Define defensive stocks - BinaryOptions

Which one of you was it?

Newbie investors: 'I didn't know I'd lose money so fast'
"I started off with €100. I felt super-confident watching the ticker as stocks and shares were going up and down," he said. He piled into oil at $16 a barrel, thinking the price was sure to go up, but it fell almost immediately to $14. I didn't have enough money to cover the loss, so it crashed out my position and I got an email. I had no idea what had happened. I thought I was owning barrels, but I wasn't, I was borrowing. It was the fastest €100 I'd ever spent."
submitted by SlickMongoose to UKInvesting [link] [comments]

No gods, no kings, only NOPE - or divining the future with options flows. [Part 2: A Random Walk and Price Decoherence]

tl;dr -
1) Stock prices move continuously because different market participants end up having different ideas of the future value of a stock.
2) This difference in valuations is part of the reason we have volatility.
3) IV crush happens as a consequence of future possibilities being extinguished at a binary catalyst like earnings very rapidly, as opposed to the normal slow way.
I promise I'm getting to the good parts, but I'm also writing these as a guidebook which I can use later so people never have to talk to me again.
In this part I'm going to start veering a bit into the speculation territory (e.g. ideas I believe or have investigated, but aren't necessary well known) but I'm going to make sure those sections are properly marked as speculative (and you can feel free to ignore/dismiss them). Marked as [Lily's Speculation].
As some commenters have pointed out in prior posts, I do not have formal training in mathematical finance/finance (my background is computer science, discrete math, and biology), so often times I may use terms that I've invented which have analogous/existing terms (e.g. the law of surprise is actually the first law of asset pricing applied to derivatives under risk neutral measure, but I didn't know that until I read the papers later). If I mention something wrong, please do feel free to either PM me (not chat) or post a comment, and we can discuss/I can correct it! As always, buyer beware.
This is the first section also where you do need to be familiar with the topics I've previously discussed, which I'll add links to shortly (my previous posts:
1) https://www.reddit.com/thecorporation/comments/jck2q6/no_gods_no_kings_only_nope_or_divining_the_future/
2) https://www.reddit.com/thecorporation/comments/jbzzq4/why_options_trading_sucks_or_the_law_of_surprise/
---
A Random Walk Down Bankruptcy
A lot of us have probably seen the term random walk, maybe in the context of A Random Walk Down Wall Street, which seems like a great book I'll add to my list of things to read once I figure out how to control my ADD. It seems obvious, then, what a random walk means - when something is moving, it basically means that the next move is random. So if my stock price is $1 and I can move in $0.01 increments, if the stock price is truly randomly walking, there should be roughly a 50% chance it moves up in the next second (to $1.01) or down (to $0.99).
If you've traded for more than a hot minute, this concept should seem obvious, because especially on the intraday, it usually isn't clear why price moves the way it does (despite what chartists want to believe, and I'm sure a ton of people in the comments will tell me why fettucini lines and Batman doji tell them things). For a simple example, we can look at SPY's chart from Friday, Oct 16, 2020:

