Skillsfirst Level 5 Diploma in Financial Trading (RQF) - Module 1 - Trading Introduction
Skillsfirst Level 5 Diploma in Financial Trading (RQF) - Module 2 - Financial Products
Skillsfirst Level 5 Diploma in Financial Trading (RQF) - Module 3 - Economic Principles
1 of 2


Together with enabling market participants to physically trade much more effectively and easily themselves, electronic trading also facilitating 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).

Although global trading volumes are difficult to estimate, it was estimated that algorithmic trading accounted for roughly 50% of all trading on US equities markets – and these volumes are expected to continue to increase globally across all asset types and all exchanges. However, despite the almost exponential growth of automated trading volumes being experienced all over the world, algorithmic trading strategies can be broadly classified into 3 distinct categories:

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’.

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.

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:

Pure Arbitrage

Strategies designed to profit from pure market mispricing’s, almost instantaneously buying a certain security at a lower price and selling at a higher price (or vice versa).

Statistical Arbitrage

Strategies designed to buy and sell two or more different securities which are relatively mispriced. This is usually done with securities which have a close economic as well as statistical relationship with one another, such as government bonds of different maturities or stocks within the same country and sector.

Event Arbitrage

Sometimes referred to as Latency Arbitrage, these strategies seek to profit by reacting to certain information releases or economic data faster than other market participants. This is usually as a result of superior computer systems which are able to process information much more quickly, as well as faster electronic connections which enable trading firms to execute orders much faster. In conclusion, electronic trading has brought with it distinct advantages to trading professionals as well as unique challenges which will continue to evolve and change as time goes on. As a market participant yourself, it is imperative therefore to stay up-to-date with these market developments all the time – not only to ensure your survival in today’s highly competitive financial markets, but also to allow you to identify possible trading opportunities which secure your long-term trading success.

Scroll to Top