Algorithmic trading, also called algo trading, is a system in which pre-programmed algorithms are utilized to execute trades. There is no human intervention in this method. These trades are executed upon pre-written instructions.
Incredible, algorithmic trading is widely used today because of its speed and lower operational cost.
In this article, we compiled the recent and most important algorithmic trading statistics in different areas, including the following:
- Market Statistics
- Asset Class Statistics
- Job Market Statistics
- Hedge Funds Statistics
- Forex Statistics
- High-Frequency Statistics
- E-Trading Statistics
- In 2018, algorithmic trading contributed 60 to 73% of all US equity trading.
- In 2019, less than 50% of trades for ticket sizes over $10 million were executed through algorithmic trading.
- According to Coalition Greenwich, the top 12 investment banks earned around $2 billion from algorithmic trading in 2020.
- Between 2021 and 2026, the algorithmic market is growing at a CAGR of 11.23%.
- In 2027, equities are likely to contribute $8.61 billion to the algorithmic trading market.
- 52% of institutional investors feel workflow efficiency is instrumental in supporting the best execution in algorithmic trading.
- Morgan Stanley’s algorithm and portfolio trading account for nearly 80% of its corporate bond tickets and 20% of volumes.
- 50% of stock trading volume in the US is currently driven by computer-backed high-frequency trading.
- According to Wells Fargo, robots will replace 200,000 banking jobs over the next ten years.
- 57% of institutional investors believe that AI and Machine Learning will shape the future of trading over the next three years. Also, 6% of institutional investors believe that mobile trading applications will shape the future of trading over the next three years.
- 72% of institutional investors think AI and Machine Learning provide deep data analytics. And 23% of institutional investors reported an increase in algorithm trading during COVID-19.
- High-frequency trading costs retail investors up to $5 billion per year, and the high-frequency trading volume grew by 164% between 2005 and 2009.
- In 2009, Alternative Trading Systems (ATS) executed approximately 10.2% of share volume in NMS stocks. And top two ATSs each executed nearly 1-2% of share volume in NMS stocks, with most ATSs running under 1% of share volume.
- In 2010, 19%-40% was the range of market share of high-frequency trading in Europe, 40%-70% in the US, and 10% in Australia.
- In 2010, the May Flash Crash led the Dow Jones to plummet 1000 points in a single trading day.
- In 2010, 20% of Asia’s total trades were algorithmic, 30% in Europe, and 50% in the US.
- On August 1, 2012, Knight Capital lost $440 million in less than an hour due to HF trading.
- In 2016, HFT initiated 10-40% of trading volume in equities and 10–15% of volume in foreign exchange and commodities.
- According to Financial Industry Regulatory Authority (FINRA), in 2018, electronic trades clocked in at a daily average of 66.7 billion. It shows an 87% year-over-year surge.
- In 2018, the daily average of electronic trading was 135 billion.
- In 2018, North America had an algorithmic trading market of $3.89.
- In 2018, commodities accounted for a $1.38 billion algorithm trading market share.
- In 2018, the Dow Jones Industrial Average fell nearly 1,600 points in just fifteen minutes.
- In 2018, 10.35% of the traders of APAC chose “Ease of use” as the reason for algorithm trading. And 9.55% of the traders of APAC chose “Consistency in execution.”
- In 2018, traders of buy-side firms in APAC with more than $50 billion AUM had nearly 2-3 algorithmic traders and 3-4 traders for firms in APAC with AUM of between 1 billion and 10 billion.
- In 2018, 75% of the buy-side firm in APAC used VWAP as a strategy for algorithmic trading, and 61.98% used percentage volume.
- In 2019, 33 ATSs executed trades in NMS stocks.
- In 2019, nearly 11% of high-yield bonds traded electronically on average.
- In 2020, more than 60% of trades for ticket sizes over $10 million were executed through algorithm trading.
- In 2020, high-Frequency Trading industry revenue was expected to increase by 26.1% because of COVID-19.
- In 2021, the average daily e-trading volume was $10.6 billion.
- In 2021, 50% of institutional investors expected growth in algorithmic trading.
