Automated or algorithmic trading involves executing buy or sell orders based on pre-programmed instructions fed to a computer. Its appeal is that it leverages computers’ greater speed and analytical prowess relative to humans to produce better results. The global automated trading market is
Algorithmic traders need intermediate to advanced programming skills to build trading robots. They’re traders before programmers, so they also need in-depth knowledge of the financial markets.
Many algorithmic traders build trading robots and deploy them with their capital to hopefully make profits. That’s not the only way they can monetize their skills. People pay top dollar for trading robots built by third-party developers, often because they lack the coding skills to develop theirs.
An intriguing way algorithmic traders can make money is by joining crowdsourced automated trading communities where they can get paid for building algorithms.
Crowdsourced Trading
This type of trading leverages combined intelligence and expertise from across the globe. It doesn't matter where the algorithmic traders are. They just need the required skills plus a functioning PC and web browser to participate in crowdsourced trading endeavors.
Crowdsourced trading is a relatively new endeavor in the finance sector, but the idea of online crowdsourcing goes back decades. Here are some older examples:
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iStockPhoto - A website that allows members to upload stock imagery and receive royalties from their work.
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Wikipedia - The well-known free-access online encyclopedia with millions of contributors worldwide.
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Waze - A GPS app that allows users to submit road info, such as traffic and accident reports, to benefit other users.
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OpenStreetMap - An editable geographic database of the world with over 8 million contributors.
The rise of crowdsourcing has concurred with the declining barriers to information access. Smartphones, email, improved internet connections, and many other tools have made it feasible to crowdsource information on a scale like never before. It’s no surprise that crowdsourcing has shown its usefulness in the finance sector where information is critical.
Pros & Cons of Crowdsourced Trading
Crowdsourced trading has its advantages and disadvantages like any other trading strategy. The main advantage of crowdsourced trading is that it equalizes the playing field for global traders. People not living within
Giant hedge funds with deep pockets get a competitive advantage in the financial markets by hiring the best talent and paying for the most sophisticated computing resources. The rise of crowdsourced trading has given such funds access to a larger pool of talent they can empower to produce better results.
The main disadvantage of crowdsourced trading for finance firms is sifting through the noise. Most algorithms on crowdsourced platforms aren’t ingenious. It takes a lot of time to identify the ones that will likely generate substantial profits. Besides, if a trader comes up with a superb trading strategy, they may not want to share it with others.
Earning Profit from Crowdsourced Trading
Many hedge funds are turning toward crowdsourcing to pick winning trading strategies. Hence, if you’re a skilled algorithmic trader, you can carve up a slice of the growing market. The two main ways to earn profits from crowdsourced trading are:
- Building and selling your algorithms;
- Deploying your algorithms with capital from crowdsourced capital.
Building and selling your algorithms
The skills needed to build trading algorithms aren’t easy to develop. An algorithmic trader must have a thorough understanding of the markets they’re operating in alongside sufficient programming knowledge to feed trading instructions to a computer. Investors lacking these skills pay significant sums to buy trading algorithms created by experts.
There are some platforms where you can sell your trading algorithms like MQL5.community. This platform includes a marketplace where users can purchase trading robots and deploy them with their capital. If you have the skills, you can create and list your trading robot on the marketplace and earn money whenever someone buys it.
The MQL5 platform also includes a freelance marketplace where you can find clients that want trading robots built to their specifications and bid for the job. If you’re capable, why not monetize your skills?
Another good thing about MQL5 is that it allows you to test your trading robot before listing it on the marketplace. It supports backtesting, which is testing your algorithms on historical data, and forward testing, which entails testing your algorithms on live market data.
Deploying Algorithms with Capital
Some traders have ample skills to build trading robots but lack the capital to deploy them on the market and earn profits. These traders would be pleased to know that hedge funds are becoming increasingly receptive to funding crowdsourced investments. For instance,
If you have what it takes to manage other people’s money, you can sign up on one of the popular crowd-sourced investment platforms (e.g., Quantopian and Quantiacs) and vie for capital. These platforms allocate substantial money (up to $1 million or more) to the best algorithms. If yours is selected, you’ll get a percentage of the profits.
Note that this process is super competitive. You’ll be vying with thousands of people with top-notch analytical, finance, and programming skills– the best of the best.
Is Crowdsourced Trading Right for You?
Whether crowdsourced trading would be a fulfilling endeavor depends on many factors, such as your goals, geographical location, and how much time you can devote to trading. If you’re a full-time trader living within a major financial hub, it might be smarter to avoid the crowdsourced trading route and raise capital from local investors.
On the other hand, if you’re living far away from major financial hubs, it’ll be wiser to seek capital from crowdsourced platforms where it’s easier to find willing investors.
Before joining any crowdsourced trading platform, familiarize yourself with its rules, compensation structure, and target audience.