When you trade in a stock market, you bid on a price and get the shares into your demat account. When the share cost increases, you sell it in the market, giving you its value in exchange. Typically, a stock market’s liquidity depends on the existence of a high number of buyers and sellers. When one initiates a sell order, the buyers get allotted those shares in exchange for the amount.

Ideally, something similar happens in the market-making process.  
It’s a trading strategy that financial institutions and individuals utilise to ensure there is enough liquidity in the market.

How do Market Makers Function?

This is how the entire procedure operates:

• Buy and Sell Orders: Market makers consistently place orders to buy and sell a specific asset (e.g., stocks, cryptocurrency, etc.).  

• Earning from Spread: The spread is the difference between the asking price (ask) and the bid price (buy). Market makers profit from this spread.

• Creating Liquidity: Market makers’ continuous buying and selling keeps the market active enough to reduce volatility and increase fluidity.

• Inventory Management: To minimise directional risk factors, market makers try to acquire and sell similar volumes of assets in order to avoid maintaining a sizable net position.
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Let’s understand this process from an example:
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A market maker buys a security from a financial market at $20 and sells it at $20.20. Now, since he buys it at $20 and sells it at $20.20, he makes a profit of $0.20 per unit, which is the spread. This constant buying & selling of assets enables other traders to find someone to buy from or sell to, inducing liquidity in the market.

What Market Making Offers

1. Liquidity Provision
Market makers constantly quote bids and ask prices to guarantee the steady trade of financial instruments at these prices. This mitigates liquidity risk for traders, who can readily enter and exit positions. Additionally, most firms function as market makers in foreign exchange trading by providing both buying and selling rates for currencies. Likewise, for stock exchanges, market makers are either officially designated for specific equities or work without formal designation.
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2. Reduction in Price Volatility
Continuous quotes assist market makers in dampening price volatility.  Their active participation assures that large buy or sell orders do not lead to sharp price movement, as they are ready to absorb some of the order flow. Moreover, in modern electronic markets, market-making algorithms are used to provide steady quotes, often without the formal designation of a market maker.
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3. Conducting Trading
For low-liquid markets or less frequently traded instruments, market makers execute trading by ensuring that someone is always looking to buy or sell a financial instrument, i.e., to make a trade.

Profitability of Market Making

The primary source of profit from a market-making activity is the spread between the bid and ask prices.
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1. Exploiting the Spread
A market maker always strives to buy at the bid price and sell at the ask price, capturing the spread between these prices as profit. The spread compensates them for the risk of holding an inventory of the financial instrument and providing liquidity to the market. Furthermore, it also covers the costs associated with trading, like transaction fees and the risk of adverse price movements.
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2. Impact of Price Movement
Local price fluxes and net price charges can influence market profitability. While traders profit from local price fluctuations by capturing the spread multiple times, significant net price changes can lead to inventory imbalances and potential losses. However, market-making is usually profitable in markets with mean-riveting price series, where prices tend to revert to a long-term average. This behaviour allows market makers to capture spreads more conveniently without the risk of large directional movements.  
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3. Algorithmic Market Making
Modern markets utilise algorithmic trading strategies to operate a seamless market-making process. These algorithms are designed to quote competitively and constantly, bid & ask prices, adjusting them based on market conditions to manage inventory risk.Theoretical models and empirical studies have shown that algorithmic market-making can be profitable under certain conditions, particularly in markets with mean-reverting price processes. One such example is the Ornstein-Uhlenbeck (OU) process, which can generate consistent profits over time despite restrictions in trading frequency.
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4. Comparison with Statistical Arbitrage
Market-making differs from statistical arbitrage in its approach to risk and profitability. While they minimise directional risk by maintaining a balanced inventory, statistical arbitrage strategies deliberately take directional bets based on quantitative models of future price movements. Moreover, market-making profitability is driven by capturing spreads in a volatile but non-directional market, whereas statistical arbitrage seeks to earn from predicting and betting on price movements.

