Guide to Creating Your Own Automated Trading Bot
Did you know that a trading bot could make returns for you daily? Creating a bot can be quite profitable, and they can make you as much money as you allow them to. The trick is to configure them in a way to assess for risk management and for you to pay attention to the condition of the market.
Not all bots cost money to build, and there are multiple free cryptocurrency bots if that's your focus. Many traders, however, want to know what the process entails if they were to design and build their own. The process of creating automated trading bots is not always difficult and can be done in a cheap and effective way by a person with knowledge in a few important disciplines.
We are going to explore this list of disciplines in a guide that will put you on the path to creating your own trading bot and understanding how to build predictive algorithms. We're going to go in-depth into different forms of trading and how to execute a successful bot based on a variety of factors, so keep reading to learn how.
Not all bots cost money to build, and there are multiple free cryptocurrency bots if that's your focus. Many traders, however, want to know what the process entails if they were to design and build their own. The process of creating automated trading bots is not always difficult and can be done in a cheap and effective way by a person with knowledge in a few important disciplines.
We are going to explore this list of disciplines in a guide that will put you on the path to creating your own trading bot and understanding how to build predictive algorithms. We're going to go in-depth into different forms of trading and how to execute a successful bot based on a variety of factors, so keep reading to learn how.
How to Get Started With Creating Your Automated Trading Bot
Creating an algorithmic trading bot does not need to be expensive. You can start with a simple bot that trades based on pre-determined rules set by you. For example, you could create a bot that buys when the price of a cryptocurrency falls below $1,000 and sells when it rises above $10,000.
As your knowledge and expertise grow, you can add more sophisticated features to your bot. Notice here, though, that you are creating your bot to work within the constraints that you set. While an automated trading bot can bring in profit, it can bring in losses just as well.
This means that if you're getting started and trying this for the first time, it would be smart to set it up in a way that you can do some monitoring first. Testing it is one of the most important steps in creation. This will allow you to simulate how it would react throughout certain market conditions so that you can test the way it's built.
The main thing to do is to have access to an exchange. You'll need this access so that you can trade assets. Knowing your way around coding languages is important but having access to an exchange is vital as well.
With that, you'll need to start with knowing what you want to trade. Whether that's stocks or even cryptocurrencies, you can design your algorithm to respond to any form of trading.
As your knowledge and expertise grow, you can add more sophisticated features to your bot. Notice here, though, that you are creating your bot to work within the constraints that you set. While an automated trading bot can bring in profit, it can bring in losses just as well.
This means that if you're getting started and trying this for the first time, it would be smart to set it up in a way that you can do some monitoring first. Testing it is one of the most important steps in creation. This will allow you to simulate how it would react throughout certain market conditions so that you can test the way it's built.
The main thing to do is to have access to an exchange. You'll need this access so that you can trade assets. Knowing your way around coding languages is important but having access to an exchange is vital as well.
With that, you'll need to start with knowing what you want to trade. Whether that's stocks or even cryptocurrencies, you can design your algorithm to respond to any form of trading.
Get To Know Some Key Concepts
Understanding some key concepts for developing the base for a bot is a good place to start. Not everyone who builds one has to be a finance industry expert, so you'll need to have a good starting point so you know what to focus on. With that, one important concept to understand is algorithmic trading.
Algorithmic trading is a method of trading that uses computer-generated trading decisions instead of human decision-making. Algorithmic trading is often used by institutional investors, such as hedge funds and investment banks.
This form of trading is often associated with high-frequency trading (HFT), which is a type of algorithmic trading that trades very quickly, sometimes within milliseconds or even nanoseconds.
It's a mathematical model that's quite sophisticated. Its main point will be to trade based on more specific stock options and strategies with an end goal of generating higher profits.
Swing trading, on the other hand, is a strategy that can also be used when creating an algorithmic trading bot. Swing trading is a style of trading that attempts to capture gains in a stock or other asset from maybe one day to several weeks. Swing traders use technical analysis to look for stocks with shorter-term price momentum.
If you're starting to get how this type works, know that it's more speculative. With swing trading, you're going to try making a profit from swings in the market. Those swings are basically changes.
You'll want to align your market decisions with your chosen trade. This is what you want to get the bot to do for you. Both algorithmic trading and swing trading can be used when creating your bot and what it looks for.
