Goldman Sachs is spending $100M to shave milliseconds off stock trades
Markets around the world are determining prices on a massive variety of instruments that derive value from the current and future value of products such as currencies, interest rates, equities, grains, livestock, metals, oil, gasoline, natural gas, and electricity.  These prices allow us to prioritize resources, make fair transactions, and manage risk (i.e. buy insurance on the value of critical products so that we can plan and invest more effectively).  The value of all these instruments are related to one another, as well as to realtime world events, in complex ways that no one entity has a perfect view of.  Consequently, markets work by polling the expertise of many different parties who all understand a piece of how things should be valued.  This results in millions, if not billions, of interconnected price-discovery feedback loops.  The markets are kind of like a massive, distributed, realtime, ensemble, recursive predictor that performs much better than any one of its individual component algorithms could. The reason why shaving a few milliseconds (or even microseconds) can be beneficial is because the price discovery feedback loops get faster, which allows the system to determine a giant pricing vector that is more self-consistent, stable, and beneficial to the economy.  It&#x27;s similar to how increasing the sample rate of a feedback control system improves performance and stability.  Providers of such benefits to the markets get rewarded through profit.