Since the emergence of the internet, algorithmic trading has come to dominate the financial trading world, but what percentage of trading is actually algorithmic?
About 60-75 percent of overall trading volume in the U.S. equity market, European financial markets, and major Asian capital markets is generated through algorithmic trading, according to Select USA, in 2018. However, the overall trading volume of algorithmic trading in emerging economies like India is estimated to be around 40 percent.
What is algorithmic trading?
Algorithmic trading is a method of trading the financial markets using pre-programmed algorithmic trading strategies to monitor the markets and execute trades. Algorithmic trading facilitates automated trading across all asset classes and market segments. This happens with zero direct human intervention, as the trades are executed based on pre-written instructions.
Here’s how it works: A trader loads his server with trading algos with specific instructions. The algos monitor the markets, searching for qualifying trade setups, and once they encounter the right setups, they execute the trades and manage them in accordance with the coded instructions.
So, from spotting the trade setups to executing and managing the trades, the entire process is automated. The idea of creating computer programs to trade one’s trading strategies is not just fascinating but has also become the ideal trading approach in recent times.
What percentage of trading is algorithmic?
In the U.S. equity market, European financial markets, and major Asian capital markets, algorithmic trading accounts for about 60-75 percent of the overall trading volume. Algo trading has been on the rise in the U.S. equity markets since the turn of the century but seems to have plateaued around 70-80 percent in the last 5 to 10 years.
In 2003, algo trading accounted for only about 15 percent of the market volume, but by 2010, more than 70 percent of U.S. equity market trading was through trading algorithms. It is also the same in the Forex markets, where algorithmic trading is measured at about 80 percent of orders in 2016 — up from about 25 percent of orders in 2006.
In the UK and EU, only about a third of all stock trades in 2006 were driven by computer trading algorithms, but by 2009, algorithmic trading accounted for 60-73 percent of all equity trading volume, according to study reports. For instance, in 2006, about 40 percent of all orders were entered by algorithmic traders at the London Stock Exchange, and the number was expected to be 60 percent by 2007.
Generally, American markets and European markets tend to have a higher proportion of algorithmic trades than other markets, and the estimate for 2012 was as high as an 80 percent proportion in some markets.
In Asia, Japan has the highest level of algorithmic trading, which accounted for approximately 70-80 percent of all trading in 2019 in the FX spot market transacted on the EBS2 — one of the most commonly used electronic broking systems in the interbank market. In the equity market, more than 70 percent of orders on Tokyo’s stock exchange are now made by algorithmic traders.
However, the contribution of algo trading is much lower in emerging economies. For example, in India, the overall trading volume of algorithmic trading estimated is roughly 40 percent.
Current trends in algorithmic trading
Presently, algorithmic trading is dominated by institutional traders and investors — traders who trade for a group or institution and buy and sell stocks on their behalf. These include pension funds, mutual fund families, insurance firms, and exchange-traded funds (ETFs).
Institutional investors use numerous computer-driven algorithmic strategies to execute and manage their orders. These techniques enable them to cut down the costs of trades and improve their profitability. Algorithmic trading is particularly helpful for high order sizes, which is why institutional investors and large brokerage firms largely make use of it to reduce trading expenses.
Institutional traders currently dominate the algo trading market, and they are expected to hold the major share for a long time. These traders not only trade huge sizes but also practice high-frequency trading. So, it is normal to use algorithmic trading to break the whole amount into small parts and continue to perform in specific time intervals or according to dedicated strategies.
For instance, if an institutional trader has to place an order for 1,00,000 shares, which can unduly affect the market, he can set up an algorithmic-trading instruction to execute 1,000 shares out every 15 seconds. This way, he gradually loads up orders in the market without unduly affecting the market prices.
Furthermore, algorithmic trading offers them the advantage to profit from value, which is based on millisecond arbitrage or little price movements. Algo trading also reduces the likelihood of human-caused errors and reacts to marketing conditions in a fraction of a second.
Apart from institutional traders, big retail, high-frequency traders use algorithmic trading to automate their trading process. It helps them to speed up the execution of trades, as they make many trades per day.