https://preview.redd.it/jgg3kup9dpt51.png?width=1368&format=png&auto=webp&s=bf8e08402ccef20832c96203126b60c23277ccc2
I'm sure again 7 different people can tell me 7 different things about why the chart shape looks the way it does, or how if I delve deeply enough into it I can find out which man I'm going to marry in 2024, but to a rationalist it isn't exactly apparent at why SPY's price declined from 349 to ~348.5 at around 12:30 PM, or why it picked up until about 3 PM and then went into precipitous decline (although I do have theories why it declined EOD, but that's for another post).
An extremely clever or bored reader from my previous posts could say, "Is this the price formation you mentioned in the law of surprise post?" and the answer is yes. If we relate it back to the individual buyer or seller, we can explain the concept of a stock price's random walk as such:
Most market participants have an idea of an asset's true value (an idealized concept of what an asset is actually worth), which they can derive using models or possibly enough brain damage. However, an asset's value at any given time is not worth one value (usually*), but a spectrum of possible values, usually representing what the asset should be worth in the future. A naive way we can represent this without delving into to much math (because let's face it, most of us fucking hate math) is:
Current value of an asset = sum over all (future possible value multiplied by the likelihood of that value)
In actuality, most models aren't that simple, but it does generalize to a ton of more complicated models which you need more than 7th grade math to understand (Black-Scholes, DCF, blah blah blah).
While in many cases the first term - future possible value - is well defined (Tesla is worth exactly $420.69 billion in 2021, and maybe we all can agree on that by looking at car sales and Musk tweets), where it gets more interesting is the second term - the likelihood of that value occurring. [In actuality, the price of a stock for instance is way more complicated, because a stock can be sold at any point in the future (versus in my example, just the value in 2021), and needs to account for all values of Tesla at any given point in the future.]
How do we estimate the second term - the likelihood of that value occurring? For this class, it actually doesn't matter, because the key concept is this idea: even with all market participants having the same information, we do anticipate that every participant will have a slightly different view of future likelihoods. Why is that? There's many reasons. Some participants may undervalue risk (aka WSB FD/yolos) and therefore weight probabilities of gaining lots of money much more heavily than going bankrupt. Some participants may have alternative data which improves their understanding of what the future values should be, therefore letting them see opportunity. Some participants might overvalue liquidity, and just want to GTFO and thereby accept a haircut on their asset's value to quickly unload it (especially in markets with low liquidity). Some participants may just be yoloing and not even know what Fastly does before putting their account all in weekly puts (god bless you).
In the end, it doesn't matter either the why, but the what: because of these diverging interpretations, over time, we can expect the price of an asset to drift from the current value even with no new information added. In most cases, the calculations that market participants use (which I will, as a Lily-ism, call the future expected payoff function, or FEPF) ends up being quite similar in aggregate, and this is why asset prices likely tend to move slightly up and down for no reason (or rather, this is one interpretation of why).
At this point, I expect the 20% of you who know what I'm talking about or have a finance background to say, "Oh but blah blah efficient market hypothesis contradicts random walk blah blah blah" and you're correct, but it also legitimately doesn't matter here. In the long run, stock prices are clearly not a random walk, because a stock's value is obviously tied to the company's fundamentals (knock on wood I don't regret saying this in the 2020s). However, intraday, in the absence of new, public information, it becomes a close enough approximation.
Also, some of you might wonder what happens when the future expected payoff function (FEPF) I mentioned before ends up wildly diverging for a stock between participants. This could happen because all of us try to short Nikola because it's quite obviously a joke (so our FEPF for Nikola could, let's say, be 0), while the 20 or so remaining bagholders at NikolaCorporation decide that their FEPF of Nikola is $10,000,000 a share). One of the interesting things which intuitively makes sense, is for nearly all stocks, the amount of divergence among market participants in their FEPF increases substantially as you get farther into the future.
This intuitively makes sense, even if you've already quit trying to understand what I'm saying. It's quite easy to say, if at 12:51 PM SPY is worth 350.21 that likely at 12:52 PM SPY will be worth 350.10 or 350.30 in all likelihood. Obviously there are cases this doesn't hold, but more likely than not, prices tend to follow each other, and don't gap up/down hard intraday. However, what if I asked you - given SPY is worth 350.21 at 12:51 PM today, what will it be worth in 2022?
Many people will then try to half ass some DD about interest rates and Trump fleeing to Ecuador to value SPY at 150, while others will assume bull markets will continue indefinitely and SPY will obviously be 7000 by then. The truth is -- no one actually knows, because if you did, you wouldn't be reading a reddit post on this at 2 AM in your jammies.
In fact, if you could somehow figure out the FEPF of all market participants at any given time, assuming no new information occurs, you should be able to roughly predict the true value of an asset infinitely far into the future (hint: this doesn't exactly hold, but again don't @ me).
Now if you do have a finance background, I expect gears will have clicked for some of you, and you may see strong analogies between the FEPF divergence I mentioned, and a concept we're all at least partially familiar with - volatility.
Volatility and Price Decoherence ("IV Crush")
Volatility, just like the Greeks, isn't exactly a real thing. Most of us have some familiarity with implied volatility on options, mostly when we get IV crushed the first time and realize we just lost $3000 on Tesla calls.
If we assume that the current price should represent the weighted likelihoods of all future prices (the random walk), volatility implies the following two things:
  1. Volatility reflects the uncertainty of the current price
  2. Volatility reflects the uncertainty of the future price for every point in the future where the asset has value (up to expiry for options)
[Ignore this section if you aren't pedantic] There's obviously more complex mathematics, because I'm sure some of you will argue in the comments that IV doesn't go up monotonically as option expiry date goes longer and longer into the future, and you're correct (this is because asset pricing reflects drift rate and other factors, as well as certain assets like the VIX end up having cost of carry).
Volatility in options is interesting as well, because in actuality, it isn't something that can be exactly computed -- it arises as a plug between the idealized value of an option (the modeled price) and the real, market value of an option (the spot price). Additionally, because the makeup of market participants in an asset's market changes over time, and new information also comes in (thereby increasing likelihood of some possibilities and reducing it for others), volatility does not remain constant over time, either.
Conceptually, volatility also is pretty easy to understand. But what about our friend, IV crush? I'm sure some of you have bought options to play events, the most common one being earnings reports, which happen quarterly for every company due to regulations. For the more savvy, you might know of expected move, which is a calculation that uses the volatility (and therefore price) increase of at-the-money options about a month out to calculate how much the options market forecasts the underlying stock price to move as a response to ER.
Binary Catalyst Events and Price Decoherence
Remember what I said about price formation being a gradual, continuous process? In the face of special circumstances, in particularly binary catalyst events - events where the outcome is one of two choices, good (1) or bad (0) - the gradual part gets thrown out the window. Earnings in particular is a common and notable case of a binary event, because the price will go down (assuming the company did not meet the market's expectations) or up (assuming the company exceeded the market's expectations) (it will rarely stay flat, so I'm not going to address that case).
Earnings especially is interesting, because unlike other catalytic events, they're pre-scheduled (so the whole market expects them at a certain date/time) and usually have publicly released pre-estimations (guidance, analyst predictions). This separates them from other binary catalysts (e.g. FSLY dipping 30% on guidance update) because the market has ample time to anticipate the event, and participants therefore have time to speculate and hedge on the event.
In most binary catalyst events, we see rapid fluctuations in price, usually called a gap up or gap down, which is caused by participants rapidly intaking new information and changing their FEPF accordingly. This is for the most part an anticipated adjustment to the FEPF based on the expectation that earnings is a Very Big Deal (TM), and is the reason why volatility and therefore option premiums increase so dramatically before earnings.
What makes earnings so interesting in particular is the dramatic effect it can have on all market participants FEPF, as opposed to let's say a Trump tweet, or more people dying of coronavirus. In lots of cases, especially the FEPF of the short term (3-6 months) rapidly changes in response to updated guidance about a company, causing large portions of the future possibility spectrum to rapidly and spectacularly go to zero. In an instant, your Tesla 10/30 800Cs go from "some value" to "not worth the electrons they're printed on".
[Lily's Speculation] This phenomena, I like to call price decoherence, mostly as an analogy to quantum mechanical processes which produce similar results (the collapse of a wavefunction on observation). Price decoherence occurs at a widespread but minor scale continuously, which we normally call price formation (and explains portions of the random walk derivation explained above), but hits a special limit in the face of binary catalyst events, as in an instant rapid portions of the future expected payoff function are extinguished, versus a more gradual process which occurs over time (as an option nears expiration).
Price decoherence, mathematically, ends up being a more generalizable case of the phenomenon we all love to hate - IV crush. Price decoherence during earnings collapses the future expected payoff function of a ticker, leading large portions of the option chain to be effectively worthless (IV crush). It has interesting implications, especially in the case of hedged option sellers, our dear Market Makers. This is because given the expectation that they maintain delta-gamma neutral, and now many of the options they have written are now worthless and have 0 delta, what do they now have to do?
They have to unwind.
[/Lily's Speculation]
- Lily
submitted by the_lilypad to thecorporation [link] [comments]

