Dividend derivatives have been a thing for quite a while. When Covid lockdowns started in 2020, EU mandated that EU banks are not allowed to pay dividends and Société Générale took quite a hit: "SocGen said it lost about 200 million euros on products related to the cancellation of dividend payments in the trading business." [1]
I was wondering about Trabucco as well. His name is nowhere to be seen, but he was leading Alameda together with Caroline up until last summer.
If SBF is also going for plea bargain, will various government institutions ask from him to get some dirt on Tether (and on Binance)? Might be that they are more interested in campaign financing.
> he was leading Alameda together with Caroline up until last summer
In the last paragraph on page 3 of the plea letter, we see that most of the counts cover the period from 2019-2022 (2020 for the money laundering). Thus, the crimes that Ellison is pleading guilty to were going on while Trabucco was the co-CEO.
According to Wikipedia, he "officially became the co-CEO in October 2021", and resigned in August 2022.[1]
> but he was leading Alameda together with Caroline up until last summer.
According to the SEC civil lawsuit against SBF, SBF was running Alameda the whole time, including when Ellison and Trabucco were nominally the co-CEOs. The CFTC lawsuit against SBF, FTX, Aand Alameda asserts the same, and that SBFs resignation as CEO of Alameda was done to create the false image of strong separation between Alameda and FTX.
Ellison apparently had a real role in the fraud, but I don’t know that it’s clear that Trabucco was anything other than a face set up as a distraction, in terms of substantive role.
I don't think SBF is going to be given the chance to plea down-- that's the whole point of getting Ellison and Wang to cooperated, to construct an ironclad case against SBF so that they don't need him to cooperate in any way, and can still likely convict him of enough crimes to put him in prison for 30+ years.
An important component of accepting a plea bargain is telling the truth. I was also wondering if SBF might be used as a witness for other cases. I think his reliability is a major concern for any testimony.
Good Q. You might like to check ScyllaDB written in C++, which is supposed to have considerably better performance than Cassandra (also low tail-latency) and a level of compatibility with it: https://www.scylladb.com/
Have you had any chance to compare your player strength values against other models to check how well they are aligned? You can find from Premier League's web site "Player Performance Index", e.g. for last season the top three players according to PL PPI were Harry Kane, Riyad Mahrez and Jamie Vardy.
Another obvious question is that have you checked your model against the odds on betting sites that provide "Draw-no-bet" bets since you are not yet taking into account draws?
There are many machine learning libraries that have good implementations of LDA (e.g. Gensim), so it should be "relatively" straightforward to create the topics and clustering based on the abstracts of the papers.
I think there might be confusion about wht nl was referring to. Yes, the link is to a list (produced by Karpathy) of papers on which LDA has been performed.
But one of the listed papers is also by Kapathy ("Deep Fragment Embeddings for Bidirectional Image
Sentence Mapping"), and I think this might be what nl is complimenting as being done quickly.
I've been doing some models for live betting on ice hockey, but am now thinking of working on models for other sports as well. Would be nice to discuss about this and other ideas on sports betting and fantasy sports! My contact information is on my profile.
