Quite the opposite, thanks to the tough competition the market makers are setting the bid/asks spreads as minimal as possible. Which leads to less costs for human investors, pension funds, insurance companies etc.
I used to be a market maker in the 90's before HFT took off. The margins we kept sometimes felt like a rip off but customers had no other choice but to accept them.
People who ask for transaction fees, forced delays in executing or whatever, tend to forget that these force market makers to increase their spreads, which means customers eventually pay the price.
It's not automatically the case that the disappeared margins & thinning of bid/asks have been shared equitably between the trading firms and customers.
Take two exaggerated markets for example:
1) No HFTs: The customer wants 100 shares in Company A. The shares are available on two exchanges, one at $100, and another at $105. A market maker charges the customer $5 to access the 100 shares at $1 each. The customer pays $105. The market maker earns $5.
2) With HFTs: The customer wants 100 shares in Company A. The shares are available on two exchanges, one at $100, and another at $105. The customer clicks "buy" on their trading platform, the HFT races to the $100 shares, and purchases them, then fulfills the order at $105. The customer pays $105. The HFT firm earns $5.
For the end-customer, all that's happened is the margin goes to another firm. The consumer still has no other choice but to accept these transaction fees. There was arguably a need for HFTs to reduce the market-makers exorbitant fees in the 2000's, but that requirement has been served, and the technology now exists to remove both from the market entirely.
HFTs are a rent-seeking entity interjecting in a market which, at least in theory, exists to most efficiently allocate capital to the productive benefit of all.
How the price improvement gets allocated is complicated. Some of the price improvement goes to the broker (in the form a payment-for-order-flow) and some goes to the actual investor (you). But in either case the retail investors are strictly better off.
The UK's Financial Conduct Authority:
>We use stock exchange message data to quantify the negative aspect of high-frequency trading, known as “latency arbitrage.” The key difference between message data and widely-familiar limit order book data is that message data contain attempts to trade or cancel that fail. This allows the researcher to observe both winners and losers in a race, whereas in limit order book data you cannot see the losers, so you cannot directly see the races. We find that latency-arbitrage races are very frequent (one per minute for FTSE 100 stocks), extremely fast (the modal race lasts 5-10 millionths of a second), and account for a large portion of overall trading volume (about 20%). Race participation is concentrated, with the top-3 firms accounting for over half of all race wins and losses. Our main estimates suggest that eliminating latency arbitrage would reduce the cost of trading by 17% and that the total sums at stake are on the order of $5 billion annually in global equity markets
https://www.fca.org.uk/publication/occasional-papers/occasio...
The University of Michigan's Economics department:
>We illustrate this process and the potential for latency arbitrage in Figure 1. Given order information from exchanges, the SIP takes some finite time, say δ milliseconds, to compute and disseminate the NBBO. A computationally advantaged trader who can process the order stream in less than δ milliseconds can simply out-compute the SIP to derive NBBO,a projection of the future NBBO that will be seen by the public. By anticipating future NBBO, an HFT algorithm can capitalize on cross-market disparities before they are reflected in the public price quote, in effect jumping ahead of incoming orders to pocket a small but sure profit. Naturally this precipitates an arms race, as an even faster trader can calculate an NBBO* to see the future of NBBO, and so on.
http://strategicreasoning.org/wp-content/uploads/2013/02/ec3...
The Bank for International Settlements:
>Conservative estimates suggest that at least 4% of dark trading occurs at stale reference prices. High-frequency trading firms (HFTs) almost always benefit from such stale prices, being on the profitable side of the trades between 96 and 99% of the time. Furthermore, stale trading does not happen at random but is driven by the behaviour of HFTs. HFTs as a group almost never provide marketable liquidity in the dark and rather behave strategically to exploit their speed advantage by submitting marketable orders to execute against stale quotes.
The specific strategy currently employed by HFTs is somewhat immaterial in the broader context of a discussion about front-running. For as long as a firm can legally front-run the market with any strategy, it can undermine the market and risklessly extract profits.
I don't think the reason has anything to do with price discovery, it's just because exchanges want to maximise their trading fees. Continuous order book trading leads to more trades and hence more profit for the exchange.
I think it’s pretty uncommon to do them every N seconds.
A common pattern is to collect quotes before the market open, do an “opening auction” to set the opening price, and then switch to continuous trading for the rest of the day. If trading in a stock ever pauses (which can happen for a variety of reasons) then another auction occurs when trading is restarted.
Bids and offers are collected for auctions that happen at regular known intervals, for example every 15min.
IMO, if you have a problem with limiting it to 5 seconds long quanta, you are doing something wrong.
If you want to kill HFT you can do it directly via very very small transaction fees. But guess how popular that is...
You mean you can never completely eliminate the advantage? But mostly eliminating it might still be useful?
Suppose the rule is that if you get your request in by 01:23:45 then it gets handled in the following 5-second period and the response is sent out at 01:23:50. Does someone (A) who finalises their request at 01:23:44.9999 and gets the result back at 01:23:50.0001 have an advantage over someone else (B) who has to finalise their request by 01:23:44.8 and gets their result back at 01:23:50.2? Yes, certainly, but it doesn't seem to be much of an advantage ... So person A can take account of exciting news that arrives at 01:23:44.9, while person B can't, true, but when it comes to reacting to other trades, person A has 4.9998 seconds to think about the news, while person B has 4.6 seconds to think about it, which doesn't seem like a huge difference. Compared to how things work today.
A per-message would probably significantly affect existing strategies and greatly increase spreads, but I don't think it would prevent all forms of ULL trading.
[1] But even there exchanges offer rebates, if not outright incentives, for market makers to provide liquidity.
You could match what you can distributed equally and leave the rest unsettled.
You could let people decide whether to roll-over the partial bid into a new bid on the next clock or to cancel unsettled.
You could clock to something both very fast on a human scale (50ms), quick enough it'd still feel instant but slow enough that it could reduce HFT silliness and need for extreme low latencies.
Equally per market participant? Do large participant like banks trade same amount as retail investor one trade at a time? Per quantity? HFT will time the end of the interval and decide to place a large order or not.
I'm not sure I understand the problem with "waiting" for the end of the clock. The pool wouldn't be public so you couldn't get knowledge inspecting the pool. All bids and offers would be published on the clock and settled by weighing all the bids and offers against each other and matching by volume.
The trickier issue is what happens in this scenario (assuming limit orders):
Person A bids for 500 units @62
Person B offers 100 units @61 Person C offers 400 units @60
Clearly there needs to be full settlement, we have a bidder who wants to buy 500 units at a price which sellers are happy to sell at.
Correct me if I'm wrong, but in a traditional market it would depend on the order they came in.
Here we would need a formula to work out the correct settlement price. Intuitively this ought to be somewhere just above 61. ( If it were just two people, a bid at 62 and an offer at 60, you could intuit a fair settlement would be 61. )
I'm sure fair formulae can be derived however.
I guess it is possible that there are remaining marketable orders that never fill because of an imbalance one way or the other, but I doubt that ever happens in practice.