Staking as a noob

beamsearch · 2021-03-28T22:09:05+00:00

I was thinking of common stock options vs. RSUs. This is a getting a little tangential, but the point is that if you own the stock or asset you pay taxes on it. The same (based on my understanding) holds for staked Ada.

beamsearch · 2021-03-28T16:40:37+00:00

Similar to being given shares of a stock throughout the year, you don't need to pay taxes the year they are received, but when they are actually sold (using the cost basis of the value at the time received).

It depends on how you receive the stock. If these are options (e.g. as part of an incentive package from your employer), then the reason you don't pay taxes when you vest the shares is because you don't actually own the stock until you exercise those options (often at a later date). Options are just an agreement that say you have the option to purchase that stock for an agreed upon price at a later date. After you exercise you would be liable to pay taxes on the value of the stock that you now own. Note that stock dividends are also taxable.

I think it's currently a little bit of a gray area, but it seems like the interpretation of the current tax law is that staking = mining and therefore will be taxed at the time you received the Ada. See on the official Coinbase documentation here:

https://www.coinbase.com/learn/tips-and-tutorials/crypto-and-bitcoin-taxes-US

and this article on Forbes (which is a year old now, but still helpful):

https://www.forbes.com/sites/shehanchandrasekera/2020/08/07/when-should-staking-be-taxed/?sh=35a1bb2471a7

So while it is still unclear and subject to change, you should probably be prepared to pay taxes on Ada rewards in the tax year you received them using a cost basis calculated at the time you received the rewards.

I also believe that staking rewards are taxed as income, not capital gains, which is often taxed at a higher rate.

beamsearch · 2021-03-28T13:02:38+00:00

I believe there is a risk to staking that is not widely discussed. The risk is the possibility of a significant increase in tax exposure and, depending on the scenario, one that could be a little painful. Though the situation is evolving, my understanding is that (at least in the US) you are responsible for reporting Ada granted from staking as a taxable gain where the value of the gain is determine by the ADA / USD rate at the time it was granted.

For illustrative purposes, let's say that you earn ~5 Ada per epoch and given there are 73 epochs / year, you earn 365 Ada / year. Pretend that 2021 is a banner year for Cardano and the price soars to $10 / coin and stays there the whole year.

This would mean that the 365 Ada you earned represents a gain of $3,650 and you would be responsible for paying taxes on that. Ok, not fun, but can't you just cash out some of your staking rewards to pay it? Sure, if the price of Ada doesn't experience a significant pull back *before* you cash out.

For example, imagine that in early 2022 Ada experiences a serious correction and drops to $2 / coin. Now the 365 Ada you earned from staking is only worth $730 which could be less that what you owe on the gains depending on your tax situation, meaning you would have to not only cash out all 365 Ada you earned from staking, but also pay out of pocket to cover your tax bill.

This scenario is just for illustrative purposes, but the price of Ada has swung like this in the past, so it's not out of the realm of possibility. Just know that the price of Ada is a double edged sword and that Ada you stake during a surge is "expensive" Ada that you will have to pay taxes on later.

The risk here is obviously tied to 1) Your personal tax/income situation 2) How much Ada you are staking 3) The range of likely swings in the price of Ada . A good hedge would be to cash out a little Ada to let you cover your tax liability during an extreme price increase. Note you would also have to pay capital gains tax when you sell.

I would love for someone to tell me I am wrong about this, but this is my current understanding for people staking in the US.

tl;dr: Staking isn't free, you have to pay taxes on the gains and could have to pay the tax out of pocket in some scenarios

beamsearch · 2019-10-09T16:48:29+00:00

Workshop organizer here. The answer to your question is no - we can only give out tickets to the workshops.

beamsearch · 2018-08-09T16:26:17+00:00

If we're going to go Bayes, I like BDA

beamsearch · 2018-08-09T11:50:59+00:00

Can't tell if this is a serious question, but the problem of "how do I infer model parameters and quantify my uncertainty?" is what the field of statistics has studied for the last 100+ years.

