lnofeisone

Sold DNNGY and went for ARKK march puts.

I realize not the point of the thread but Predict it has been out of control lately. There is free $ to be had. For example, "Which party will win presidential election" was settled a few days ago and the last trading price was $0.94 (the payout is $1). Even 2 weeks after the election this market was trading in the $0.85 range. There are few other markets that are trading at unreasonable prices, given that we already know what the outcome will be. I suppose the gamblers/the believers are those who are taking the opposite side of these bets and they really just need to be right once to recoup their losses. *The catch with predictit is that withdrawal cost is 5% (4% is you use cash back card) and they take 10% of your winnings.

+1 Ride or die. I just sold my starter ABNB. 30% in a week is just money growing on trees but it's so uncomfortable. Bought some AIV, ATCO, and bought back my 25% in KNOP.

25% of my KNOP. Will look to buy it back. As pointed out by Wabuffo in KNOP thread, some turbulence ahead as Cushing is rebalancing and KNOP is out.

I've come to this conclusion too (and don't think SCOTUS will resolve all issues) . I've traded in and out and holding what is essentially free shares but not holding my breath for anything spectacular either.

Starter ABNB

Congrats on your accomplishments! Between the two of us, we have a math degree, 3 computer science degrees, 1 electrical engineering degree, and a physics degree. I teach AI/ML at a university (historically, non-online 8)) and worked for an insurance company. So now that we pointlessly settled that (and really credentialed our mutual "technobabble") do we really need to go through the false equivalence that is the next 3 lines you wrote? On a more cordial note, I found this particularly hilarious "Hey, a human and a lump of coal floating in a bucket of water are made of roughly the same stuff, so to anyone but a purist, they're the same." Got to give some love to kinetics and thermodynamics. Call me in 100 years. Pretty sure we will all be lumps of coal floating in a bucket. Though maybe if I turn myself into a diamond, I'll sit there on a shelf for a bit longer or sink to the bottom of the said bucket ;D. For my curiosity, forget prop algorithm(s) that Lemonade has, what AI/ML technique in your mind is not rooted in statistics? In fact, let's say for a second that Lemonade (like Capital One in the past) found a way to stratify the broad population into smaller segments. And now they have to make inferences. So, back to statistics. More importantly, and probably more pertinent to this forum: 1) Today, Lemonade ratios are declining but are still above the industry average (59.6% for 219, 61.6% for 2018 - I'll agree upfront that these numbers aren't totally accurate as Lemonade doesn't cover everything P&Cs do). So, for now, they are converging to average. 2) Let's peel off some of that sweet, sweet, AI/ML magic. Lemonade's largest markets are CA, TX, NY (around 70%). All 3 of those markets clock in net loss ratios that are typically below the industry average with premiums above the industry average. As a fun fact, in California, they have a pretty high justified complaint ratio. Imagine what it takes to get a millennial to complain and take it to the state. By the way, few companies just above and below Lemonade have 2 star ratings and some very scratching remarks, as per Gooogle. 3) They are currently ceding 75% of their policies. Curious how their reinsurance fees will hold up as more data comes in. 4) Aside from my belief that they are simply converging on the weighted average of the rations of the markets they operate in, I'm genuinely curious what general set of AI/ML algorithms differentiates Lemonade from Progressives of the world? What makes you believe that the latter can't figure these algos out? The latter are sitting on plenty of data, can afford to acquire new datasets, and hire an army of data scientists to get through the data. Cloud is not really a differentiator anymore. I agree, Lemonade is willing to try things that others haven't (e.g., behavior analytics) at the production level but at its core, it's still a test-and-learn shop. I don't have a high conviction in the timing of this short (hence such a small short). I do think it's a nice platform that beautifully obfuscates a traditional insurance company. Probably should take this to the Lemonade thread...

No, they didn't, and I'm not quite sure why you'd pretend these are the same thing. On a practical level, ML uses historic data (usually entire dataset, let's ignore train-test-split for a second) to make generalizable predictions. Statistics draw inferences from a sample. To make statistics ML, just up your sample size to make it population size ;). I can walk you through the same path to show you how AI is basically the same thing (starting with perception). I'd love for you to explain what is it that makes you think I'm pretending? Generally, AI/ML fields borrow heavily from statistics. Sure they are different if you take the purist approach (e.g., ML predicts based on passive observations and AI implies agent interaction with the environment to maximize chances of goal achievement). Sure, other fields are contributing (EE, CS, etc.) and some of the latest algorithms don't come from the field of statistics but at the core, these are all statistical methods (see the assumption with any algorithm that is available today). The reality of things is that what changed the field are three things: 1) availability for computing power (AWS, GCP, etc.) and 2) data, lots of it 3) fusion of different methods (e.g., TensorFlow). Feel free to let me know what insurance-specific algorithm(s) Lemonade has that is not rooted in statistics that are not available to Progressive, Geico, etc. I say insurance-specific because I'm sure Lemonade, by virtue of being new (i.e., no cultural or digital transformations necessary), can rapidly deploy a bag of algorithms to help with processing (robotics process automation), translation (nlp/nlg), etc. So is the premise that they are an efficient back office?