The important thing is to understand how each works and what the benefits are to using them. Algorithmic trading can be faster and more efficient than human decision-making, but it can also be more tricky to grasp.
Algorithmic trading is a method of trading that uses computer-generated trading decisions instead of human decision-making. Algorithmic trading is often used by institutional investors, such as hedge funds and investment banks.
This form of trading is often associated with high-frequency trading (HFT), which is a type of algorithmic trading that trades very quickly, sometimes within milliseconds or even nanoseconds.
It's a mathematical model that's quite sophisticated. Its main point will be to trade based on more specific stock options and strategies with an end goal of generating higher profits.
Swing trading, on the other hand, is a strategy that can also be used when creating an algorithmic trading bot. Swing trading is a style of trading that attempts to capture gains in a stock or other asset from maybe one day to several weeks. Swing traders use technical analysis to look for stocks with shorter-term price momentum.
If you're starting to get how this type works, know that it's more speculative. With swing trading, you're going to try making a profit from swings in the market. Those swings are basically changes.
You'll want to align your market decisions with your chosen trade. This is what you want to get the bot to do for you. Both algorithmic trading and swing trading can be used when creating your bot and what it looks for.
The important thing is to understand how each works and what the benefits are to using them. Algorithmic trading can be faster and more efficient than human decision-making, but it can also be more tricky to grasp.
Keep In Mind Other Forms Of Trading
Keep in mind that there are other forms of trading that you can use while preparing your bot as well. A few examples could be position trading or even momentum trading.
Position trading is a longer-term strategy where you buy and hold a stock for weeks or even months. The goal is to benefit from long-term price trends. This form of trading can be passive, meaning you don't have to watch the markets as closely.
Momentum trading is a strategy that tries to take advantage of continued price momentum but in a particular direction. For example, if a stock keeps going up in price, a momentum trader might buy the stock and try to ride the momentum higher. A bot can be designed to do this as well.
Position trading is a longer-term strategy where you buy and hold a stock for weeks or even months. The goal is to benefit from long-term price trends. This form of trading can be passive, meaning you don't have to watch the markets as closely.
Momentum trading is a strategy that tries to take advantage of continued price momentum but in a particular direction. For example, if a stock keeps going up in price, a momentum trader might buy the stock and try to ride the momentum higher. A bot can be designed to do this as well.
There Are Two Main Types of Algorithmic Trading
The first is High-Frequency Trading (HFT), as we mentioned earlier. HFT is a type of algorithmic trading that focuses on executing trades at very high speeds. HFT algorithmic traders aim to make a small profit on each trade, but they rely on large volumes of trades to generate significant profits.
And then there's Low-Frequency Trading (LFT). This is a type of algorithmic trading that executes trades less frequently than HFT algorithmic functions. LFT algorithms aim to make a larger profit on each trade in comparison to the opposite.
Let's take a closer focus on LFT algorithmic trading since this form is more suitable for individuals who are not constantly monitoring the markets.
There are some specific types of algorithmic trading strategies you should be aware of:
Trend-Following Strategies
Trend-following strategies aim to profit from market trends just as it sounds given their name. These strategies buy assets when prices are rising and sell them when prices are falling.
Mean-Reversion Strategies
Mean-reversion strategies aim to profit from price discrepancies between an asset’s current price and its average price over a certain period. These strategies buy assets when prices are low and sell them when prices are high.
And then there's Low-Frequency Trading (LFT). This is a type of algorithmic trading that executes trades less frequently than HFT algorithmic functions. LFT algorithms aim to make a larger profit on each trade in comparison to the opposite.
Let's take a closer focus on LFT algorithmic trading since this form is more suitable for individuals who are not constantly monitoring the markets.
There are some specific types of algorithmic trading strategies you should be aware of:
Trend-Following Strategies
Trend-following strategies aim to profit from market trends just as it sounds given their name. These strategies buy assets when prices are rising and sell them when prices are falling.
Mean-Reversion Strategies
Mean-reversion strategies aim to profit from price discrepancies between an asset’s current price and its average price over a certain period. These strategies buy assets when prices are low and sell them when prices are high.
Choosing the Right Strategy
Many different algorithmic trading strategies fall into the two categories we just covered. Some of the more popular ones include:
Moving Average Convergence Divergence (MACD)MACD is a trend-following strategy that uses moving averages to identify market trends. This is one of the more popular options.
