Automated markets are not new
Algorithmic trading isn’t new – it’s a concept that has existed since the early 1970s with the computerization of order flow and the 1980s with the introduction of program trading within the S&P 500 index and futures markets. Today, large financial institutions like banks and mutual funds use sophisticated algorithms to build and liquidate positions at breakneck speed. This setup allows them to take advantage of minor discrepancies in live market conditions and dwarf what can be done manually.
Automated strategies lead where manual execution is lacking – in the processing of bulk transactions. Automated trading processes enable users to accurately and quickly test more trades in a shorter time frame.
Algorithmic trading: a super effective but inaccessible innovation
In some contexts, algorithmic trading, also known as algo trading, black box trading, or automated trading, uses mathematical formulas and high-speed computer programs to execute trades.
These formulas are based on a number of predefined instructions such as price, volume, timing, or other mathematical models. In theory, algo trading can make profits at a rate even experienced traders cannot.
In addition, algo trading makes trading more systematic and eliminates human emotions from trading activities.
In general, algo trading simplifies and systematizes cumbersome trading processes through automation.
… but they are skewed in favor of institutional players
Although algo trading technology is used exclusively by mutual funds, banks, and institutional traders, it has seen exponential demand from retailers. In the foreign exchange market, for example, retailers account for an estimated 5.5 percent of the global market, which translates into an incredible daily trading volume of $ 250 billion. This is in line with data suggesting that the algo trading market will see a CAGR of 11.23 percent between 2021 and 2026.
However, the past few years have sparked heated discussions about how the speed and ubiquity of high frequency trading software (HFT) has given Wall Street suits the upper hand over retailers. This begs the question: What would it take to make algorithmic trading accessible and profitable at the retail level? Because according to the current status, high barriers to entry keep this technology within the walls of some financial giants.
Can Retailers Still Compete?
A retailer’s journey into the world of algo trading has not been the smoothest. To get started, a retailer would either have to learn to code, hire specialist tech talent, or pay for expensive legacy software to start algo trading. You also need to find separate platforms that support critical algorithm validation techniques such as backtesting and paper trading. These and other bottlenecks discourage the group of retail investors who may be interested in incorporating algo trading into their trading routine.
However, retail algo trading is not an impossible dream. There are many fin tech platforms that spring up with the sole aim of democratizing institutional technology for all traders. Breaking Equity, for example, reveals the exclusivity of algo trading by allowing retailers to create, test and paper-trade their own algo bots before trading live. Users can also view sample strategies and historical data.
According to his website, users can automate their portfolios in five easy steps with little to no programming experience.
There are several other apps that enable individual traders to make better trading decisions by providing easy access to institutional quality market data.
While retailers may not have the big pockets to control the evolution of the market, their lot size gives them the freedom to navigate the market effectively. Plus, they don’t have to deal with the same regulatory hurdles that more prominent players face. These benefits, combined with the accessibility of automated trading tools, can empower small investors and make economic markets much fairer.
In conclusion, trade automation is an effective way to experiment with strategies and automate everyday processes for faster results. There is no question that as retailing continues to grow, algorithmic trading will always find rapid adoption – especially now that platforms exist that really simplify complicated technologies for everyone.
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