792 karma · joined June 21, 2023
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.
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.
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.
>The film follows a group of heroin addicts in an economically depressed area of Edinburgh and their passage through life
This song sounds like a disturbing uncanny-valley rendition of a slow Phoebe Bridges song performed by Taylor Swift using a broken auto tuner.
While I think it's technically impressive that this exists at all, I think this tune is still at the stage of "Pope in a puffer jacket".
They could have definitely spent 12-24 months building the platform diligently from naught, but they'd have the same end product, just 12 months too late. The demand could have been satisfied by any one of several players in the industry (Tiktok, bluesky, LinkedIn, Twitter itself, Snapchat, a resurrected MySpace, etc), so rushing to gain first-mover advantage was likely the singular consideration for the project.
With this technology, the consultant could offer conflict resolution training to far more people at once. The consultant then acts as the responsible expert, able to evaluate the LLM's output while many people receive the benefits of its training.
I don't see it as credible to say that China are currently investing $60bn/yr, or anything approaching that figure. They seem to currently be struggling to hit $10bn/yr.
The closest I can find to this figure is a Dept of Commerce report that estimates China gave $150bn in subsidies in total to its semiconductor industry in the period 2013-2023.
Do you mean that they give 60bn rmb per year?
If YouTube, Spotify, Apple, Tidal, Deezer, Soundcloud, and Amazon all adopt this practice, taking your edge-case artist, they're out of pocket for $3,500 per year.
That makes a situation where the more highly concentrated Spotify's monopoly is, and the less productive an artist is, the fairer the outcome for that small artist. Meanwhile the $3,500 is distributed between the monopolist, and the very large artists on the service. That's a quite uniquely perverse set of economic outcomes.
>Photobucket declined to identify its prospective buyers, citing commercial confidentiality.
>tech companies are also quietly paying for content locked behind paywalls and login screens, giving rise to a hidden trade in everything from chat logs to long forgotten personal photos from faded social media apps
In this market, ethics seem to exist when it comes to corporate clients, but not when it comes to end-users.
It's immediately and self-evidently obvious that no end-user in 2007 consented to photos of their 2007 era teenage self being used to train an AI how to identify an emo kid.
>[pseudonym], an expert analyst, technology director, commander of an elite intelligence unit, and winner of the prestigious Israel Defense Prize for his artificial intelligence based anti-terrorism project
The defense prize projects & unit conducting the projects are published in The Times of Israel. The person's rank & name is publicly known from other historic news articles. With that context, the google account and Amazon weren't really important to linking the General to the unit in question.
Or a paying client of GitHub's, venting their frustration that a business critical service is frequently encountering service outages.
For example, the number of people who die from TB annually is way in excess of 1 million, with 10million+ falling ill with the disease. This is a disease for which we have the cure - and have had the cure for 80 years. TB could be ended within 6 years with a $250bn commitment.
While these millions upon millions are dying, a couple of thousand billionaires donate miserly single-digit-percentages of their wealth per year, and complain that they can't find a philanthropic outlet, while reaping the publicity benefits of saying they'll give away 50% "eventually, maybe before they die".
Outlets for this wealth exist, and it's not as if it's particularly challenging to pick one "save literally tens of millions of people" project over another "save literally tens of millions of people" project.
A former employee tweeted [1] shortly after that "Having worked at Tesla, I can say with some confidence that the design engineers are hearing about this requirement for the first time here".
[1] https://twitter.com/Superfast/status/1575591147828744192
I'm not a python user, but in most languages, libraries are referenced in (what most devs would consider) boilerplate code. Purely conjecture, but perhaps without boilerplate code, the LLMs are left guessing the names of popular libraries and just merges together two common naming conventions "huggingface" and "-cli".
To a large extent, it's still dogmatic and prescriptivist, but unorthodox opinions (not just limited to behavioral economics) are more accepted & considered following Kahneman's input.
From what I've tested, all of the current models will see a prompt like "are you sure that's correct" and respond "no, I was incorrect [here's some other answer]", irrespective of the accuracy of the original statement.
There's 13bn leaked accounts on the site, and although Hunt does appear to run the site entirely selflessly with little/no profit motive, there is at least some commercialisation of the accounts listed bringing in revenues to cover its costs.
It's free for us because somewhere in the chain, someone is paying for data about us - even if their use-case isn't nefarious.
Buffet could lose 99% of his net worth, and still be one of the top 5,000 or so wealthiest people in history. He could then lose 99% of that wealth, and still be comfortably inside of the top 1% of wealth holders. He could invest that 1% of 1% of his money in a broad index, and comfortably live off the hundreds of thousands of dollars in annual returns.
The mental model he has of the market is completely different to someone who is putting 1/5th of their $50k life-savings into investments. His appetite for risk and loss are entirely detached from most investors, and even many investment firms. Similarly, the range of opportunities open to Berkshire Hathaway is considerably different to the range of options available to a typical investor.
Zooming in to 125% the effect goes away, and the font-weight at the top and bottom appear equally thick.
The Firth of Forth is visible with the naked eye from the ISS though. So picking a resolution that misses that geological feature and making an estimate for crossing the Forth that's out by an order of magnitude would be transparently and self-evidently incorrect... Particularly if you and your team are on the bank of the Forth when you make the estimate.
Picking an exact resolution is challenging, but picking a "good enough" resolution that minimises "out by an order of magnitude" errors really isn't for most tasks unless you're taking part in the most cutting edge of research.