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Re:Lessons learned building an ML trading system by criddell on Wednesday November 27, 2019 @05:27PM (#21652783)
What's the value of HFT? If exchanges were required to add a random delay to very trade to work against high frequency traders, would anything of value be lost?
Re:Lessons learned building an ML trading system by jstanley on Wednesday November 27, 2019 @05:54PM (#21652978)
If exchanges added a random delay, that would mean traders have to plan for a longer time horizon, which means they need to offer more conservative prices. That means when you're selling, you get less money, and when you're buying, you get less stuff.

Some people have this notion that if their trade got matched against a HFT that they have somehow lost out. The exact opposite is true. If the party on the other side of your trade was a HFT, then that implies that all other parties were offering worse prices than the HFT was. If the HFT had not been there, you would have got a worse price (whether on the buy side or the sell side). The presence of high-frequency traders (or any traders, for that matter) reduces spreads and increases liquidity.

The only people who get worse deals as a result of high-frequency trading are people who would sell you the same stuff for more money.

Re:Lessons learned building an ML trading system by roenxi on Wednesday November 27, 2019 @06:55PM (#21653390)
Hang on, that is conflating separate ideas.

The substance of your post is describing price discovery - price discovery isn't the issue here. The issue is that the price discovery is being done in milliseconds.

The substance of the complaint is the speed of the auction that discovers the price. The faster price discovery is being done, the fewer traders can participate. If a few milliseconds can change the value of a financial instrument then we have to accept that waiting a second or two will allow a lot more traders to reevaluate and offer a fair price.

The HF in HFT looks like a play to reduce the number of traders who can act on information, which means the buyer/seller is probably getting scalped. HFT traders are making money arbitraging the speed of information dissemination, which indicates that other traders would offer different (/better) prices if the market waited a half-second or so to let everyone gather all the relevant data.

Re:Lessons learned building an ML trading system by growse on Wednesday November 27, 2019 @07:06PM (#21653465)
> The substance of the complaint is the speed of the auction that discovers the price. The faster price discovery is being done, the fewer traders can participate.

The faster the price discovery, the shorter the validity time. This means a more accurate price.

> If a few milliseconds can change the value of a financial instrument then we have to accept that waiting a second or two will allow a lot more traders to reevaluate and offer a fair price.

You're making the mistake of assuming the price is static. If I have to quote you a price on an instrument that's valid for the next 5s, I have to be more conservative than if I'm quoting for the next 5ms. Which means you get a worse price.

> The HF in HFT looks like a play to reduce the number of traders who can act on information, which means the buyer/seller is probably getting scalped. HFT traders are making money arbitraging the speed of information dissemination, which indicates that other traders would offer different (/better) prices if the market waited a half-second or so to let everyone gather all the relevant data.

There's literally nothing stopping or limiting the numbers of players operating at this speed. What the race actually results in is all market participants getting smaller spreads and better prices.

Re:Lessons learned building an ML trading system by perl4ever on Wednesday November 27, 2019 @07:29PM (#21653639)
"The faster the price discovery, the shorter the validity time. This means a more accurate price."

A continuous market price is an illusion; let's not forget that. Every market is made up of trades, which are discrete, and every price has an unstated amount of uncertainty, which may be large by any standards. You can't know from first principles whether a change in quoted price is even a change in the market, because it could be within the +/- range that's implicit. Apple is quoted to the nearest penny, at least, but the idea that the current price is accurate to within 0.004% is ridiculous.

Edit:

"Fischer Black famously defined an efficient market as “one in which price is within a factor of 2 of value, i.e., the price is more than half of value and less than twice value,”

...I hadn't heard this before Matt Levine mentioned it, but I was like "yeah, obviously, why haven't most people gotten the message?"

But: "BNP Paribas...said [Saudi] Aramco was worth exactly $1.424394 trillion."

I wonder which particular millisecond that held for.