# /r/Peloton Pre-TDF Survey 2020

Gentlemen, Ladies and those otherwise addressed - we know you've been waiting for a good thing, and the survey results are finally ready!
The answers were collected from you all during August 2020 with 1428 unique replies. That's a participation of 0.5% of all subscribers! That's really not too bad, when you keep in mind how popular these kind of surveys are. But we here at /peloton want to show you that this is all about presenting the information in the subreddit to cater better to our audience!
Updated after a few hours to include some more historical data the final edit that for some reason wasn't copied properly
Year 2013 2014 2015 2016 2018 Mar 2018 Aug 2019 2020
Results 2013-06-12 2014-06-25 2015-08-07 2016-11-17 2018-03-06 2018-08-20 2019-07-22 2020-10-12
Replies 351 598 1395 892 630 928 986 1428
Without further ado, let's get cracking on the response

You and Cycling

1. Where do you live?

Country 2015 2016 2018 Mar 2018 Aug 2019 2020
USA 32% 28.3% 22.84% 25.32% 20.23% 24.59%
UK 18.6% 17.6% 14.70% 20.13% 15.48% 14.80%
Netherlands 6.4% 9.4% 11.50% 11.58% 10.01% 11.01%
Germany 3.73% 3.4% 4.95% 6.39% 7.84% 6.65%
Denmark 3.9% 3.6% 4.31% 3.79% 7.64% 5.79%
Belgium 3.8% 2.7% 8.15% 3.57% 5.78% 5.36%
France 2.01% 1.08% 2.88% 2.27% 5.26% 3.50%
Canada 4.9% 7% 6.39% 4.22% 4.95% 4.50%
Australia 5.2% 4.7% 3.83% 4.00% 4.33% 3.93%
Slovenia 0.73% 0.32% 1.30% 1.14% 2.14%
Norway 2.58% 1.8% 1.60% 1.95% 2.58% 1.86%
Sweden 1.08% 1.09% 1.44% 1.41% 1.75% 1.43%
Ireland 1.00% 1.09% 1.44% 1.19% 0.72% 1.36%
Portugal 1.65% 1.8% 2.40% 1.52% 1.34% 1.14%
Italy 1.45% 1.44% 0.65% 1.03% 1.07%
Largely the same picture as ever, with the US leading the way, the UK in second and then a sliding scale of Europeans countries. Slovenia continues to pick its way up the pile for obvious reasons!
World Map to demonstrate