Relative Strength Index (RSI)
RSI is a momentum-based strategy that uses price oscillations to identify overbought and oversold conditions in the market. The main idea is to assess how fast bidding is taking place toward the security of up or down. If an RSI level is below 30, your bot should be operating on buying signals.
Bollinger Bands
Bollinger Bands is a volatility-based strategy. This type mainly uses price bands to identify periods of low and high volatility in the market.
Ichimoku Cloud
Ichimoku Cloud follows trends as well, and it uses support and resistance levels to identify market trends. You may or may not use this method, but if you do, or you're interested in giving it a shot, it does show you more reliable data points.
It's a predictive model based on Japanese candlestick charting. Yes, you can use this method for any stock approach.
Fibonacci Retracements
Fibonacci Retracements uses Fibonacci levels to identify market retracements. If you're wondering what this is, it's a type of trend-trading. All you're doing with this is paying close attention to a replacement that's in place within a certain trend.
Then you'll be making lower risk entryways into that trend based on the Fibonacci levels. This is a good strategy to use Python for.
Once you've selected a strategy, the next step is to set up your trading platform and inputs.
Moving Average Convergence Divergence (MACD)MACD is a trend-following strategy that uses moving averages to identify market trends. This is one of the more popular options.
Relative Strength Index (RSI)
RSI is a momentum-based strategy that uses price oscillations to identify overbought and oversold conditions in the market. The main idea is to assess how fast bidding is taking place toward the security of up or down. If an RSI level is below 30, your bot should be operating on buying signals.
Bollinger Bands
Bollinger Bands is a volatility-based strategy. This type mainly uses price bands to identify periods of low and high volatility in the market.
Ichimoku Cloud
Ichimoku Cloud follows trends as well, and it uses support and resistance levels to identify market trends. You may or may not use this method, but if you do, or you're interested in giving it a shot, it does show you more reliable data points.
It's a predictive model based on Japanese candlestick charting. Yes, you can use this method for any stock approach.
Fibonacci Retracements
Fibonacci Retracements uses Fibonacci levels to identify market retracements. If you're wondering what this is, it's a type of trend-trading. All you're doing with this is paying close attention to a replacement that's in place within a certain trend.
Then you'll be making lower risk entryways into that trend based on the Fibonacci levels. This is a good strategy to use Python for.
Once you've selected a strategy, the next step is to set up your trading platform and inputs.
Setting Up Your Trading Platform and Inputs
To start algorithmic trading, you'll need to set up a trading platform and inputs. A trading platform is a software application that enables you to place trades on financial markets. Some popular trading platforms include MetaTrader 4 (MT4), TradeStation, NinjaTrader, and Zorro S, which is a free analysis tool used for algo trading.
Inputs are the variables that your algorithmic trading strategy will use to make decisions. For example, a moving average crossover strategy will use two moving averages (fast and slow) as inputs.
The most important input for an algorithmic trading strategy is the entry price. The entry price is the price at which your bot will enter a trade. Other important inputs include the exit price, stop-loss price, and take-profit price.
The exit price that your bot will exit a trade. The stop-loss price is the price your bot will place a stop-loss order, and a stop-loss order is an order that closes a trade at a loss if the market moves against you. It's all pretty straightforward.
The take-profit price is the price at which your bot will place a take-profit order. And that type of order is an order that closes a trade at a profit if the market moves in your favor. The last step before putting your algorithmic trading bot into live trading is to backtest and optimize it.
Back-testing and Optimization
Back-testing is the process of testing a trading strategy based on historical data. Back-testing enables you to test your strategy on past data to see how it would have performed.
Optimization is the process of finding the best inputs for your trading strategy. Optimization will allow you to find the best values for your entry price, exit price, stop-loss price, and take-profit price.
When back-testing and optimizing your bot, it's important to use out-of-sample data. This type of data is data that your bot has not seen before. Back-testing on out-of-sample data will give you a more accurate picture of how your bot will perform in live trading.
Putting It Into Live Trading
Once you've back-tested and optimized your bot, it's time to put it into live trading. When putting your bot into live trading, there are a few things you need to do:
Choose a Broker
You'll need to choose a broker that offers an algorithmic platform. Some popular brokers that offer them could include Interactive Brokers, TradeStation, and NinjaTrader, as we mentioned before. You could even get started by using a platform like Alpaca and connecting its API if you decide that you know more about Python.
Choose a Data Feed
You'll need to choose a data feed that provides real-time market data. Some popular data feeds include Thomson Reuters, Bloomberg (B-PIPE), and eSignal.
Get Your Bot Set Up
You'll need to set up your algorithmic bot on your chosen platform. In general, this involves choosing the inputs for your strategy and connecting your broker account.
Start Trading
Once you've set up your bot, you can start live trading. Algorithmic trading bots can automate trades following your chosen strategy.
Inputs are the variables that your algorithmic trading strategy will use to make decisions. For example, a moving average crossover strategy will use two moving averages (fast and slow) as inputs.
The most important input for an algorithmic trading strategy is the entry price. The entry price is the price at which your bot will enter a trade. Other important inputs include the exit price, stop-loss price, and take-profit price.
The exit price that your bot will exit a trade. The stop-loss price is the price your bot will place a stop-loss order, and a stop-loss order is an order that closes a trade at a loss if the market moves against you. It's all pretty straightforward.
The take-profit price is the price at which your bot will place a take-profit order. And that type of order is an order that closes a trade at a profit if the market moves in your favor. The last step before putting your algorithmic trading bot into live trading is to backtest and optimize it.
Back-testing and Optimization
Back-testing is the process of testing a trading strategy based on historical data. Back-testing enables you to test your strategy on past data to see how it would have performed.
Optimization is the process of finding the best inputs for your trading strategy. Optimization will allow you to find the best values for your entry price, exit price, stop-loss price, and take-profit price.
When back-testing and optimizing your bot, it's important to use out-of-sample data. This type of data is data that your bot has not seen before. Back-testing on out-of-sample data will give you a more accurate picture of how your bot will perform in live trading.
Putting It Into Live Trading
Once you've back-tested and optimized your bot, it's time to put it into live trading. When putting your bot into live trading, there are a few things you need to do:
Choose a Broker
You'll need to choose a broker that offers an algorithmic platform. Some popular brokers that offer them could include Interactive Brokers, TradeStation, and NinjaTrader, as we mentioned before. You could even get started by using a platform like Alpaca and connecting its API if you decide that you know more about Python.
Choose a Data Feed
You'll need to choose a data feed that provides real-time market data. Some popular data feeds include Thomson Reuters, Bloomberg (B-PIPE), and eSignal.
Get Your Bot Set Up
You'll need to set up your algorithmic bot on your chosen platform. In general, this involves choosing the inputs for your strategy and connecting your broker account.
Start Trading
Once you've set up your bot, you can start live trading. Algorithmic trading bots can automate trades following your chosen strategy.
Get the Expertise You Need
Now that we know the specifics that can go into automated trading, you have a better baseline to start with. You can automate just about any form of trading, and while it may take some practice to get the hang of it, it's not far out of reach to do so.
Consult with KJ Trading Systems for the most detailed and usable trading strategies and advice to get you started within the market sooner rather than later. For workshops and trading tips, review our Strategy Factory Workshop today.
Consult with KJ Trading Systems for the most detailed and usable trading strategies and advice to get you started within the market sooner rather than later. For workshops and trading tips, review our Strategy Factory Workshop today.
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About The Author: Kevin Davey is an award winning private futures, forex and commodities trader. He has been trading for over 25 years.Three consecutive years, Kevin achieved over 100% annual returns in a real time, real money, year long trading contest, finishing in first or second place each of those years.
Kevin is the author of 5 highly acclaimed books, including "Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading" (Wiley 2014). Kevin provides a wealth of trading information at his website: https://www.kjtradingsystems.com
Copyright, Kevin Davey and KJ Trading Systems. All Rights Reserved. Reprint of above article is permitted, as long as the About The Author information is included.
Kevin is the author of 5 highly acclaimed books, including "Building Algorithmic Trading Systems: A Trader's Journey From Data Mining to Monte Carlo Simulation to Live Trading" (Wiley 2014). Kevin provides a wealth of trading information at his website: https://www.kjtradingsystems.com
Copyright, Kevin Davey and KJ Trading Systems. All Rights Reserved. Reprint of above article is permitted, as long as the About The Author information is included.