Edit Edit: The market has a whole (mostly) unseen dimension other than uncertainty, which is depth. You can only buy or sell so many shares at the instantaneous market price. Further away, there may be orders, but the price of the whole company is going to be way outside of that. The shorter the timescale, the shallower the "market" so you can't just say we're making progress by doing things faster. It's like when research lasers are said to make unbelievable power, but it's like for a femtosecond or something. Liquidity, in my mind, requires depth, just as with water.

Re:Lessons learned building an ML trading system by Akababa on Wednesday November 27, 2019 @09:55PM (#21654266)
I don't believe liquidity necessarily has anything to do with efficiency, but more liquidity can never hurt. Even if the price of every stock right now is 100x what it should be, I still want lower spreads.

And to address your concerns about depth, I believe that's where market makers (which are related to HFT) come in.

Re:Lessons learned building an ML trading system by perl4ever on Friday November 29, 2019 @06:30PM (#21667421)
Everything is about costs and benefits. It doesn't make sense to say "I want an improvement in X, no matter how small" without regard to cost, because as X becomes tiny, a very small cost could mean a net loss to society, and multiplied by lots of people, is a large loss.

Look at gas stations. If people are spending $1 driving around to save $0.10, then that's not good and at least public policy shouldn't encourage it.

Re:Lessons learned building an ML trading system by Akababa on Wednesday November 27, 2019 @10:01PM (#21654296)
> If a few milliseconds can change the value of a financial instrument then we have to accept that waiting a second or two will allow a lot more traders to reevaluate and offer a fair price.

I'm not quite getting this point. If I have a sell order at price x and it's filled by a HFT 1 second before someone with a slower algorithm, how does that result in a more "fair" price for me? If the HFT instead posts a buy order at an unfair price x-1, there's nothing stopping the slower traders from taking my sell order at x one second later.

Re:Lessons learned building an ML trading system by roenxi on Thursday November 28, 2019 @02:00AM (#21655182)
That would be totally boring trading and unremarkable, but that isn't what HFT firms are doing. If that were the strategy then exchanges would presumably just sell a skip-the-queue service when two traders offer the same price and there wouldn't be much point worrying about how far machines are from the exchange.

HFT trading isn't about executing the same trade as someone else but a tiny margin faster. That wouldn't have any special impact on market spreads or liquidity, for example.

There aren't any complaints against the T in HFT; as traders they are helpful. The value questions are about the HF and whether it is a desirable part of the market or an unhelpful arbitrage opportunity created only by implementation details of the exchange.

Re:Lessons learned building an ML trading system by traK6Dcm on Wednesday November 27, 2019 @05:57PM (#21653009)
Many HFT systems provide liquidity. If there is no liquidity, retail investors like you or me cannot buy or sell.

Just imagine you want to exchange a currency because you go traveling and the exchange tells you "Sorry, nothing available right now, gotta come back in a few weeks". That's what would happen if there is no liquidity.

Re:Lessons learned building an ML trading system by akra on Wednesday November 27, 2019 @06:52PM (#21653368)
I always had questions about the liquidity on offer though seeing participants flee the market in black swan events. HFT liquidity could be illusionary - its only there when its not quite required similar to how the bank "only offers you a loan when you don't need one". Of course this is exactly the point when liquidity is required; normally there's sufficient liquidity in normal times from market participants. Its easy to offer liquidity in normal times; harder to do so when no one else wants to offer it.
Re:Lessons learned building an ML trading system by wellactually on Wednesday November 27, 2019 @08:51PM (#21654015)
Offering liquidity is not equivalent to offering free money. The offer comes at a cost.
Re:Lessons learned building an ML trading system by kortilla on Thursday November 28, 2019 @01:14AM (#21654998)
> normally there's sufficient liquidity in normal times from market participants.

Not really. The spreads were terrible before HFT market making.

Re:Lessons learned building an ML trading system by roenxi on Wednesday November 27, 2019 @06:38PM (#21653275)
It isn't obvious that the retail investors are that excited by sub-second liquidity.

