Hedge funds driven by AI outperform hedge funds that rely mostly on human input (2024)

A new study has found that hedge funds with the highest level of automation outperform those that rely more on human involvement.

During the period that was studied (2006 to 2021), the AI-based hedge funds generated average returns of about 0.75% per month, vs. about 0.25% per month for the human-guided hedge funds.

The study, called “Man Versus Machine: On Artificial Intelligence and Hedge Funds Performance,” was written by researchers from Texas A&M University and Finland’s University of Vaas. It appeared on April 22 in the journal Applied Economics.

What you will learn in this post:

  • 1 What are hedge funds?
  • 2 Automation in the hedge fund industry
  • 3 Hedge fund database
  • 4 Categorizing hedge funds into clusters
  • 5 The four trading strategies explained
  • 6 AI-based hedge funds got the best results
  • 7 Combined funds did the worst
    • 7.1 Other recent studies of note:

What are hedge funds?

Hedge funds, as the authors explain, are “pooled investment funds that engage in short-selling, leverage, and derivatives in an effort to improve risk-managed performance.”

These funds are often used by institutional investors, such as pension plans and university endowments, as well as high-net-worth individuals.

A 2020 report found that the total amount of assets managed by hedge funds around the world is $3.87 trillion, a figure that is expected to grow to $4.28 trillion by 2025.

The industry also employs about 18,000 hedge fund managers worldwide.

Automation in the hedge fund industry

Trends in this increasingly competitive industry represent a major challenge. And that competition is prompting hedge funds to increasingly rely on technological advantages.

Although computerized, automated trading systems have existed for many decades, they are becoming more and more sophisticated every year.

The current study aimed to find out whether giving more control to advanced trading algorithms leads to better returns, and whether hedge funds might eventually progress towards “fully automated decision making.”

Hedge fund database

The authors based their findings on a database containing information on thousands of hedge funds. This massive data source is managed by a London-based company called Preqin, which specializes in providing financial data.

For the purposes of this study, the authors only included hedge funds that a) operate within North American markets, b) report U.S. dollar-denominated returns, and c) mainly focus on equities.

They also excluded any funds that did not provide the database with information about their trading style.

This resulted in a final sample of 826 hedge funds. The study looked at fund results from 173 consecutive months, spanning from September 2006 to January 2021.

Categorizing hedge funds into clusters

The study’s authors assigned each of these 826 hedge funds to one of four categories, depending on the fund’s “level of human involvement in the decision-making process,” as the authors write.

Those four categories are discretionary, systematic, combined, or AIML (which stands for “artificial intelligence and machine learning”).

The categorization procedure was based on data from the Preqin database. And that database itself is based on information gathered from a range of sources, including open data warehouses, SEC disclosures and other regulatory filings, and information provided by the funds themselves.

Almost all the funds included in the database indicate that they use a certain kind of trading style (e.g. systematic, discretionary, or combined), and also indicate whether they use AI methods in their trading strategies.

The four trading strategies explained

The least automated of the four fund categories are the “discretionary funds,” which rely mostly on mechanical trading rules performed by humans.

These funds place a greater emphasis on managers in general, specifically their professionalism and skill.

The second-least automated type is the “systematic fund,” which typically uses a sophisticated quantitative framework based on statistical methods.

This class was followed by “combined funds,” which for example emphasize a systematic trading style, but manually choose when trades are closed.

And the most automated of the four hedge fund categories are the “AIML funds.”

As the authors explain, these AI funds “are simply given an input along with a desired output, and the model itself determines the best course of action via a mathematical function.”

Of the 826 funds in the researchers’ sample, they identified 36 as AIML funds.

AI-based hedge funds got the best results

The authors found that the hedge funds with the highest level of automation (in terms of using AI and machine learning in their investment process) generate the highest returns.

These funds averaged a return of 74 – 79 basis points per month (a “basis point” is one hundredth of a percentage point, so in this case that equates to an average monthly return of 0.74% – 0.79%).

In contrast, the average returns for the least-automated category of funds – the discretionary funds – were only 0.23 – 0.28 basis points, i.e. a difference of about 0.5% per month compared to the AIML funds.

Specifically, the authors write, employing a strategy that relies on the AI-driven funds generates “statistically significant average payoffs that range from 50 to 56 basis points per month.”

Combined funds did the worst

Curiously, the authors also found that the so-called “combined funds,” with a medium level of both automation and human involvement, performed the worst among the four types of hedge fund strategies.

“We infer that mixing human decision-making with automated processes,” they write, “is inferior to relying predominantly on either human or machine decision-making. This puzzle is left for future research.”

In sum, they found that the AIML funds “generated superior average returns compared to hedge funds with higher levels of human involvement.”

The authors add that this is the first study they know of to carry out this kind of performance comparison of hedge funds.

Study: Man versus machine: on artificial intelligence and hedge funds performance
Authors: Klaus Grobys, James W. Kolari, and Joachim Niang
Publication date: April 22, 2022
Journal: Applied Economics
DOI: https://doi.org/10.1080/00036846.2022.2032585
Picture: by DepositPhotos

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Hedge funds driven by AI outperform hedge funds that rely mostly on human input (2024)

FAQs

Hedge funds driven by AI outperform hedge funds that rely mostly on human input? ›

Hedge funds driven by AI outperform hedge funds that rely mostly on human input. A new study finds that automated hedge funds get better results than hedge funds that rely on human judgement. A new study has found that hedge funds with the highest level of automation outperform those that rely more on human involvement ...

Do AI powered mutual funds perform better? ›

AI-powered mutual funds significantly outperform their human-managed peers. AI-powered mutual funds show superior stock selection capability and lower turnover ratios to humans.

How many hedge funds use machine learning? ›

Over 50% of the existing Hedge Funds use Artificial Intelligence and Machine Learning to inform their investment decisions. Can they bring in better results than the industry standard? Certainly, you'll agree with me that the hedge fund investment industry has become synonymous with the popular machine vs. Man debate.

Do hedge funds use bots? ›

One of the most significant advantages of automated trading for hedge funds is Backtesting. It's a method of making the robot perform on historical data. Thus, you can have the performance graph of the robot in multiple previous and various market scenarios from different times.

What technology do hedge funds use? ›

Hedge fund managers and their service providers are also using AI to optimize middle and back office operations. As teams move away from managing work through spreadsheets and towards digital and cloud enterprise resource planning (ERP) solutions, AI can provide an edge.

Do hedge funds use AI? ›

In an analysis done in 2020, consulting and research firm Cerulli claims that there is increasingly strong evidence for hedge funds to use AI technologies.

Do hedge funds use artificial intelligence? ›

AI-based hedge funds got the best results

The authors found that the hedge funds with the highest level of automation (in terms of using AI and machine learning in their investment process) generate the highest returns.

What kind of machine learning do hedge funds use? ›

They usually work with time series data and try to make some predictions. There is a special type of deep learning architecture that is suitable for time series analysis: recurrent neural networks (RNNs), or even more specifically, a special type of recurrent neural network: long short-term memory (LSTM) networks.

Can machine learning be used for investing? ›

Due to their unique abilities to identify new relationships, machine learning models are the perfect tools to identify new investment opportunities. Investors can use this potential to gather market insights and make novel investments based on factors like your risk tolerance and financial situation.

What do data scientists do at hedge funds? ›

Lead investment research, predictive modeling, and quantitative research for a specific industry setting. Use a variety of alternative data sets to draw insights, create predictions and uncover new investment strategies. Develop specific granular data sets, exploring economical factors that can be used as key insights.

How many hedge funds use algorithmic trading? ›

In terms of the distribution of how much value of portfolio traded, the survey finds that over half (53%) of respondents are using algos to trade the majority of their total value traded; this was also the case in 2020 (Figure 5).

Do hedge funds use algorithmic trading? ›

Within this competitive environment, the investment strategies of top-performing hedge funds are increasingly dominated by algorithmic trading, with more than 50 percent of hedge funds now employing algorithms to trade the majority of their total value traded.

Do hedge funds trade with algorithms? ›

Algorithmic trading uses algorithms to help answer these questions — and it's an enormous industry. There are a lot of hedge funds and traditional investment banks that try to make money there.

What are the roles of technology in fund management? ›

Technology has been supporting the fund management sector covering many different areas in the likes of asset management systems, regulatory compliance, risk management, document management and reporting solutions when it comes to the buy-side, but also solutions dedicated to funds distribution, unit-holders' ...

What is a hedge fund do? ›

A hedge fund's purpose is to maximize investor returns and eliminate risk. If this structure and these objectives sound a lot like those of mutual funds, they are, but that's where the similarities end. Hedge funds are generally considered to be more aggressive, risky, and exclusive than mutual funds.

What is machine learning? ›

Machine learning (ML) is a type of artificial intelligence (AI) that allows software applications to become more accurate at predicting outcomes without being explicitly programmed to do so. Machine learning algorithms use historical data as input to predict new output values.

Can artificial intelligence beat the stock market? ›

Not only are machines incapable of predicting a black swan event, but, in reality, they are more likely to cause one, as traders found out the hard way during the 2010 flash crash when an algorithmic computer malfunction caused a temporary market meltdown. Ultimately, A.I is doomed to fail at stock market prediction.

Can hedge funds beat the market? ›

2021 wasn't the year for hedge funds to finally outperform passive investing. The big picture: Some hedge funds are sure to beat the index in any given year. But average hedge fund returns continued to lag — in a big way, according to data provided by eVestment.

Do hedge funds have Alpha? ›

Morgan Stanley strategist Adam Parker did an analysis of HFRI equity hedge index and found out that hedge funds do not have alpha anymore. The first finding of the analysis is that correlation between the HFRI index and the S&P 500 index passed 90%. The second finding is that HFRI's alpha is now zero.

How do hedge funds use Python? ›

Hedge funds don't use Python for everything, but they use Python for a lot. Balyasny Asset Management, for example, is looking for data analysts conversant in Python to work on fundamental research, data gathering and processing, along with back-testing data-driven idea generation.

Can AI replace fund managers? ›

AI won't replace investment managers, but it could improve returns.

Is AI trading profitable? ›

AI Robots provide a decent portfolio return with excellent winning rates and profit factors. AI Real-Time Patterns are excellent for day trading and swing trading.

What are the main limitations of applying artificial intelligence and machine learning to financial trading? ›

Challenges faced by finance companies while implementing AI solutions
  • Cost. Implementation of artificial intelligence in finance does not come cheap. ...
  • Financial risks. Even if the business has the necessary money to invest, there is always the risk of a low ROI.
  • Lack of resources. ...
  • Skillset challenges. ...
  • Data protection.
Dec 16, 2020

How much do data scientists at hedge funds make? ›

How much does a Data Scientist Hedge Fund make? As of Aug 9, 2022, the average annual pay for a Data Scientist Hedge Fund in the United States is $107,863 a year. Just in case you need a simple salary calculator, that works out to be approximately $51.86 an hour. This is the equivalent of $2,074/week or $8,988/month.

How much do hedge fund quants make? ›

What do Quants Earn? Compensation in the field of finance tends to be very high, and quantitative analysis follows this trend. 45 It is not uncommon to find positions with posted salaries of $250,000 or more, and when you add in bonuses, a quant likely could earn $500,000+ per year.

Can algorithmic trading make money? ›

Algorithmic trading (also called automated trading, black-box trading, or algo-trading) uses a computer program that follows a defined set of instructions (an algorithm) to place a trade. The trade, in theory, can generate profits at a speed and frequency that is impossible for a human trader.

