4 reasons why YOU should automate your trading strategy

6. Juli 2022

Automating your strategy ⚙️

The current times are tough for investors looking to spare their portfolios from the havoc of the financial markets. The S&P500, by many considered to be the best overall measurement of American stock market performance, fell 3.88% on 12 June 2022. The index reached its lowest level since March 2021, bringing its losses from its January peak to more than 21%. Naturally, many private investors are asking themselves what they can do to stay profitable. Automating your trading strategy can offer a great solution by allowing you to:

  1. harness increased computing power
  2. test your strategy before deploying it
  3. minimise emotional trading and
  4. level up your diversification

In this article you will learn how these advantages play out in detail and how you can use them to leverage your portfolio.

1. Computers outperform humans 🤖

Many trading strategies are based on technical analysis — i.e. looking at numbers that translate into indicators and trading signals. For example, the Relative-Strength-Index (RSI) can indicate that a particular asset at a specific time is overbought, which might be a reason to exit your positions. Or take the Moving Average (MA), which identifies emerging and common trends in markets. Considering the vast amount of numerical data that goes into these indicators, it can be quite challenging for humans to react appropriately. This is where automation comes into play. Indicators and signals can be represented by formulas, which means that technical analysis just boils down to a bunch of math. Newsflash! Computers are quicker and more accurate than humans at solving such problems. They are able to look at a much bigger scope regarding the financial history and development of a stock chart, all while analysing the financial data faster and more reliably than humans. For a computer, it’s easy-peasy-lemon-squeezy 🍋. For a human, not so much.

2. Back/forward testing your strategy 🤓

A strategy might seem reasonable at first glance, but it’s important to test it in different market conditions to make sure it performs as intended. This will help you develop a better understanding of the viability of your idea and, in the long run, increase the chances of a successful trading strategy. How to execute? Traders can take a precise set of rules defined in their strategy and test them on historical market data (backtesting) or in a simulated environment with paper money (forward testing) before setting their algorithm live. The two can even be combined: backtesting to determine a strategy’s effectiveness and forward testing to further evaluate its accuracy. Such methods can even be incorporated into the design of your strategy — in case you’re displeased with its backtesting performance, you can go back and fine-tune your code. Testing your code manually though is a strenuous and time consuming task which will result in less valuable data for you to iterate on. Automating this process allows you to test different scenarios simultaneously and on a grander scale with higher quality results. Keep in mind, no matter how much you test, the behaviour of the real market can still differ.

3. Minimise emotional response 😱

In some situations, emotions can heavily influence your trading decisions. How many times have you removed a stop-loss because you just knew that the stock would bounce back up? Or how many times have you hesitated to follow your initially defined strategy because you got nervous?

Trading based on emotions can be very dangerous as they lead to irrational decisions that could potentially cause big losses to your portfolio. The stock market in its nature is a risky affair. While there are many strategies to counter these risks, you tend to adopt a myopic approach if you trade under emotions. This generally exposes you to unnecessary risk. Another danger is that you diverge from your predefined goals, as you depart from the larger picture and get sucked in by the heart-racing excitement of the live market. A common emotional response is also indulging in revenge trading. This is the habit of making random irrational trades in an effort to overcome a loss as quickly as possible.

Automating your trading plan can help you to control your emotions. To keep emotions under check, Forbes advises to “formulate your trading strategy based on your needs and market knowledge”. Setting clear benchmarks and exits is important. Trading success thus relies heavily on having the discipline to stick to your trading plan, irrespective of its outcome. An automated strategy makes this easier as you can build your strategy with a clear and concise mind, not disturbed by the turbulences of the live market. The algorithm will then perform the set of rules you applied to it consequently and won’t change its mind about it. It‘s always possible to revalidate your strategy. But that revalidation happens decoupled from the live events of the market by just focusing on the strategy itself. By preserving discipline in even volatile markets, automated strategies allow to achieve consistency.

4. Diversify your portfolio ⚖️

Diversification is key in mitigating risks at the stock market. Let’s say you only invest in airline stocks. As soon as bad news hits the industry (let’s say something as unimaginable as a pandemic) your whole portfolio would slump. In order to prevent such big hits on your portfolio you want to diversify your investment capital into stocks, ETF’s, gold, crypto, bonds, warrants etc. But that’s not all. These vehicles can be further diversified by purchasing shares in different companies, asset classes, investing into multiple tokens or buying different kinds of commodities. Thus allowing you to spread the risk over various different financial instruments while also creating a hedge against unsystematic risks like business or financial risks. It’s important to realize, as noted in this paper by Harvard University, that while diversification can reduce unsystematic risk directly related to a financial instrument, it doesn’t mitigate common market risk caused by e.g. inflation rates, exchange rates, political instability, war, and interest rates.

But what does that have to do with an automated trading strategy? I know what you’re thinking: yes, it’s possible to diversify your portfolio manually. But computers are able to conduct diversification on a whole different scale. Automated trading systems permit the user to trade multiple accounts or various strategies at one time. This would be incredibly challenging for a human to accomplish. An algorithm can scan for trading opportunities across a range of markets and efficiently execute different strategies designed for different market scenarios in milliseconds.

Better safe than sorry 😇

Even though there are many advantages to automating your trading strategy, in some scenarios it can make sense to supplement with manual analysis. For example, performing fundamental analysis by looking into a company’s history or examining its balance sheet. It’s important to note though that with the amount of data being made available online and the possibilities of digital tools accelerating, fundamental analysis becomes increasingly automated, too. For example, you could create an automated sentiment analysis tool to catch the general public’s opinion of a financial instrument. As often in life, a healthy balance does the trick. When it comes to investing, this could mean a hybrid concept of doing manual fundamental analysis and then handing over the work to your algorithms.

Start coding🧑‍💻👩‍💻

Now that you know how automating your trading strategy can be beneficial, you want to know how to act on it. Understandable. 🤝

This is were lemon.markets comes into play. Who are we and how can we help you? We are a Berlin-based Fintech powering the infrastructure for developers to create their own brokerage experience at the stock market. With the help of our Trading API and Market Data API we give you direct access to the financial world and its instruments.

For example, try building a trading strategy based on the mean-reversion effect, which operates under the assumption that a stock will eventually converge towards an average value. This allows you to make predictions on the future course of the stock. Or you could base your trades on insider information obtained by scraping SEC forms. Go ahead and get creative. If you want some additional inspiration we have collected some beginner-friendly trading strategies you could automate.

I hope you enjoyed this article. If you want to learn more about investing, make sure to follow our blog. And don’t forget to sign up to lemon.markets to start building your own algorithmic trading project. If you have any questions, make sure to contact us via support@lemon.markets or join our Slack community 🚀

We are looking forward to your projects with lemon.markets :)

🍋 David

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