Speaking personally, I'd even be happy to wait several seconds to see if someone else is willing to pay a better price.

Re:Lessons learned building an ML trading system by vecter on Wednesday November 27, 2019 @06:48PM (#21653347)
That's not how things work. You would see much less demand/supply for a particular stock at every price level, which means you'd pay much more to buy less and would have to pay much more to sell less also. There are no upsides to having fewer market makers.
Re:Lessons learned building an ML trading system by roenxi on Wednesday November 27, 2019 @06:57PM (#21653407)
> you would see much less demand/supply

Why? If the HFT firm was willing to offer me $X 2 milliseconds ago they are probably still willing to offer $X now. It isn't like there has been time for anything to change; there are going to be short periods of time where there is literally no new information.

And they are just as likely to be offering me more now than less as conditions change.

Re:Lessons learned building an ML trading system by gpderetta on Thursday November 28, 2019 @08:15AM (#21657053)
if they weren't able to move their price 2 milliseconds later, they wouldn't offer $X in the first place.
Re:Lessons learned building an ML trading system by perl4ever on Wednesday November 27, 2019 @07:35PM (#21653672)
We obviously can have liquidity on in-between timescales, because we had it before modern HFT trading, right?

The average person may be overly paranoid about HFT, but it doesn't make sense to say they benefit from it, because they are not going to be in a position where they benefit from an execution in a fraction of a second.

Price improvement of fractions of a penny has gotten silly too. It's easy to think of it as more significant than it is, until you figure it as a percentage (or the spread for that matter).

It's kind of like how ultra-sensitive people are to gas prices...

Re:Lessons learned building an ML trading system by growse on Thursday November 28, 2019 @04:13AM (#21655733)
Before HFT, we had enormous spreads and expensive trades on many instruments in many markets.

Smaller spreads lower costs for everyone: institutional, retail etc.

Re:Lessons learned building an ML trading system by perl4ever on Thursday November 28, 2019 @09:31PM (#21661549)
When exactly are you thinking of? Are you old enough to remember before decimalization? Do you consider that "enormous"?
Re:Lessons learned building an ML trading system by 1e-9 on Wednesday November 27, 2019 @07:00PM (#21653427)
Yes, adding delay generally lowers the economic value of markets. In addition to improving liquidity, as mentioned by others here, HFT also improves the relative pricing of related instruments. There is an enormous number of financial instruments traded for the purpose of prioritizing resources, transforming assets, and offsetting risk. Equities and cryptocurrencies are a small part of this connected financial universe. There are many trading entities with unique information and/or understanding about different parts of this constantly changing universe of prices. None of them has a complete view, but by communicating with each other through trading, their expertise is pooled. HFT speeds this communication network, which improves the dynamic consensus.
Re:Lessons learned building an ML trading system by downerending on Wednesday November 27, 2019 @06:05PM (#21653063)
As sibling said, it's liquidity. Worked at an HFT for a while, and they once got in a snit with an exchange over some policy change. They turned off their trading there one morning, and within 20 minutes, the exchange was on the phone begging them to come back.
Re:Lessons learned building an ML trading system by rb808 on Wednesday November 27, 2019 @07:45PM (#21653724)
The liquidity from bots has replaced the human brokers. Sell side stock trader is a job that mostly no longer exists Eg https://www.bloomberg.com/news/articles/2018-04-30/goldman-t...
Re:Lessons learned building an ML trading system by musicale on Wednesday November 27, 2019 @07:40PM (#21653698)
Not really. The real-world value of Google (or any other company) doesn't change meaningfully on a millisecond basis.
Re:Lessons learned building an ML trading system by munk-a on Wednesday November 27, 2019 @07:17PM (#21653559)
Liquidity, which honestly has very little value to a traditional stock market. HFT and day trading both just exist as rent seeking behaviors on company valuation growth.