2. What's your age?

u17 17-19 20-25 26-30 31-35 36-40 41-50 51+ Total
2015 2.22% 12.04% 41.51% 24.66% 10.68% 4.87% 2.94% 1.08% 1395
2016 1.5% 8.9% 40.8% 24% 12% 5.4% 5.2% 2% 887
2018 Mar 1% 7.1% 33.5% 27.4% 16.2% 7% 5.7% 2.1% 617
2018 Aug 1.7% 9% 33.9% 26.4% 15.5% 7% 5% 1.5% 905
2019 1.5% 6.6% 33.2% 27.5% 16.4% 7.1% 5.8% 2% 972
2020 1.3% 6.8% 31.7% 28% 16.6% 7.2% 5% 2.5% 1420
Pretty much the same as last year, with the usual reddit demographics of majority 20 somethings dominating.

3. What's your gender?

'13 '14 '15 '16 '18 (1) '18 (2) '19 '20
Male 97.2% 97% 94.9% 93.4% 93.3% 93.6% 95.1% 94.9%
Female 2.8% 2.7% 4.8% 5.3% 5.3% 5.4% 3.7% 4.8%
Other - 0.33% 0.29% 0.78% 0.76% - -
Non-Binary - - - - 0.64% 0.99% 1.2% 0.4%
More normality here for reddit.

4. How much of the men's season do you watch/follow?

Type March '18 (%) August '18 (%) 2019 (%) 2020 (%)
Grand Tours 84.7 92.0 90.2 87.3
Monuments 79.1 74.9 79 75.9
WT Stage races 67.4 62.4 70.5 71.7
WT One day races 73.3 59.8 62.3 60.7
Non WT Stage races 32.6 16.7 17.4 25
Non WT One day races 34.8 13.7 17.4 20.7
Literally everything I can consume 35.9 18.1 21.1 27.1
Whilst GT following may be down (somehow), all the lower level stuff is up, which makes sense considering how desperate we have been for any racing during the season shutdown.

5. Do you maintain an interest in women's professional road racing?

Do you maintain an interest in women's professional road racing? '19 '20
Yes 49.8 49.2
No 50.2 50.8
Still very much a half/half interest in women's cycling on the subreddit.

6. How much of the women's season do you follow?

The following is true for the half of you that follows womens cycling.
How Much %
Just the biggest televised events 63.15%
Most of the live televised/delayed coverage stuff 29.08%
All televised racing 5.09%
Down to .Pro & beyond 2.69%

7. How long have you been watching cycling?

How Long %
Under a year 2,95%
1-3 years 19,50%
4-6 years 19,85%
7-9 years 14,10%
10-12 years 13,81%
13-15 years 7,15%
15-20 years 10,73%
20-25 years 6,17%
25 years + 5,75%
Simplified the years a little this time, but whilst we have a fair number of newbies, most people have picked the sport up since around 2013/14.

Sporting Favourites

8. Do you have like/dislike feelings about WT teams?

Once more, 14.4% of people really don't have feelings on the subject.
Of those that do:
AG2R Astana Bahrain Bora CCC Cofidis Quick-Step EF FDJ
Like 352 213 127 770 156 116 847 724 423
Meh 775 620 773 415 889 896 310 448 700
Dislike 52 356 263 31 112 141 71 37 53
Karma 300 -143 -70 739 44 -25 776 677 370
Israel Lotto Michelton Movistar NTT Ineos Jumbo Sunweb Trek UAE
Like 135 364 517 231 101 304 925 279 383 118
Meh 740 764 626 646 931 414 282 805 765 734
Dislike 302 40 52 326 121 562 53 97 42 331
Karma -167 324 465 -95 -20 -258 872 182 341 -213
So, the most popular team this year is Jumbo-Visma, followed by Quick-Step & Bora-hansgrohe. Least popular are Ineos & UAE.
As per usual, no one cares about NTT & CCC, with nearly 81% of users rating NTT as meh. Pretty damning stuff.
Lastly, we have the usual historical comparison of how teams have fared over time, normalised to respondents to that question on the survey.
Things to note then, firstly that the Astana redemption arc is over, seeing them back in the negative, maybe Fulgsangs spring issues helped aid that? The petrodollar teams of UAE & Bahrain are stubbornly negative too, with Israel keeping up the Katusha negative streak. Meanwhile, at the top end, EF & Jumbo go from strength to strength, whilst some others like Sunweb are sliding over time - their transfer policies no doubt helping that.

