bormaj

This is a really exciting development. Can anyone currently using this chime in on working with pyodide/dependency management in this setting?

I imagine that this reduces the iteration time for developing excel integrations. It's unfortunate that direct db queries aren't supported, but I guess that's a wasm/pyodide issue.

One of the unique aspects of dark pools (and this can vary by venue) is that orders are segmented according to the source type (e.g. retail, client of the operator of the venue, institutional trader, etc) and the quality/grading of their order flow. As an institutional trader trying to leg into/out of a large position, you'll want many different execution options to help minimize price impact + information leakage + execution time. Dark pools are a great option in which you may have the option to specifically trade against non-toxic order flow (e.g. retail) to achieve better execution.

There are other reasons as well, but these venues essentially exist to solve some very niche problems for institutional trading. Public filings are available for review in case you're interested in the rules of each dark pool. [0]

[0](https://www.sec.gov/about/divisions-offices/division-trading...)

HFTs/market makers are competing for pennies on the dollar. They do not hold risk (long term), they exist to readily provide liquidity to your buy/sell orders. HFTs can be quite profitable, but that doesn't make them inherently evil.

Can you elaborate why those bans will improve the market and what the issues are with HFTs in your eyes?

Any specific pitfalls to avoid with K8s? I've used it to some degree of success in a production environment, but I keep deployments relatively simple.

As someone else in the industry, is it fair to categorize all HFs this way?

I think it's fair to say that the context in which a work was created adds to the novelty and ingenuity of it's existence. These works don't exist in a vacuum and there's certainly a difference between a symphony created by Beethoven in his time/setting and a symphony produced as some model's output.

Sure they may functionally have the same effect or enjoyment, but appreciation of a fine work goes deeper than its function.

> And to be clear, nobody learned the lesson.

This is not true. The mortgage lending pipeline is quite different today compared to pre-GFC. There is considerably more due diligence required by lenders and banks in order to back loans. Conventional loans backed by the GSEs these days have a much higher quality control. If the originating lender lied to push the loan through or didn't due diligence, they'd be on the hook for paying the defaulted principal.

> The Trump administration is going to defang CFPB and probably bring Fannie and Freddie out of conservatorship.

I'm not aware of any chatter on the former and the latter is becoming discussed quite frequently. Though I'm not sure the GSEs are interested in a GFC 2.0

> Another mortgage meltdown is a predictable outcome of this and I would expect it around 2032.

These days I would be more concerned about private credit than the mortgage market...

The buyer of that pool of loans will be an institutional investor with an allocation for that kind of risk. Depending on the state of the market, the pool might be sold at a discount or a premium which may attract/deter certain investors.

Separately, pooling loans generally makes the aggregate product less sensitive to default risk because you're talking about many loans instead of just one.

Any reading recommendations for exploring this further?

Anyone selling the retail investor an "edge" via ML platforms or AI is selling snake oil. Sure the barrier to entry is low, but profits are never guaranteed.

> Final note, inflation helps encourage people to use their money and keep the economy moving.

That also means that costs are increasing, which may have the opposite effect

I think the parent comment here is referring to the quality of education relative to the immigrants' countries of origin.

There is an argument that elections can be understood as a referendum on the previous 4 years. E.g. voting for the incumbent candidate/party means more of the same.

That VP comp number seems quite low fwiw

The P is silent

Convicted felons cannot legally run for office

To add to openrisk's comment, classical statistics doesn't formally define or attempt to tackle causality. Regressions and the like only describe associations between variables. For a statement regarding causality to hold, you need stronger evidence than just associativity.

Pearl has published a number of primers/papers/books with instructive examples that outline the limitations of classical statistics and applications of casual diagrams/graphs.

Emphasis on _advertising in its current form_, I think it's a valuable means to be able to a). monetize something and b). to spread awareness. But I agree with GP that as a society we're allowing companies to grossly over-engineer our lives around ads.

I think it's reasonable to carryover retail investor protections to the gambling world. One market has much more history in taking advantage of the average Joe and as a result there are many sensible protections in place. If you can't withstand losing your entire investment, you probably shouldn't be able to place that bet in the first place.

Unfortunately, since gambling is only recently more accessible/prevalent, I think it's going to take a few mishaps to produce similar regulations.

Are there any attempts to address this at the package management level (not a cargo-specific question)? My first thought is that the package could declare in its config file the "scope" of access that it needs, but even then I'm sure this could be abused or has limitations.

Seems like awareness about this threat vector is becoming more widespread, but I don't hear much discuss trickling through the grapevine re: solutions.

Can't read the article because of the paywall, so this may/not be related...

Is it fair to say that the real liability here is a dataset mapping protein/molecule structures to outcomes/effects? Hypothetically the govt could always require OpenAI to blur responses with malicious intent. But if the underlying corpus is available, what's stopping a bad actor from training another model to do the same thing?

I guess the question I'm asking here is what risk is unique to their model if not the data it was trained on?

> People use python because everybody else uses python. That's it. It's not particularly good at anything it does. But it will get the job done and I can do it. But that just isn't good enough for me. It's the visual basic for data science. And that's not a compliment. Being idiot proof is it's main feature. But that doesn't make it the smart choice.

I'll leave this here as well, I think it sufficiently implies the notion of Python being a fad and not particularly useful.

I have no qualms with the OPs comment other than the same criticisms I highlighted could be applied to just about any other language in a similarly vague context. So what justice do those criticisms do if we're not being specific about them?

For example > Package management is a disaster > The interpreter is slow > The syntax is not expressive

Is your particular experience with pip bad? Or is it poetry/conda or another upstart project? Are you working with a monorepo? In what use case is the interpreter slow? The syntax is not expressive (for what)?

My point about tooling/utility is that how you use a tool matters a lot (and maybe I didn't express that in my original reply).

> The interpreter is not that fast, the language is not that expressive, what passes for package management is a bad joke, etc. I can work with it but I'm not necessarily loving it.

These are rather disingenuous criticisms of python. The utility of any language is measured by its use as a means to some end. It's clear that Python's ecosystem has prospered not just because it's a fad, but because it's actually useful. Not perfect, but useful.

Python can be improved, but I'm sure most other tools/languages can be equally criticized.

They may have been referring to (for example) reported financial results or news events which are more infrequent/rare but may have outsized impact on market prices.

Reading through Betterment's disclosure acknowledges the scenarios for potential loss. While the deposits are stored through their program banks, you're guaranteed up to $2mm in FDIC insurance. So if those banks go under, your money is as safe as it would be anywhere else.

What I did not know is that FDIC insurance doesn't apply while money is being _transferred_ between accounts (SIPC insurance apparently applies here).

Are you a professional in the field or is this your side project?

The quantitative trading posts on here typically just scratch the surface, but I have to say that I'm impressed with this one. Thanks for sharing!

Isn't there a query option to disable/configure log writes for cases like this?

Humility has to go both ways then, we can't claim that LLM models are actually (or not actually) AI without qualifying that term first.

As someone who started learning to code with C++ followed by Python and then Rust, proper threading approaches weren't drilled into my head until I started working with Rust. I agree with you that threading with message passing is a safer approach. Threading does add a level of complexity that isn't always necessary.

AFAIK it's not outlined in a PEP, but my intuition is that Python was designed to be accessible and "simple". It wasn't built to be a systems programming language. So for all its faults with the GIL I don't think it should be a major point of contention. For any task it's always about choosing the right tool for the job.

There is considerable effort at the moment to remove the GIL in future versions and implement better threading support. At 3.11/3.12, it has come a long way in terms of performance.