Market making refers broadly to trading strategies that seek to profit by providing liquidity to other traders while avoiding accumulating a large net position in a stock.
Before describing the models and results, It is worthy enough to know and to clarify the technical and historical differences between market-making and statistical arbitrage. The goal is to design a profitable automated trading strategy.
The market maker is averse to acquiring a large net long or short position in stock since in doing so there is the risk of large losses should the price move in the wrong direction. Thus if a market maker begins to acquire a large net long position, it would continue to quote a buy price. However, perhaps a somewhat lower one which is less likely to get executed.
Alternatively, the strategy might choose to lower its sell quote in order to increase the chances of acquiring short trades to offset its net long inventory. In this sense, pure M.M strategies have no “opinion” on which direction the price “should” move — indeed.
In contrast, many statistical arbitrage strategies are somehow the opposite of market-making.
they will acquire large net positions because they have a prediction or model of future price movement.
The important point here is that, in contrast to market-making, the source of profitability (or loss) is directional bets rather than price volatility.
Market Making Algorithms.
The M.M algorithm is an online decision process that can place buy and sell limit orders with some quoted limit
order prices at any time, and may also cancel these orders at any future time.
Market making algorithms are a restricted class of trading algorithms, though there is no formal specification of the restrictions. Intuitively, the restriction is that a market maker has to always be present in the market, and offer prices that are close to the asset price.
A trading algorithm is also considered as an online process. it makes its decisions about placing and canceling orders at time ‘t’ after observing the price. The algorithm may or may not have additional information about the price series.
The basic starting form of market-making algorithms can be considered as the following:
At time t,
the algorithm cancels all unexecuted orders,
and places new buy orders at prices Yt, Yt− 1, Yt − 2 . . . Yt – Ct,
and new sell orders at prices Xt, Xt +1, Xt+2…Xt+Ct,
where Yt < Xt and Ct is a non-negative integer.
These ladders of prices are for ensuring that large sudden fluctuations in price cause a proportionally large volume of executions. Ct stands for the depth of the price ladder at time t.
The overall positive impact of algorithmic Market Making can be summed up as mentioned below:
Here are some types of M.M Algorithms. you can find out more about their explanation by clicking on this link.
Mean Reversion Model, Ornstein-Uhlenbeck Processes Model, The Schwartz Model, etc.