I don't know the company well, but, having worked as a tech person in an insurance-related company, insurers often don't seem to have the culture to adopt market-changing technological solutions. I agree that something like this that seems to be the obvious strategy for tradition insurers. But it isn't necessarily something that those traditional insurers can actually execute. Traditional insurances had AI/ML for decades. They called it statistics. I haven't seen anything revolutionary (e.g., Tesla was the only EV for a while) out of Lemonade and they aren't price competitive if I have a car + rent/own. Throw in challenges with renters in big cities, at minimum there will be turbulence in the next few quarters as older policies start to roll off. Just my 2 cents and I was wrong on LMND stock before.

I'm not up to date on my SPACs. What's the deal with PTICU?

Added 1/3 short position in LMND after seeing my small short be very much worthless. Not sure what Motley Fool sees in this that is so transcending of AI/ML that Geico or Progressive don't already have or can't buy.

sold ORI (thanks Spek), JBGS (thanks Pupil), AM. Reduced KMI, KNOP, and CLMT.

Bought back my nat gas short and bought some INTC bear spreads.

I think what SpaceX has done is exceptional. I also think BA and LMT can just sit back and wait to see how it's done and then step in and replicate with economies of scale without sinking few $Bs.

I bought some December bear verticals here too. Not a lot but just in case the market decides to sell off.

Few BABA shares and a small CLMT lot. The latter has been trading rather strong in the last few weeks after some news of them exploring lubricant unit sale.

If you use thinkorswim, you can connect and export for free. If you want another API, I've been using Quandl at work for some time now. It has stocks, mutual funds, currencies though they are packaging them as different data sets so if cost is an issue this is somethign to consider. Overall, pretty easy Python set up. For personal use for stocks it is about $50/mo. It gives a lot of other metrics too (e.g., revenue). EDIT: Forgot to include the link for ToS-Excel connect - https://www.lockeinyoursuccess.com/wp-content/uploads/2016/04/Connecting-ThinkOrSwim-to-Excel.pdf

Sure. There are things that FB/Twitter/GoogleNews/Netflix/AnyMediaOrganization do that CoBF does not. You can look at these things and judge them on positive or negative: 1. Notifications. Positive: if you are waiting for friend to show up and they are late, you want to be notified that they messaged you. Negative: constant attention hog. (BTW, CoBF has notifications too, just less invasive perhaps). Solution: you can set notifications to whatever you want, including turning them off. 2. Recommendations. Positive: You just read about Model 3, you want to read more about Model 3 Autopilot. You just watched "Sleepless in Seattle", you want to watch "You've Got Mail" or "Big". Negative: Rabbit hole, splurging, etc. Solutions: I'm not sure you can turn off recommendations in most places. Maybe there are knobs in some apps. I'd argue that recommendations is not a huge issue, but maybe they are for some people. 3. Ads. Personalized ads. Positive: get relevant ads. Negative: privacy, pushing you to buy crap. Solution: just fricking adblock everything. Harder on phones... Overall ads are crap. If you ever looked at "personalized" ads, you'd despair on how bad ad targeting is and not about how powerful AI is. 4. Curated timelines/posts. Positive: you see what you want to see. Negative: you see what company thinks you want to see. Echo chambers. Crappy feeds. Maybe addictive feeds. Solution: Personally I think the curated feeds are just crap, so just don't use them. It's not that they are evil-great and addictive. It's that they are just crappy selection. So don't use them. Pretty much every platform allows you to avoid curated feeds. It's possible to have a discussion about all these issues. But not if documentary authors turn the documentary into echo chamber that they themselves condemn. Basically zero opposing or even moderate opinions. And the fake "real story about teenager who got radicalized and missed on love and foodball practice due to evil AI" is just a mind manipulation porn. I think what the documentary authors tried to convey is that when there is a direct and proportional exchange of $ for your attention, the companies will do everything in their power to shift individuals to the "negative" while making it seem innocuous. It's easy to make it innocuous because we, humans, are really easy to trick. It's even easier to trick us when some of these services get so deeply entrenched into the fabric of our lives (e.g., Whatsapp/WeChat for communication with loved ones). The ease with which we get tricked is well captured by Kahneman's "Thinking fast and slow." Nonwithstanding the cheesy side story (or as you call it, manipulation porn), the authors did a pretty good job highlighting how our fallibility got weaponized against us. The "Solution" that you are bringing forward, that's the slow, rational brain. Sure, it makes sense, but we just don't slow down enough to think it through.

DNNGY and ORI starters.

Can you provide some examples of what you viewed as gross exaggerations and unproven claims all over the place?

Corning fits this mold too.

Starter positions in PGRE and JBGS.

Covered GME calls. Not feelign easy with all the outside involvement.

Sold some GME 5 and 10 calls going out to Jan 22.

Closed UNG short. Bought NVAX 50 DEC/Apr and LMND 40 Dec/Mar calendars.