complete source code. Coaching, live calls, and a managed community are not included.
- How long does it take?
- There are about 80 minutes of video across 11 lessons, plus written material and the code download. Allow additional time to run, understand, and modify the code.
- Is real money involved?
- The project uses an Alpaca paper-trading account so you can test the bot with simulated funds.
- Will the bot make money?
- The challenge teaches the process of building and testing a bot. The example strategy is for learning and does not promise trading profits.
- Is finished code included?
- Yes. The Code Download lesson contains the complete bot project.
Build a complete trading system in the masterclass
Learn how to research and backtest strategies, manage market data, connect broker APIs, and build a larger trading bot.