10. Do you ride a bike regularly?

Answer 2018Mar 2018Aug 2019 2020
For fun 61.5% 63.4% 59.9% 62.9%
For fitness 59.3% 59.6% 54.8% 59.8%
For commuting 46% 46% 45.6% 40%
For racing 20.6% 20.6% 15.9% 17.7%
No, I don't 14.2% 12.9% 14.8% 13.6%
Still a fairly small group of racers out of all of us

11. Out of the sports you practice, is cycling your favourite?

Yes No
58,29% 41,71%
A new addition to the survey prompted by a good point last time, just over half of us rate cycling as the favourite sport we actually do.

12. What other sports do you follow?

Sport #
Association Football / Soccer 50.78%
Formula 1 35.81%
American Football 26.27%
Basketball 22.46%
Track & Field 17.58%
Esports (yes, this includes DotA) 17.30%
Rugby 14.27%
Skiing 14.12%
Ice Hockey 13.63%
Baseball 12.15%
Motorsports (Not including F1) 10.59%
Cricket 10.52%
Tennis 9.53%
Chess 8.97%
Triathlon 8.69%
Biathlon 8.12%
Snooker 7.06%
Golf 6.92%
Swimming 6.85%
Ski Jumping 6.78%
Climbing 5.72%
Martial Arts 5.65%
Handball 5.44%
Darts 5.01%
Speed Skating 5.01%
Football always tops the charts, and Formula 1 continues to rank extremely highly among our userbase. Those who have a little following below 5% include Sailing, Fencing, Surfing, Boxing & Ultra-Running.
Other cycling disciplines
Sport #
Cyclocross 22.10%
Track Cycling 14.34%
MTB 8.97%
BMX 1.20%

13. Out of the sports you follow, is cycling your favourite sport?

Yes No
61.79% 38,21%
Good. Makes sense if you hang out here.

Subreddit stats

14. How often do you participate in a /Peloton Race Thread whilst watching a race?

2015 2016 2018Mar 2018Aug 2019 2020
I always participate in Race Threads during races 2.8% 2% 2.2% 4% 2.5% 3%
I follow Race Threads during races 41.7% 36.7% 38.1% 42.1% 42.5% 38.9%
I often participate in Race Threads during races 16.8% 19% 16.5% 18.9% 15.2% 13%
I rarely/never participate in Race Threads during races 38.7% 41.3% 43.1% 35% 39.8% 45.1%
Slightly less invested than before, reverting back to an older trade.

15. How do you watch Races?

Method 2018Mar 2018Aug 2019 2020
Pirate Streams 62% 46.5% 50.2% 47.9%
Free Local TV 55.7% 64.5% 59.6% 53.9%
Desperately scrabbling for Youtube highlights 37.9% 30.2% 28.2% 24.9%
Paid Streaming services 32.3% 35.4% 38.3% 46.3%
Year on year, paid streaming services go up - the increasing availability of live content legally continues to improve, and so do the numbers on the survey.

16. Where else do you follow races live (in addition to watching them)?

Type 2018Mar 2018Aug 2019 2020
/Peloton race threads 86.2% 83.4% 80.2% 76.9%
Twitter 30.5% 34.7% 33.3% 38.3%
PCS Liveticker - - 30.2% 32%
Official tracker (if available) 24%
The Cyclingnews liveticker 26% 23.5% 21.5% 18.9%
Sporza (site/ticker) 1.89% 9.5% 10.8% 10.8%
NOS Liveblog - 6.8% 7% 9.2%
Steephill 0.52% 13.5% 10.2% 8.2%
/Peloton discord 6.5% 5.4% 7.5% 7.2%
Other cycling forums 15.1% 8.1% 7.6% 7%
feltet.dk - 2.2% 5.4% 5.2%
Facebook 3.8% 5.4% 4% 4.2%
BBC Ticker - 3.5% 2.1% 4.1%
DirectVelo - 1.3% 1.6% 1.8%
Non Cycling Forums - 1.3% 1.2% 1.2%
/cyc/ - 1.3% 1% 0.6%
/peloton IRC ~0 0.8% 0.4% 0.5%
The PCS liveticker continues to have a strong following, whilst the cyclingnews ticker slowly slides into less usage over time.

17. Do you use /Peloton mostly in classic reddit or redesign when on the desktop?

Type 2018 Aug 2019 2020
Classic 75.1% 67.2% 46.2%
Redesign 24.9% 32.8% 53.8%
Time to abandon ship. The end has come.

