HFT gives securities 'false liquidity' in the sense that large numbers of trades, performed over a short period, would mimic an increase in market demand and achieve no significant increase in mobility. Remember from What Is Liquidity Risk, that liquidity describes how easily a security can be bought and then sold back on the market at a profit to the seller. High frequency trading uses computers to buy or sell large pools of securities in fractions of a second, which gives the traded asset the appearance of high liquidity. But this 'liquidity' isn't real, because the net change in volume between the purchase and sale are too close to zero. It's as if you were to go into the grocery store, buy 10 apples paying no tax, then return them and be compensated the tax by accident. In the end, you returned the exact number of apples you originally bought bearing no weight on the overall marketability of the apples.
It's this parity that makes share volume a less useful metric. Looking back at What Is High Frequency Trading, these traders end their day with no net investment positions, meaning that they put back what they take out at the end of every trading day. Share volume is useful to see how many times a particular security is bought and sold, ideally to find a variance between the number of buyers/sellers and forecast where that security is headed. HFT heavy markets are full of transactions that have a 1:1 ratio, resulting in much less variance, because the number of sales by each investor would counterbalance their purchases.
How Could We Regulate HFT?
Based on past issues with computerized trading, any regulations created for this system would need the following elements:
- Regulatory agencies would need to establish uniform standards, to be used between each body, for what types of trading activities qualify as "high-speed" or "high frequency". There also would need to be definitions qualifying traders and investors as "high frequency traders" and for types of computer software that perform these trades
- A comprehensive list of algorithms and software used for "high frequency trading", which would update as the market for it continues to evolve, would be needed
- Regulators would be required to have an exhaustive list of firms that self-identify as "high frequency" or "high speed" institutions, and to use the above standards to qualify other financial institutions who participate in this type of trading.
- There needs to be a way for authorities to verify that firms using HFT systems have a fast, effective way of shutting down, or disabling their software in the event that the programs act unexpectedly or out of sync with the firms trading agenda that day.
- Also needed is a verification method to ensure that one firm's computer can recognize erratic market behavior and stop its own trading to offset the "hot potato" effect seen in the Flash Crash.
Having uniform defitions for HFT would allow the various regulatory agencies involved to approach the issue from the same direction, moving in cohesion and creating rules that make sense across exchanges. Collecting data on the firms and the software they use makes it easier to regulate having a smaller footprint on the markets as whole. Regulators need to make rules, but the rules also need to be specifically tailored to the issue and have as little spill over as possible.