Automated Market Making and Its Impact

Automated Market Making

Market makers are entities that provide both buy & sell quotes for certain securities. They can also be termed as ‘liquidity providers’. Market makers fulfill a large amount of orders in the financial markets. Essentially, market makers take the opposite side of investor trading volume. For investors who want to buy, market makers will sell to them. For investors who want to sell, market makers will buy from them.

Market makers, therefore, satisfy the supply & demand of the financial markets & keep securities changing hands between sellers & buyers.

Automated Market Making

How does the Market Maker make money?

Market makers aim to buy at their ‘bid’ quote price and sell at their ‘ask’ quote price. The difference between the ‘bid’ price and ‘ask’ price is the ‘bid-ask spread’, and that is the profit that market makers target.How does Market Maker make money

If the market maker successfully sells at Rs 110 & buys at Rs 100, then he makes a profit of Rs 10 after those two trades.

Automated Market Making

To be efficient, market makers should be able to adjust their quotes immediately in response to events. These events could be,

  • changes in prices of financial instruments,
  • trading positions accumulated by the market maker

Automated systems are more efficient than human beings in detecting & responding to such events. Therefore, they can handle their risks better

Since automated systems can handle their risks better, therefore they offer better quotes which are closer to fair valuation for others.

Automated Market Making

How Algorithmic Trading enables Market Making?

Faster Response Time

Pricing of derivatives that enable investors to hedge often involve time-consuming mathematical calculations While humans can take minutes, automated systems are can do these calculations in microseconds.

Faster Respaonse Time

Higher Scalability

Human traders can only track activities in a few instruments, while automated systems can do thousands simultaneously. The same trader using an automated trading system provide liquidity in significantly more financial instruments simultaneously.

Higher Scalability

Availability is better

Machines don’t have to take breaks. Automated market making systems are always active.


Asset price volatility reduces

The prices between consecutive trades done against a human market maker will be much higher than the prices between consecutive trades done against automated market maker.

Asset price volatility reduces

With automated market making, the order book becomes thick. Execution price for even big orders are close to fair price.

What are market makers’ risks?

Stuck with wrong positions

Market makers are always counter parties to trades done by informed traders. In case of price moves, the market makers are often stuck with wrong positions.

Stuck with wrong positions

Information asymmetry

The biggest risk for the market maker is not having the latest information. Information asymmetry can make market making unviable.

Lack of latest information is biggest risk

Speed Barriers

Efficient market making therefore requires the ability to quickly respond to events so as to be not stuck with positional losses.

Market makers who manage such positional loss risks by adjusting to new information in the market quick can therefore afford to keep making markets in a sustainable and profitable way.

Introduction of speed barriers would make it difficult for market makers to respond quickly to events. And make their slowed orders as easy targets for arbitrageurs.

In its Discussion paper on ‘Strengthening of the Regulatory framework for Algorithmic Trading & Co-location’ SEBI has proposal certain mechanisms for stock exchanges and sought inputs and suggestions from market participants on the same. Read the proposal and share your inputs on how you think this would influence the market and market makers!

Next Steps

Learn more about algorithmic market making and other automated trading strategies like Trading with ETF, Candlestick Trading Strategy, Pair Trading Strategy and Black-Scholes Option Pricing Model. If you are a coder or an intraday trader looking to start your own automated trading desk, learn automated trading from live Interactive lectures by daily-practitioners. Executive Programme in Algorithmic Trading covers training modules like Statistics & Econometrics, Financial Computing & Technology, and Algorithmic & Quantitative Trading. Enroll now!

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