18. With what version of reddit do you browse the sub?

Version 2019 2020
Official App 17.9 31.1
Desktop Classic 37.8 25.8
3rd Party App 18.3 17.2
Mobile Web 12.4 14.7
Desktop Redesign 13.7 11.2
Phone browsing is very much in vogue.

19. How did you find the sub?

How %
Through other forms of reddit, f.e. /bicycling 48.33%
Too long - can't remember 38.65%
Google search 9,11%
My friend told me 2,28%
I wanted to talk about my exercise bike 0.78%
Twitter 0.5%
Lantern Rouge Youtube 0.28%

Other bits and bobs

20. Did you think back in March we would see any more racing this year?

Yes No
52,81% 47,19%
Despite the threat, we have seen racing again

21. Will we manage to fulfill the rest of the UCI calendar without further Covid-19 issues postponing more races?

Yes No
25.3% 74.7%
Sorry to you 25%, Amstel, Roubaix & a bunch of other races have falled foul of COVID-19 related cancellations.

22. When did you become aware of Alexander Foliforov?

When %
Before the 2016 Giro 3,25%
22nd May, 2016 15,55%
On /pelotonmemes in 2020 21,13%
Who? 60,07%
If you didn't know of the man, watching him demolish the Giro field in 2016 on the stage 15 ITT should help to gain understanding

23. Who will win the 2020 Tour de France?

Rider %
Roglic 52,12%
Bernal 16,57%
Pinot 9,24%
Dumoulin 7,9%
N.Quintana 2,82%
Pogacar 1,41%
Richie Porte 0,35%
We can safely say that most of us were wrong about this one.
That's not a lot of confidence in Richie Porte either, the man who was to finish on the third spot of the podium. Alexander Foliforov (0,23%) had just a tiny number of votes less, and that man wasn't even in the race.

24. What for you was the defining cycling moment of the previous decade?

We had a lot of brilliant suggestions, but these were the clear five favourites when we tabulated the results.
Honorable mentions go to the Giro 2018, which had Tom Dumoulin winning, and of almost identical fascination to many of you - Tom Dumoulin going on someones porta-potty in the middle of the stage.
Little bit of recency bias perhaps, but that's better than ignoring that this was for the last decade and firmly insisting Tom Boonens 2005 WC win was the biggest thing. Special shoutout to almost all the Danes present in /peloton who voted for Mads Pedersens WC win last year. It's an understandable reaction.

25. Any suggestions for the Survey?

New Questions
We promise to feature one of these suggestions in the next survey
Suggestions
We will try to implement this. But it will also skew results.
About the Survey
The subscribers are torn on Women's cycling, nearly a 50/50 split there as the survey showed - The moderators at /peloton are firmly in the "more cycling is better" basket, and we will continue to get as good coverage of womens cycling as possible.
Are you trying to give the moderators PTSD? Because this is how you give the moderators PTSD.

26. Any suggestions for the sub?

ALSJFLKAJSLDKJAØLSJKD:M:CSAM)=#/()=#=/")¤=/)! - Your moderator seems to be out of function. Please stand by while we find you a new moderator
The Weekly threads are great for these types of questions, where several people can contribute and build up once it is understood which information is relevant.
Our experience is that "limited" will never be so, if we're going to moderate it fairly. Moderating is not a popularity contest, but believe it or not, we're actually trying to be as fair as possible. and for that, we need rules that are not subjective. Unless you have a stationary exercise bike.
All of these are good suggestions, but remember that all of you can also contribute - The mods are sometimes stretched thin, specially in the middle of hectic race schedules. It's easier if one of you has a way to contact a rider or a person of interest and can facilitate the initial communication.
We've worked on this! The Official Standard is now as follows: [Race Thread] 202x Race Name – Stage X (Class)
This sounds as a nice community project for the after-season, and hopefully many of you subscribers can contribute.
Come with suggestions on how to tidy it up!
We have chastised all the mods. They are now perfectly trained in gender-neutral pronouns. Be well, fellow being.
If we can implement this for hard liquor, you know we will.
The spoiler rule is one that is discussed frequently - in general - some users absolutely hate it, but a majority love it. Perhaps we'll include a question in the next survey to see how this divide is exactly.
We actually do - whenever there is a matter of life or death, we think public information is more important than a spoiler rule. But at the same time, we try to collect all the different posts into one main thread, so to keep things focused and letting very speculative posts meet with hard evidence from other sources.
This is a tough ask of the internet. While we can agree that voting should be done accordingly to what insights they bring, not subjective opinions, it is very hard to turn that type of thinking around. We can ask of you, our subscribers, that you please think twice about hitting that downvote button, and only do so because of you think a post is factually incorrect, not because it differs with your own subjective opinion.
That's the primary analysis of the survey! Feel free to contribute with how you experience things here!
submitted by PelotonMod to peloton [link] [comments]