Algorithmic trading technology is not easy to afford, which is why it is mostly employed by institutional traders. But that trend is changing now as coding trading algorithms is becoming increasingly democratized. Trading platforms are making the coding languages easier, such that a retail trader can learn them and code their strategies themselves. Moreover, it is becoming easy to find freelance programmers that will code good algos for a few thousand bucks.
Algo trading market statistics
To get a full grasp of the algo trading market, we will discuss algorithmic trading stats under the following categories:
- Asset class statistics
- Equity statistics
- Forex statistics
- Hedge funds statistics
- Job market statistics
Asset class statistics
Algorithmic traders and investors use the method to trade most assets, including equities, foreign exchange, commodities, futures, options, and fixed income. But equities have the maximum share. Another market with a high volume of algo trading is the futures market.
According to data compiled by Goldman Sachs and shared by Analyzing Alpha, about 60%-70% of trading in equities in 2016 was via algorithmic trading, while about 40%-50% of futures trading was contributed by algorithmic trading. About 35%-50% of the commodity trading volume is generated by algorithmic trading, and similarly, nearly 40% of options trading was via trading algorithms. During that period, Forex recorded about 20%-30% of algorithmic trading, while fixed-income trading had about 10% of algorithmic trading. see the chart below:
In 2018, about 12-15% of municipal bonds were traded electronically. Also, of the $31.2 billion average daily volume traded in corporate bonds, about 26% were traded electronically in the third quarter of 2018. Similarly, 34.4% of investment-grade bonds traded electronically in November 2019.14
In 2021, nearly 92% of the multiple-listed options (equities & ETPs) were traded electronically, and 57.6% of the index options were electronically traded as of the time of the report.
The algorithmic trading volume in the stock market is growing at a CAGR of 11.23% between 2021 and2026, so it is projected that equities are likely to contribute $8.61 billion to the algo trading market share in 2027.
In 2018, algorithmic trading contributed nearly 60-73% of all U.S. equity trading. But less than 50% of trades for ticket sizes over $10 million were executed through algo trading in 2019. In Europe and the US, 10% of the hedge funds used algos to trade over 80% of their value in 2020, with the leading 12 investment banks earning about $2 billion from algo-managed portfolios, according to Coalition Greenwich.
In fact, about 52% of the institutional investors feel workflow efficiency is most instrumental in supporting best execution in algo trading.
There is no doubt that the introduction of algorithmic trading in the foreign exchange market has improved its efficiency. Now, even retail traders are also widely using algo trading to trade the market. However, while algorithmic trading gives an edge to Forex traders in terms of speed and execution, it is still difficult to acquire and implement. As a result, only a handful of influential traders can acquire such sophisticated trading, leading to imbalances and liquidity issues.
Nonetheless, these are some of the key stats: About 92% of trading in the Forex market was performed by trading algorithms instead of humans, and over 70% of total spot FX turnover across the globe is executed electronically in 2019. Moreover, 46% of all institutional trading volume is now executed through either direct market access (DMA), intelligent order routing, or algorithmic trades. Institutional traders believe that an additional 15% of FX trading is likely to be done via algos over the next two years.
There has been nearly 54% growth in trading FX algorithmically using mobile devices. About 15% of Forex traders believe that execution algorithms are most frequently accessed through multi-dealer platforms, while 14% of forex traders believe that execution algorithms will be distributed through voice chat.
Hedge funds statistics
It’s been reported that hedge funds with massive assets under management are increasingly turning to algorithmic trading to handle their portfolio strategically. Apart from convenience and speed, algo trading helps hedge funds to reduce market volatility and gain price efficiency. It also makes for easy access to dark pools and alternative trading systems.
According to Analyzing Alpha report, in Europe and the US, hedge funds managing funds between 0.5 million and 10 billion have posted a rise in their average number of algo providers in 2020, while those managing over 10 billion and those managing less than 500 million posted a decline in the average number of algo providers. Likewise, hedge funds managing between 500 million and 1 billion reported an average of 4.0 providers in 2020. Overall, about 46% of the hedge funds in Europe and the US used 5 or more algo providers, representing a 33% increase from 2019.
In the same 2020, about 10% of the hedge funds in Europe and the US used algos to trade over 80% of their value in 2020, while about 16.1% used algos to trade around 50%-60% of their value. But in 2019, about 25% of the hedge funds used algos to trade over 80% of their value.