- In 2024, the total algorithmic trading market is expected to grow to $18.8 billion.
- In 2027, equities are likely to contribute $8.61 billion in the algorithm trading market share.
Asset Class Statistics
- About 35%-50% of the commodity trading volume is executed by algorithmic trading.
- In 2016, 60%-70% of algorithmic trading was contributed by equities, and futures contributed 40%-50% of the algorithmic trading. Moreover, 40% of the algorithmic trading was contributed by options, 20%-30% of algorithmic trading was contributed by forex, and about 10% of algorithmic trading was contributed by fixed income.
- In 2018, 12-15% of municipal bond trading was traded electronically.
- In 2018, 26% of the corporate bond volume was traded electronically.
- In 2018, $31.2 billion was the average daily volume traded in corporate bonds.
- In 2019, 34.4% of investment-grade bonds were traded electronically.
- In 2021, 92% of the listed options (equities & ETPs) and 57.6% of the index options were electronically traded, and $1 million was a rough upper bound for automatically executed trades In the corporate bond market.
Job Market Statistics
- In the UK, 87,560 permanent vacancies have requirements for process and methodology skills such as algorithmic trading.
- In May 2021, 0.15% of the job postings in the UK cited algorithmic trading as a proportion of all IT jobs advertised.
- GBP 90,000 is the median annual salary for jobs citing algorithmic trading in the UK year-to-date.
- In the US, the annual salary of an algorithmic trader ranges between 48,570 and 53,845.
- In April 2021, the average algorithmic trader salary in the US was $52,037.
Hedge Funds Statistics
- In 2020, hedge funds managing funds between 0.5 million and 10 billion in Europe and the US had posted a rise in their average number of algorithm providers. And those managing over 10 billion and those managing less than 500 million posted a decline in the average number of providers. Moreover, those managing between 500 million and 1 billion reported an average of 4.0 providers.
- In 2020, 10% of the hedge funds used algorithms to trade over 80% of their value.
- In 2020, 16.1% of the hedge funds used algorithms to trade around 50%-60% of their value.
- In Europe and the US, there was a 7% year-over-year increase in dark liquidity algorithm usage in 2020. And nearly a 6% increase in the implementation shortfall (single stock) usage.
- In 2020, the volume algorithm strategy usage percentage fell 10.58%, while the volume-weighted average price (VWAP) algorithm dropped 0.86%.
- The usage Time-weighted average price (TWAP) rose by nearly 13% from its 2019 score.
- From the 33% in 2019, 46% of the hedge funds in Europe and the US used five or more algorithm providers.
- In the Forex market, 92% of trading is executed by Algorithms.
- Only 37% of the buy-side forex traders In the US and Europe use algorithmic trading.
- In 2019, 70% of total spot FX turnover worldwide was executed electronically.
- An additional 15% of FX trading will likely be done in the next two years through algorithms.
- There is a growth of 54% in trading FX algorithmically using mobile devices.
- About 15% of forex traders believe execution algorithms are most frequently accessed through multi-dealer platforms.
- About 14% of forex traders believe execution algorithms will be distributed through voice chat.
- In 2016, 36% of organizations measured latency through one-way and round-trip methods.
- In 2016, 26% of the organizations measured latency through Round-trip methods.
- 58.43% of organizations use infrastructure monitoring software and manual troubleshooting.
- 49.16% of the organizations leverage running virtualized workloads on dedicated clusters.
- According to the FCA, latency eliminating latency arbitrage would lower the cost of trading by 17%.
- The UK FCA study found that 20% of trading volume was from latency arbitrages.
- It is found that a 1-millisecond advantage in latency can cost more than $100 million per year.
- For April 2021, the average daily volume for Tradeweb was $896.8 billion. This shows a 17.5% increase year-over-year.
- For January 2021, the monthly electronic trading volume of MarketAxes Holdings is $575.3 billion.
- UBS accounts for 19.3% of the algorithmic trades in 2019.
- In 2019, The share volume of Crossfinder ATS in algorithmic trading was 9.8%.
- In 2019. JPM-X garnered a market share of 7.1% in algorithmic trading.
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