No gods, no kings, only NOPE - or divining the future with options flows. [Part 3: Hedge Winding, Unwinding, and the NOPE]

Hello friends!
We're on the last post of this series ("A Gentle Introduction to NOPE"), where we get to use all the Big Boy Concepts (TM) we've discussed in the prior posts and put them all together. Some words before we begin:
  1. This post will be massively theoretical, in the sense that my own speculation and inferences will be largely peppered throughout the post. Are those speculations right? I think so, or I wouldn't be posting it, but they could also be incorrect.
  2. I will briefly touch on using the NOPE this slide, but I will make a secondary post with much more interesting data and trends I've observed. This is primarily for explaining what NOPE is and why it potentially works, and what it potentially measures.
My advice before reading this is to glance at my prior posts, and either read those fully or at least make sure you understand the tl;drs:
https://www.reddit.com/thecorporation/collection/27dc72ad-4e78-44cd-a788-811cd666e32a
Depending on popular demand, I will also make a last-last post called FAQ, where I'll tabulate interesting questions you guys ask me in the comments!
---
So a brief recap before we begin.
Market Maker ("Mr. MM"): An individual or firm who makes money off the exchange fees and bid-ask spread for an asset, while usually trying to stay neutral about the direction the asset moves.
Delta-gamma hedging: The process Mr. MM uses to stay neutral when selling you shitty OTM options, by buying/selling shares (usually) of the underlying as the price moves.
Law of Surprise [Lily-ism]: Effectively, the expected profit of an options trade is zero for both the seller and the buyer.
Random Walk: A special case of a deeper probability probability called a martingale, which basically models stocks or similar phenomena randomly moving every step they take (for stocks, roughly every millisecond). This is one of the most popular views of how stock prices move, especially on short timescales.
Future Expected Payoff Function [Lily-ism]: This is some hidden function that every market participant has about an asset, which more or less models all the possible future probabilities/values of the assets to arrive at a "fair market price". This is a more generalized case of a pricing model like Black-Scholes, or DCF.
Counter-party: The opposite side of your trade (if you sell an option, they buy it; if you buy an option, they sell it).
Price decoherence ]Lily-ism]: A more generalized notion of IV Crush, price decoherence happens when instead of the FEPF changing gradually over time (price formation), the FEPF rapidly changes, due usually to new information being added to the system (e.g. Vermin Supreme winning the 2020 election).
---
One of the most popular gambling events for option traders to play is earnings announcements, and I do owe the concept of NOPE to hypothesizing specifically about the behavior of stock prices at earnings. Much like a black hole in quantum mechanics, most conventional theories about how price should work rapidly break down briefly before, during, and after ER, and generally experienced traders tend to shy away from playing earnings, given their similar unpredictability.
Before we start: what is NOPE? NOPE is a funny backronym from Net Options Pricing Effect, which in its most basic sense, measures the impact option delta has on the underlying price, as compared to share price. When I first started investigating NOPE, I called it OPE (options pricing effect), but NOPE sounds funnier.
The formula for it is dead simple, but I also have no idea how to do LaTeX on reddit, so this is the best I have:

https://preview.redd.it/ais37icfkwt51.png?width=826&format=png&auto=webp&s=3feb6960f15a336fa678e945d93b399a8e59bb49
Since I've already encountered this, put delta in this case is the absolute value (50 delta) to represent a put. If you represent put delta as a negative (the conventional way), do not subtract it; add it.
To keep this simple for the non-mathematically minded: the NOPE today is equal to the weighted sum (weighted by volume) of the delta of every call minus the delta of every put for all options chains extending from today to infinity. Finally, we then divide that number by the # of shares traded today in the market session (ignoring pre-market and post-market, since options cannot trade during those times).
Effectively, NOPE is a rough and dirty way to approximate the impact of delta-gamma hedging as a function of share volume, with us hand-waving the following factors:
  1. To keep calculations simple, we assume that all counter-parties are hedged. This is obviously not true, especially for idiots who believe theta ganging is safe, but holds largely true especially for highly liquid tickers, or tickers will designated market makers (e.g. any ticker in the NASDAQ, for instance).
  2. We assume that all hedging takes place via shares. For SPY and other products tracking the S&P, for instance, market makers can actually hedge via futures or other options. This has the benefit for large positions of not moving the underlying price, but still makes up a fairly small amount of hedges compared to shares.

