Latency arbitrageurs outperform efficient markets. To explain this, we describe the flow of new price-sensitive information into financial markets using three steps.

Liquidity providers also outperform an efficient market, as described before. So do arbitrageurs, if there is a cost to price-sensitive information, see here.

If price-sensitive information is either freely available or all market agents pay for the information, the market should reflect new price-sensitive information, without any transactions being concluded. When new relevant information arrives, market agents will simultaneously and instantaneously adjust their bid or offer prices to the new fair value. However, the assumption that market participants can act synchronously on the arrival of new information is unrealistic.

For the purpose of the explanation here we describe the flow of new price-sensitive information into financial markets with the following three steps:

  1. New information flows from the information source to the market agents;
  2. The market agents use the information to determine a new fair value;
  3. The agents trade or adjust their bid or offer prices on the securities exchange to reflect the new fair value.

The latency arbitrageur who is the quickest in executing these three successive steps will outperform competitors. The race is won by those who are closest to the source of information and are able to calculate the new fair value the quickest and are closest to the securities exchange.

High-frequency traders are real world examples of market participants who engage in this race. Michael Lewis gives a fascinating and entertaining overview of high-frequency traders in his book “Flash Boys: A Wall Street Revolution”.

At any moment there can only be one agent who wins this fastest-to-market race. More importantly, at this instant, only the winner of this competition will outperform the market as he will execute on all bids and offers that are favourable to him until all other agents have discovered and acted on the new fair value. The market participants that are slowest in the race to execute the above three steps will lose the most to the winner.

Competing firms will expend resources to win, and the winner could change from instant to instant. The total combined amount latency arbitrageurs would spend to win this competition would be determined by the amount of outperformance that can be achieved by being a winner. As discussed earlier this would, for example, depend on the magnitude by which new information changes the fair value of an asset.  

To be the best, latency arbitrageurs have to strive continuously to improve their speed. Typically, only a few players would be able to compete in such a scenario. It would be challenging for new entrants to join in, since a significant initial investment is required, without knowing whether it will lead to any success. It is even possible to envisage a winner takes all situation, as the winner will have the means to improve its resources continuously.

This hypothetical scenario is very similar to what is happening in real life where a few high-frequency trading firms do make huge profits. Refer to the paper “Risk and Return in High-Frequency Trading” by Baron et al. (2016).