Together with enabling market participants to physically trade much more effectively and easily themselves, electronic trading also facilitates the rise of a completely new type of trading – namely, algorithmic trading. Sometimes referred to as automated or ‘black box’ trading, algorithmic trading sees modern computer systems taking over the actual trading process itself to do everything from transact a client much more efficiently to profiting from market inefficiencies within a matter of microseconds, a practice known as High-Frequency Trading (HFT).
Algorithmic trading strategies can be broadly classified into 3 distinct categories:
Market Making:
In a majority of cases, the major algorithmic trading companies currently operating engage in market-making – essentially, implementing computer systems which ensure market liquidity by providing continuous bid and offer prices, the purpose of which is to profit from the difference between the price at which they buy a certain security and the price at which they sell. This is known as ‘Scalping’ or ‘Trading the Spread’.
Order Execution:
With increased levels of price and market transparency than ever before, it can often be highly difficult for market participants to buy or sell large amounts of securities without adversely impacting the price as other traders seek to profit from this information. This is known as Slippage, and has given rise to a vast range of so-called execution algorithms which seek to process these large orders quickly, easily, and with minimal slippage.
Arbitrage:
With electronic trading enabling greater access to more markets around the world than ever before, market participants have a much larger arena within which to identify and profit from market mispricing’s and other inefficiencies. The arbitrage algorithms developed to take advantage of these opportunities can be classified into 3 types: