Build a LIVE Algorithmic Trading Bot with Python, Lumibot and Alpaca: A Step-by-Step Guide

​ @MattMacarty
#algotrading #python #tradingbots #algorithmictrading #lumibot #alpaca #alpacamarkets
#livetrading #quantfinance
** Note you also need to set broker = "Alpaca" in the .env file **
How to Code a Trading Bot in Python
Building a LIVE Stock Trading Bot with Python, Lumibot and Alpaca: A Step by Step Guide
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**This video is for educational purposes only. It should not be construed as investment advice.**
In this video, you'll learn how to build a simple algorithmic trading bot using Python, Lumibot, and Alpaca. We'll start by setting up a paper trading account on Alpaca and then configure Lumibot to interact with it.
Key topics covered:
Setting up a Paper Trading Account: Learn how to create a free paper trading account on Alpaca to test your strategies without risking real money.
Configuring Lumibot: Understand the basics of Lumibot and how to set up your environment variables to connect to your Alpaca account.
Implementing a Simple Buy-and-Hold Strategy: We'll build a straightforward strategy that buys a specific asset and holds it for a certain period.
Backtesting Your Strategy: Evaluate your strategy's historical performance using Lumibot's backtesting capabilities.
Deploying Your Bot: Learn how to deploy your bot to a live trading environment and execute trades automatically.
Whether you're a beginner or an experienced trader, this video will provide you with a solid foundation for building your own algorithmic trading bots.

[@james9164]

Good to see you back Matt, only found your stuff a few months ago but have really found it helpful!

[@MattMacarty]

Glad it helped

[@laixdy9819]

I just started looking for info like this and this video pop out, amazing content! :D

[@MattMacarty]

Thanks. Glad it helped

[@pghimire]

Great video Matt! Do you have a video (or resource) for how you are analyzing / viewing the backtesting reports?

[@MattMacarty]

You mean something that talks about the metrics generated? No I don't have anything like that. I think there are a few metrics that are widely used to evaluate or compare strategies at a high level. Sharpe and Max Drawdown are probably the most common.

[@bryanruiz9673]

I am new to Python programming. Watching your vids motivates me. What advice would you give to a newbie?

[@MattMacarty]

Thanks. It's a bit of a journey, but I think I would at least do an online introductory Python course from a reputable source. If you want to go the book route I would suggest "Python Crash Course".

[@bryanruiz9673]

@@MattMacarty Thanks!

[@calebeldredge925]

Been following you for a while, really enjoy your content. Tell me, do you think it's possible for a retail trader to create algo's that beat the market consistently? I enjoy coding them up as a hobby, but am curious if it would be possible to uncover alpha if taken seriously.

[@james9164]

Yes, but. the but being that you will probably have to do it in murky/constrained/new markets where the big boys have trouble operating or getting access. Think the small cap shorting craze a few years ago and on-chain crypto, for example.

[@MattMacarty]

I mean it's not easy and it's likely if you find something that works, it will need constant monitoring and revision. I guess you only need need to "win" more than 50% of the time and minimize the size of your losses. The question always becomes is my effort worth it? In other words do I beat buy and hold?

[@BrennanVest]

I’m going to upload a video here soon but I started learning machine learning like rentech to have my algorithms adjust a bit better than manual analysis. However it’s extremely hard to beat buy&hold consistently. To Matt’s point you’ll need to constantly backtest and re adjust accordingly. Right now my algo is at 62% win rate so I’ll take it but it’s also conservative. What I’m doing now is more complex and I had to buy a second computer just to compute everything I needed.