There was a 7% year-over-year increase in dark liquidity algo usage in 2020 in Europe and the US, and nearly a 6% year-over-year increase in the implementation shortfall (single stock) usage within the same period. The usage of the percentage of volume algo strategy fell 10.58%, while volume-weighted average price (VWAP) algo dropped 0.86% over the same period. however, the usage Time-weighted average price (TWAP) rose by nearly 13% from its 2019 score.
Job market statistics
Given the rise in algorithmic trading, one can build a rewarding career trading with algorithms or creating trading algos. The work can be intellectually stimulating, and to succeed, one needs to possess a blended skillset that includes trading, programming, analytical, and mathematical skills, in addition to knowing how to develop trading strategies.
In fact, there are about 87,560 permanent vacancies in the UK with a requirement for process and methodology skills such as algorithmic trading year-to-date. As of May 2021, about 0.15% of the job postings in the UK cite algorithmic trading as a proportion of all IT jobs. And, the median annual salary for jobs citing algo trading in the UK is £90,000. In the United States, $52,037 was the average algorithmic trader salary as of April 27, 2021, with the range of annual salary of an algorithmic trader being between 48,570 and 53,845.
Algo market growth expectations and forecasts
According to a report from Mordor Intelligence, North America is expected to hold the major market growth in the market studied. With the US financial markets being the largest and most liquid globally and algorithmic trading accounting for around 60-73% of the overall US equity trading, the forecast is by no means surprising.
Some of the major factors contributing to the market growth during the forecast period are rising investments in trading technologies (including blockchain), increasing presence of algorithmic trading vendors, and growing government support for global trading. With modern technologies rapidly changing the formats of traditional investment models, automating all related trading processes is essentially a way to create a safe and efficient ecosystem for every interested investor.
For example, a team of developers, in February 2022, launched a new ecosystem known as Dex Finance. Dex Finance created a low-risk algorithmic trading model that nearly anyone can use. It automates advanced trading strategies while incentivizing investors to leave their deposits within the protocol. Many of such platforms are also on their way.
In fact, the global algorithmic trading market is expected to grow from 11.1 billion in 2019 to 18.8 billion by 2024. This growth is likely to be driven by rising demand for quick, reliable, and effective order execution. Some of the factors that would fuel the growth in the algo trading market include lowered transactional costs, heightened government regulations, and increased demand for market surveillance.
Below is a chart showing the expected growth by regions between 2018 and 2024:
However, as algorithmic trading strategies, including high-frequency trading (HFT) strategies, have grown more widespread, the potential for these strategies to impact the market adversely and firm stability has likewise grown. So, it is important to manage risks aggressively, both at the individual traders’ level and at the exchange regulation level. This is why major exchanges introduced circuit breakers.
The key players in algorithmic trading
Before concluding this report, let’s take a look at some of the major players that develop new solutions and create effective marketing strategies in algorithmic trading. The big players include Virtu Financial, Inc., Algo Trader AG, MetaQuotes Software Corp., IG Group, and Refinitiv Ltd.
Many of these key players keep repositioning themselves to dominate their ecosystem through strategic acquisitions. For instance, in June 2021, IG Group acquired Tastytrade, a brokerage and investor education platform, in a deal worth $1 billion.
Similarly, in November 2021, Refinitiv and Pio-Tech announced the partnership to provide banking clients of both companies in the Middle East and African region with sophisticated contemporary solutions that offer many distinct business values.
Many other moves are also in the pipeline. In February 2022, AlgoTrader raised $4.9 million in the Pre-Series B funding round to continue its digital asset growth strategy. This Pre-Series B funding was co-led by Credit Suisse Entrepreneur Capital and C3 EOS VC Fund with participation from East Asian venture capital firms Fenbushi Capital and SBI Investment.
What Percentage of Trading Is Algorithmic? Final words
In summary, the algorithmic trading market continues to grow and is likely to touch $18.8 billion by 2024, with equities likely to contribute $8.61 billion in the algo trading market share in 2027. The algorithmic trading market is expected to grow at a CAGR of 11.23% between 2021 and 2026, with the Asia Pacific region being the fastest growing market but North America remains the largest market.
Source: Mordor Intelligence and Analyzing Alpha