Market Making Strategy

Proper market-making strategies involve continuously quoting both buy (bid) and sell (ask) prices for financial instruments to offer liquidity and profit from the bid-ask spread.
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Well-defined strategies include:
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1. Quoting Bid and Ask Prices:
The core idea of market-making is to quote competitive buy-and-sell prices. Market makers set these prices to entice buyers and sellers, ensuring they can capture the bid-ask spread. Prices are adjusted based on recent market conditions, inventory levels, and risk management principles.
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2. Capturing the Spread
The difference between the ask and bid prices is known as the spread. By purchasing low at the bid price and selling high at the ask price, market makers hope to profit from this spread. A thorough understanding of market dynamics and meticulous order management are necessary for consistently capturing the spread.
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3. Inventory Management
A key component of reducing directional risk is efficient inventory management. Market makers work hard to balance inventories to avoid taking positions that, should market prices go against them, could result in significant losses. Inventory levels are changed in real-time based on trading activity and market conditions.
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4. Algorithmic Market Making
Modern market making often includes using sophisticated algorithms to automate the quoting process.

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• These algorithms work by:
  
  • Continuously update bid and ask prices based on real-time market data
  • Adjust quotes to maintain a desired inventory level.  
  • Respond rapidly to market changes to capture the spread efficiently.
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5. Risk Management
Managing risk is a critical component of market making. Strategies are designed to minimize exposure to adverse price movements and market volatility. Risk management techniques include setting limits on inventory levels, using stop-loss orders, and dynamically adjusting quotes based on market conditions.
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6. Mean Reversion and Local Price Fluctuations:
Market making is advantageous in markets that show mean reversion—a phenomenon in which prices tend to return to a long-term average. Market makers can more reliably capture spreads thanks to this tendency. Furthermore, as prices swing between the quoted bid and ask levels, local price variations can catch the spread several times.
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7. Theoretical Model
A published paper reviews several theoretical models that examine market making’s profitability. These models consider variables, including mean reversion, local price swings, and the effects of trading frequency limitations. The Ornstein-Uhlenbeck (OU) process describes a mean-reverting price series. Because price swings are predictable, market-making tactics applied to OU operations can yield steady returns.
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8. Empirical Observations
Empirical studies have proved that market-making can be advantageous in specific markets like foreign exchange and commodities with a provision of mean revision and high trading volumes. Furthermore, practical implementation of market-making strategies involves adapting to real-world challenges, such as executing speed and regulatory requirements.  

Market-Making Software

Here is a list of industry-grade market-making software that are used by top market-makers:
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Qualaroo: This market research platform offers features such as real-time feedback, expertly created survey templates, and connectivity with other applications like Hubspot, Zapier, and Slack1.
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Empirica: Empirica offers market-making software customised for small hedge funds and cryptocurrency initiatives. It highlights the necessity of cutting-edge technology, algorithms, and trader supervision2.

Market-Making algorithm

An efficient market making algorithm is necessary for providing liquidity and promoting smooth market operations.
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We have shortlisted five popular market-making algorithms:
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• Volume-Weighted Average Price (VWAP): This algorithm uses a trading benchmark: the volume-weighted average price at which a securities trades. It facilitates the execution of orders near the distribution of market volume.
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• Time-Weighted Average Price (TWAP): By breaking orders into smaller pieces and releasing them at regular intervals, TWAP executes large orders throughout the trading day to reduce the impact on the market.
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• Percentage of Volume (POV): This algorithm, also called Participation Rate, aims to place orders that represent a specific percentage of trading volume and modify their size based on current market conditions.
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• Implementation Shortfall (IS): This technique limits an order’s execution cost by weighing the market impact and the opportunity cost of a delayed execution.
  
  

• Staggered Orders: This entails putting in several limit orders to purchase or sell at various prices. The market picks up these orders as it moves, offering liquidity and capturing the spread.

Market-Making Firm

1. Flovtec: Flov Technologies AG, a Swiss technology firm, provides market-making solutions to token issuers and digital asset exchanges, enhancing market liquidity and efficiency. Recognised for two consecutive years among the top 50 blockchain companies globally by CVVC and PWC’s strategy &, Flovtec received the Crypto Valley Blockchain Award 2019 for its significant contributions to blockchain technology. Additionally, it won the inaugural TADS international award for outstanding contributions to blockchain-based tokenization.
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2. G-20 Group: Established on the principles of teamwork and integrity, the G-20 Group places client service at its core. Since 2010, it has operated as an Asset Manager and Advisor for Institutional clients in Switzerland, holding regulatory licences across various jurisdictions. Its team melds a startup mentality with extensive experience in Proprietary Trading, Digital Assets, Technology, and Quantitative Finance. Offering Liquidity Provision, Asset Management, and Advisory services, G-20 emphasises a quantitative, technology-driven approach.  

Market making Services

Token issuers can trade and control their liquidity by using Market-Making Services, which allows them to define their market-making methods. Traditional market makers provide liquidity by using a combination of tokens lent from the projects’ money and their cash to generate trading pairs. They market on their terms and keep the money they make from these endeavours.
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As a prominent firm in the cryptocurrency market making sector, we are ready to make acquiring and selling digital assets more efficient and increase token accessibility and liquidity. We also understand how crucial it is to have liquid trading environments in developing and mature markets. Therefore, the main goals of market-making services are to increase trading efficiency, decrease market slippage, promote liquidity, tighten spreads, and strengthen order books.

Here is the list of market-making services:

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1. Order-Book Liquidity Management
   A significant amount of liquidity in the order book gives you enough depth to execute orders without significantly impacting the price.
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2. Cross-Exchange Arbitrage Management
   You can profit from spreads by purchasing an asset at a lower price on one exchange and selling it at a higher price on another. This allows you to take advantage of price variations for the same asset across many exchanges.
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3. Bid-Ask Spread Management
   Keeping the bid-ask spread small can save transaction costs and promote a more efficient market environment.
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4. 24X7 Agile Cryptocurrency Market Making
   Since the digital currency markets are always open, you may access liquidity that adjusts to changing market conditions to reduce volatility and guarantee stability.
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5. Volume Facilitation
   Market-making services generate large trade volumes that attract more participants to the market while promoting liquidity and active participation.
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6. Liquidation
   A steady conversion of swift assets into cash or other liquid forms is crucial during rapid market movements or margin calls.
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7. Price Support
   You will get support to uphold asset prices, such as purchasing back assets to prevent prices from dropping below a certain level.
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8. Strategic Insights from Experts
   In addition to the aforementioned market-making services, you will implement trading strategies to help you achieve the maximum spread.

Automated Market Maker

In a decentralized exchange (DeX), no single entity is involved, and smart contracts carry out the whole crypto trading process. So far, unlike traditional centralized exchanges, the price of cryptocurrencies is determined by an algorithm using mathematical formulae. Something similar happens with Automated Market Makers.  
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Automated Market Maker (AMM) is a type of DEX that relies on algorithms to facilitate the trading of digital assets. Automated Market Makers strives to maintain liquidity in the DeFi ecosystem through liquidity pools. Additionally, participants supply these liquidity pools with crypto tokens, and mathematical formulas determine their prices.
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• Automated Market Makers have several advantages over traditional market makers:
   
  • Continuous Liquidity: AMM provides ongoing liquidity for various assets, making it easier to trade less popular cryptocurrencies.  
  • Open Participation: Anyone can provide liquidity to AMMs and engage in trading, often with lower fees than traditional exchanges.  
  • Decentralization: It operates without centralized intermediaries, giving users more autonomy and ownership over their trades.  

Algorithmic Market Making

The central concept is managing inventory, conducting deals, and reducing market-making risks using automated procedures and statistical models. Because algorithmic market makers can work faster and more often than human traders, they can execute trades efficiently and react to market situations instantly.
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Here is the popular algorithm for the market maker:
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• The Avellaneda-Stoikov model
  
  
  • The Avellaneda-Stoikov model is a market-making framework that establishes the optimal ask and bid prices. It assumes that an asset’s price moves in a Brownian motion. Based on the asset’s cost, the market maker modifies the bid and asks for quotes; as bids are more cautious, the frequency of trades decreases.
     
    Additionally, the model ensures that the market maker’s inventory does not exceed predetermined bounds by withholding quotes when such bounds are reached. To balance possible rewards against risks, the objective is to maximise the market maker’s final cash and inventory value while considering risk aversion.

