Skillsfirst Level 3 Certificate in Introduction to Financial Trading (RQF) - UNIT 1: Principles of financial trading
Skillsfirst Level 3 Certificate in Introduction to Financial Trading (RQF) - UNIT 2: Principles of Financial Planning and Cash Flow in Financial Trading
Skillsfirst Level 3 Certificate in Introduction to Financial Trading (RQF) - UNIT 3: Understanding financial trading techniques


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.


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:

  1. Pure Arbitrage – Strategies designed to profit from pure market mispricings, almost instantaneously buying a certain security at a lower price and selling at a higher price (or vice versa).
  2. 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.
  3. 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.
  4. Arbitrage – This type of investment is used by investors who expect their potential returns to be a result of many different factors as opposed to purely market risk.
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