Do banks use algorithmic trading? ›

Banks have made heavy investments in algorithmic trading with top institutions offering a variety of solutions for trading currencies. For example, "adaptive algos", offered by many banks in recent months, can change their trading styles automatically depending on fluctuating market conditions.

Who uses algorithmic trading? ›

Algorithmic trading is mainly used by institutional investors and big brokerage houses to cut down on costs associated with trading. According to research, algorithmic trading is especially beneficial for large order sizes that may comprise as much as 10% of overall trading volume.

Do automated trading systems work? ›

While a few EAs will work, and produce good returns, most will not. An incredibly small percentage of people who attempt day trading are successful at it, and that includes people who create and buy EAs. The odds of success are still very small even when using a trading robot.

What do hedge funds use to trade? ›

Using derivatives.

Hedge funds often take advantage of financial derivative contracts such as options, forwards and futures. Options often trade at a fraction of the original instrument's price and are a great way to lower certain market risks (hedge) against other open positions.

Is there an algorithm for the stock market? ›

You've likely heard the term “algorithms” or (algos for short) used in reference to trading. Algorithms run the markets and are responsible for most of the trading volume in the U.S. stock markets on any given trading day.

What is the difference between quantitative trading and algorithmic trading? ›

Algorithmic trading, simply put, is the use of Algorithms to perform trading, irrespective of the type of trading strategy. Quantitative Trading on the other hand is about using statistical methodologies to create trading strategies to generate alpha, as well as for better execution.

How much do algorithmic traders make? ›

The salaries of Algorithmic Traders in the US range from $20,072 to $535,864 , with a median salary of $96,858 . The middle 57% of Algorithmic Traders makes between $96,858 and $243,042, with the top 86% making $535,864.

What is the role of technology in the investment banking business activities? ›

Machines are likely to take up to 10-25 percent of work across all bank functions with AI and automation, according to a report by McKinsey. Automation in banking will multiply capacity and allow employees with free bandwidth to concentrate on higher-value projects.

What is hedge fund in simple words? ›

Put simply, a hedge fund is a pool of money that takes both short and long positions, buys and sells equities, initiates arbitrage, and trades bonds, currencies, convertible securities, commodities and derivative products to generate returns at reduced risk.

Why is it called a hedge fund? ›

The word "hedge", meaning a line of bushes around the perimeter of a field, has long been used as a metaphor for placing limits on risk. Early hedge funds sought to hedge specific investments against general market fluctuations by shorting the market, hence the name.

What is wrong with hedge funds? ›

Another problem with hedge funds is that many of them lock up investor money for relatively long periods of time. In other words, an investor cannot redeem (withdraw) their money until a number of months or years has passed, even if the fund fails to perform.

What's the difference between AI and machine learning? ›

Put in context, artificial intelligence refers to the general ability of computers to emulate human thought and perform tasks in real-world environments, while machine learning refers to the technologies and algorithms that enable systems to identify patterns, make decisions, and improve themselves through experience ...

What is artificial intelligence in simple words? ›

What is artificial intelligence? Artificial intelligence (AI) is the ability of a computer or a robot controlled by a computer to do tasks that are usually done by humans because they require human intelligence and discernment.

How do you learn AI? ›

It learns from itself as more data is fed to it, like machine learning algorithms. However, deep learning algorithms function differently when it comes to gathering information from data. Similar to unsupervised machine learning algorithms, neural networks create a hidden structure in the data given to them.

How is machine learning used in stock market? ›

Predict The Stock Market With Machine Learning [Project Tutorial]

How can I invest in deep learning? ›

One way to invest in deep learning that may carry lower risk than direct investment in startups is to buy shares of a bigger, established public company that has deep learning initiatives.

What is Q AI? ›

Q.ai uses quantitative techniques and artificial intelligence to generate investment recommendations across multiple asset classes including Stocks, ETFs, Options, and Cryptocurrencies.

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