Example Of A Market Maker

Goldman Sachs & Co (GSCO) is one of the firms that functions as an equity market maker on the NASDAQ in the US. These firms actively quote two-sided markets in a given asset, providing bids and asks together with the market size, thereby supplying liquidity to the market. They offer the markets depth and benefit from variations in the bid-ask spread.
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Leading equity market makers are JP Morgan Securities, Inc. (JPHQ), Deutsche Bank Securities (DBAB), Morgan Stanley & Co. Inc. (MSCO), Merrill Lynch (MLCO), and Credit Suisse Securities LLC (FBCO). These significant institutions make buying and selling securities smoother, improving the efficiency and liquidity of the financial markets.
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Orcabay and Empirica are the leaders in the crypto market-making industry. Acheron Trading and Cumberland, a company of DRW Holdings, are renowned for providing extensive assistance for digital assets. Bluesky Capital and Altonomy are commended for their price and liquidity stability contribution. Virtu Financial and Jump Trading provide sophisticated liquidity solutions by leveraging their global expertise. With their extensive liquidity and effective trading techniques, GSR and Wintermute round out the list and guarantee thriving and easily accessible cryptocurrency marketplaces.

Market-Making Companies

Several market-making companies in the crypto industry are distinguished by their outstanding offerings. Wintermute is a well-known participant, recognised for its algorithmic trading and broad presence on more than 50 exchanges, including Coinbase and Binance. Efficient Frontier is a San Francisco, Gibraltar, and Tel Aviv-based company that provides expert liquidity management and analytics.
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With ten years of experience, GSR is a world leader in cryptocurrency trading and market-making, offering solutions for risk management and liquidity on various platforms. DRW’s subsidiary Cumberland is a prominent player in major financial centres such as the US, London, Seoul, Tokyo, and Singapore, focusing on trading crypto-assets. These companies significantly influence the stability and liquidity of the cryptocurrency markets, promoting effective and equitable trading for all players.

Equity Market Making

Equity market makers are companies or individuals that actively maintain liquidity in the stock markets by offering to purchase and sell shares at a price disclosed to the public.  
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• They are vital to the financial markets because they:
  
  • Offering two-sided quotes, which include the ask (sell) and bid (purchase) values for securities.
  • They enable transactions by promptly filling orders from their inventory, preserving continuous trade.
  • They are making money from the difference between their purchasing and selling prices or the bid-ask spread.

Mean Reversion

Mean Reversion is a financial concept where an asset’s price eventually reverts to its long-term average. This phenomenon is observed when prices fluctuate around a central value and tend to revert to this average after periods of deviation.
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• What The Book Says
  A stochastic price series is mean-reverting if the price shows a downward trend when it is above its long-term mean and an upward trend when it is below this mean. Market-making algorithms can exploit this tendency to revert to the average price.
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• Profitability
  Market-making algorithms are typically profitable on mean-reverting time series because the prices tend to oscillate around the mean, allowing the market maker to buy low and sell high within these oscillations.
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• Examples
  Empirical observations of mean reversion have been made in several markets, including foreign currency rates and commodities. The Ornstein-Uhlenbeck process is a well-researched mean-reverting process that predicts pricing dynamics and sustains the long-term profitability of market-making techniques.

Mean Reversion Trading

Mean reversion trading returns asset values to their mean or historical norms. This strategy is predicated on the idea that prices will eventually return to average and that high and low points are transient.
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Traders use indicators such as Bollinger Bands, moving averages, and the Relative Strength Index (RSI) to determine whether a market is overbought or oversold. When prices diverge significantly from the norm, traders expect a reversal; they sell high (overbought) and buy low (oversold) prices.
 

To successfully trade mean reversion, one needs to manage risk effectively and use stop-loss orders to limit losses if prices continue to move away from the mean rather than reverting.

Mean Reversion Strategy

Earlier, we discussed that market-making is typically profitable for mean-reverting time series that tend to return to a long-term average. Many markets, particularly those related to commodities and foreign exchange, have empirically shown mean reversion.  
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In addition to obtaining greater profit guarantees for the Ornstein-Uhlenbeck (OU) process—the canonical stochastic mean-reverting process—and other stochastic mean-reverting series explained in the finance literature, it demonstrated that even the smallest mean reversion produces positive expected profit. Hence, the Ornstein-Uhlenbeck process is a specific example of a mean-reverting process that supports these strategies.

Takeaway

Because they offer vital stability and liquidity, market makers are essential players in equities and cryptocurrency markets. They maintain market equilibrium and efficient trading by consistently providing buy and sell prices and utilising techniques like mean reversion. Organisations like Merrill Lynch and Wintermute are prime examples of this crucial function, adjusting to technology breakthroughs to preserve stable and equitable market conditions. Their continuous support keeps the world’s financial systems robust and effective.