The Bollinger Bands technical indicator is a technical indicator that is widely used to calculate the movements of financial assets. Adding it to your trading bot can be a powerful way to analyze crypto, forex, and stock data patterns and use the insights you gain to level up your trading strategies.

In this episode, I’ll show you how to add the Bollinger Bands technical indicator to your trading bot and customize it for your trading bot strategies.

Legal Stuff

• DYOR. Note that all trading is at your own risk. My goal is to provide you with the self-developed methods, systems, and tools I use — it is up to you to figure out if this solution works for you AND if I’ve provided credible content. Always DYOR (Do Your Own Research).
• Not Financial Advice. At no point should you consider anything in these articles to be financial advice. Any opinions expressed are about the technical aspects of the topic, not financial suitability.
• Referrals. I receive no commissions for any of the products I mention in this blog. They’re all free (or have a free tier), and I simply provide links to simplify your learning experience.
• AI Use. No AI was harmed in the creation of this blog. Some of the images are partially generated or enhanced through AI tools, we always use a real human to put them together. I do not use AI to generate the text, just spell check.

How to Set up Your Trading Bot for Indicators

Algorithmic trading relies on analysis to inform decision-making. Almost always, this means adding some kind of indicator.

The thing about indicators and trading bots is that they tend to breed. The more you analyze data, the more likely it is that you’ll have more and more indicators you want to add to your trading bot.

A common way to manage this complexity is by building your own indicator library

In this library, you can add any indicator you choose.

• Bollinger Bands✅
• Other indicators from TradeOxy ✅
• Indicators from other content creators✅

It’s a powerful way to simplify much of your future autotrading development 🚀🚀🚀

Add an indicators.py file

If you haven’t done this in a previous episode, add the indicators.py file to your trading bot. This file will handle anything to do with indicators in the rest of your TradeOxy Trading Bot development.

Get the Python Pandas Library

The Python Pandas Library is considered a gold standard in data analysis. It’s transcended the into the ranks of mythical status in Python and is widely used in an incredible set of industries.

Adding this exceptionally powerful analysis tool to your trading is as simple as 4 steps:

1. Navigate to requirements.txt
2. Add the word pandas to the bottom
3. Save
4. Run pip install -r requirements.txt

Here’s what your should look like if you used my dev environment episode to get started:

Dynamic Indicator Selection

To prepare for a multi-indicator future for your trading bot, we’re going to add some routing to your indicators.py file. This routing allows you to simply specify the indicator you want to use at any stage of your algorithm by using normal human language.

Add this code to your indicators.py (note that we’ll be adding in the Bollinger Bands technical indicator in the next section):

Here you can see:

1. We create a parent routing function
2. We use the **kwargs special Python argument to allow us to add the components specific to each indicator
3. We add in some helpful error handling

To see how this might work when you have multiple indicators, check out the indicators.py file in the main trading bot repo.

How to Add the Bollinger Bands Indicator to Your Trading Bot

Now that we can route to the Bollinger Bands indicator, we can go ahead and add the code to calculate it.

Default Values

I used the following default values for the Bollinger Bands indicator:

1. Bollinger Period: 20
2. Bollinger Standard Deviation: 2

You could easily expand the standard deviation to provide a differential between the upper and lower standard deviations, but I’ve left that aside for a more advanced approach in a future episode.

P.S. A great reference article to read more about Bollinger Bands is from Investopedia here.

Python Code + TA Lib for the Bollinger Bands Indicator

TA Lib is considered by many traders to be the go-to library for calculating technical indicators. It’s also a part of the dev environment.

The code below adds the Bollinger Bands indicator to your library using Python and TA Lib:

You’re all set!

Check out the Bollinger Bands in Action on Your Trading Bot!

1. Navigate to your app.py
2. Update the code in your file to look like this:

   	# Part of the Medium blog article, "Step-by-Step Guide to Add Bollinger Bands ©️ to Your Trading Bot" by AppnologyJames
   	# URL to access article: https://appnologyjames.medium.com/step-by-step-guide-to-add-bollinger-bands-%EF%B8%8F-to-your-trading-bot-c3b858926e12
   	# Main GitHub Trading Bot Repo: https://github.com/jimtin/tradeoxy-trading-bot
   	import alpaca_interactions as alpaca
   	import datetime
   	import indicators
   	# List of symbols
   	symbols = ["AAPL"]
   	max_number_of_candles = 1000
   	timeframe = "1hour"
   	indicator = "bollinger"
   	# Function to run the trading bot
   	def auto_run_trading_bot():
   	"""
   	Function to run the trading bot
   	"""
   	# Print Welcome to your very own trading bot
   	print("Welcome to your very own trading bot")
   	# Set the end date to yesterday
   	end_date = datetime.datetime.now() - datetime.timedelta(days=1) # Note that if you have a premium subscription you can remove this restriction
   	# Set the start date to one year ago
   	start_date = end_date - datetime.timedelta(days=365)
   	#### Calculate the an indicator ####
   	for symbol in symbols:
   	# Save the symbol text
   	symbol_text = symbol
   	# Convert symbol to a list
   	symbol = [symbol]
   	# Get the historical data for the symbol
   	symbol_historical_data = alpaca.get_historic_bars(
   	symbols=symbol,
   	timeframe=timeframe,
   	start_date=start_date,
   	end_date=end_date,
   	limit=max_number_of_candles
   	)
   	# Calculate the specified indicator
   	print(f"Calculating the {indicator} for {symbol_text}")
   	indicator_result = indicators.calc_indicator(
   	indicator_name=indicator,
   	historical_data=symbol_historical_data,
   	bollinger_period=20,
   	bollinger_std=2
   	)
   	# Branch based on indicator_result
   	if indicator_result["outcome"] == "calculated":
   	# Print succcess
   	print(f"The {indicator} was successfully calculated for {symbol_text}")
   	# Extract the values
   	values_dataframe = indicator_result["values"]
   	print(values_dataframe)
   	else:
   	# Print and error
   	print(f"An error occurred when calculating the {indicator} for {symbol_text}")
   	# Print the full message
   	print(indicator_result)
   	# Main function for program
   	if __name__ == "__main__":
   	auto_run_trading_bot()

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