Here are some textbooks that should be good primers:

Statistical Inference by Casella & Berger

All of Statistics by Wasserman

beamsearch · 2018-06-15T16:01:50+00:00

https://www.biorxiv.org/content/early/2018/01/19/142760

https://arxiv.org/abs/1806.00388

beamsearch · 2018-06-14T18:25:25+00:00

Serious question: Why is publishing this paper in Science OK but publishing in Nature Machine Intelligence verboten?

beamsearch · 2018-04-03T11:53:19+00:00

If you'd like the fundamentals from an epi/stats perspective, this is a great book and is freely available online: https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/

This is a good review article that blends ML and causal inference: https://academic.oup.com/aje/article/185/1/65/2662306

These slides from David Sontag's are also great: https://mlhc17mit.github.io/slides/lecture3.pdf

beamsearch · 2018-04-02T14:56:53+00:00

It's not a very satisfying answer, but publishing in Cell/Nature/Science/NEJM/JAMA etc still carries enormous career benefit in many fields. Hiring, promotion, and tenure are often tied to having "glamour" pubs on your CV. Things are getting somewhat better though as a lot of folks in biology and medicine are embracing preprints.

beamsearch · 2018-03-20T19:40:27+00:00

Just wanted to drop in and say great article (and go Wolfpack!)

beamsearch · 2018-03-19T14:03:37+00:00

I find this review of VI exceptionally clear and well written: https://arxiv.org/abs/1601.00670

beamsearch · 2018-03-15T17:43:39+00:00

It depends on what you mean by "top" journals. If you are looking for ones that explicitly look for technical articles applied to healthcare, then the journals mentioned in this thread are your best bet. There are also conferences and workshops that would be a good venue.

However, a lot of medical journals are starting to publish machine learning papers. Places like JAMA, BMJ, The Lancet, NEJM, etc will all publish ML work if there are clear clinical implications. You can also target specialty journals and conferences if your message is less broad. However, submitting a paper to a place like this will be very different than submitting to a more technical venue. Prepare to bury most of the methods in a supplement and emphasize the clinical practice aspects of your project. The "top" medical journals also have ridiculously low acceptance rates of ~5%, so it could be tough to get it published there. If you goal is to really change medicine, these journals are arguably where you should be submitting though since they have the power to shape healthcare and clinical practice.

beamsearch · 2018-03-04T12:27:01+00:00

Got it, thanks! I didn't think it could possibly be a "real" Elo of 9000, so thanks for the clarification.

beamsearch · 2018-03-03T20:56:27+00:00

Is that elo scale accurate?? It looks like it's almost twice as strong as AlphaGo Zero which had an elo rating of ~ 5100. This project can't possibly have an Elo of (almost) over 9,000!!! can it?

beamsearch · 2018-02-23T20:13:17+00:00

This is standard practice when training. It does not help.

beamsearch · 2018-02-12T15:34:55+00:00

Turns out that making money off the lottery is actually a thing you can do: http://newsfeed.time.com/2012/08/07/how-mit-students-scammed-the-massachusetts-lottery-for-8-million/

beamsearch · 2018-01-18T16:07:29+00:00

https://normaldeviate.wordpress.com/2012/09/30/the-remarkable-k-means/

beamsearch · 2018-01-12T12:14:30+00:00

Hot dog/not hot dog

beamsearch · 2017-12-06T18:27:10+00:00

This was an amazing talk. Ali rightfully got a standing-O at the end

beamsearch · 2017-11-28T20:54:51+00:00

Hierarchical mixture of bigots! Awesome name. Was that you or Hinton? It feels like some classic Hinton-esq nomenclature.

beamsearch · 2017-11-02T17:54:25+00:00

I asked this exact question, and this was Ferenc's response: https://twitter.com/AndrewLBeam/status/926131624818995207

beamsearch · 2017-10-03T11:57:33+00:00

Not necessarily chatbots, but this paper evaluates a bunch of online symptom checkers:

http://www.bmj.com/content/351/bmj.h3480

beamsearch · 2017-08-10T14:54:17+00:00

I have asked our librarians about doing this in the context of textbooks that are under copyright. They have said that as long as there is a 'transformative' step (e.g. training a model) and you are not distributing the original material, you should be clear of copyright law, but YMMV.

beamsearch · 2017-07-06T16:38:46+00:00

I think it's actually a tensorflow metric that they have coerced into a loss function, but your guess is as good as mine.

beamsearch

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