Winding and Unwinding

I briefly touched on this in a past post, but two properties of NOPE seem to apply well to EER-like behavior (aka any binary catalyst event):
  1. NOPE measures sentiment - In general, the options market is seen as better informed than share traders (e.g. insiders trade via options, because of leverage + easier to mask positions). Therefore, a heavy call/put skew is usually seen as a bullish sign, while the reverse is also true.
  2. NOPE measures system stability
I'm not going to one-sentence explain #2, because why say in one sentence what I can write 1000 words on. In short, NOPE intends to measure sensitivity of the system (the ticker) to disruption. This makes sense, when you view it in the context of delta-gamma hedging. When we assume all counter-parties are hedged, this means an absolutely massive amount of shares get sold/purchased when the underlying price moves. This is because of the following:
a) Assume I, Mr. MM sell 1000 call options for NKLA 25C 10/23 and 300 put options for NKLA 15p 10/23. I'm just going to make up deltas because it's too much effort to calculate them - 30 delta call, 20 delta put.
This implies Mr. MM needs the following to delta hedge: (1000 call options * 30 shares to buy for each) [to balance out writing calls) - (300 put options * 20 shares to sell for each) = 24,000 net shares Mr. MM needs to acquire to balance out his deltas/be fully neutral.
b) This works well when NKLA is at $20. But what about when it hits $19 (because it only can go down, just like their trucks). Thanks to gamma, now we have to recompute the deltas, because they've changed for both the calls (they went down) and for the puts (they went up).
Let's say to keep it simple that now my calls are 20 delta, and my puts are 30 delta. From the 24,000 net shares, Mr. MM has to now have:
(1000 call options * 20 shares to have for each) - (300 put options * 30 shares to sell for each) = 11,000 shares.
Therefore, with a $1 shift in price, now to hedge and be indifferent to direction, Mr. MM has to go from 24,000 shares to 11,000 shares, meaning he has to sell 13,000 shares ASAP, or take on increased risk. Now, you might be saying, "13,000 shares seems small. How would this disrupt the system?"
(This process, by the way, is called hedge unwinding)
It won't, in this example. But across thousands of MMs and millions of contracts, this can - especially in highly optioned tickers - make up a substantial fraction of the net flow of shares per day. And as we know from our desk example, the buying or selling of shares directly changes the price of the stock itself.
This, by the way, is why the NOPE formula takes the shape it does. Some astute readers might notice it looks similar to GEX, which is not a coincidence. GEX however replaces daily volume with open interest, and measures gamma over delta, which I did not find good statistical evidence to support, especially for earnings.
So, with our example above, why does NOPE measure system stability? We can assume for argument's sake that if someone buys a share of NKLA, they're fine with moderate price swings (+- $20 since it's NKLA, obviously), and in it for the long/medium haul. And in most cases this is fine - we can own stock and not worry about minor swings in price. But market makers can't* (they can, but it exposes them to risk), because of how delta works. In fact, for most institutional market makers, they have clearly defined delta limits by end of day, and even small price changes require them to rebalance their hedges.
This over the whole market adds up to a lot shares moving, just to balance out your stupid Robinhood YOLOs. While there are some tricks (dark pools, block trades) to not impact the price of the underlying, the reality is that the more options contracts there are on a ticker, the more outsized influence it will have on the ticker's price. This can technically be exactly balanced, if option put delta is equal to option call delta, but never actually ends up being the case. And unlike shares traded, the shares representing the options are more unstable, meaning they will be sold/bought in response to small price shifts. And will end up magnifying those price shifts, accordingly.

NOPE and Earnings

So we have a new shiny indicator, NOPE. What does it actually mean and do?
There's much literature going back to the 1980s that options markets do have some level of predictiveness towards earnings, which makes sense intuitively. Unlike shares markets, where you can continue to hold your share even if it dips 5%, in options you get access to expanded opportunity to make riches... and losses. An options trader betting on earnings is making a risky and therefore informed bet that he or she knows the outcome, versus a share trader who might be comfortable bagholding in the worst case scenario.
As I've mentioned largely in comments on my prior posts, earnings is a special case because, unlike popular misconceptions, stocks do not go up and down solely due to analyst expectations being meet, beat, or missed. In fact, stock prices move according to the consensus market expectation, which is a function of all the participants' FEPF on that ticker. This is why the price moves so dramatically - even if a stock beats, it might not beat enough to justify the high price tag (FSLY); even if a stock misses, it might have spectacular guidance or maybe the market just was assuming it would go bankrupt instead.
To look at the impact of NOPE and why it may play a role in post-earnings-announcement immediate price moves, let's review the following cases:
  1. Stock Meets/Exceeds Market Expectations (aka price goes up) - In the general case, we would anticipate post-ER market participants value the stock at a higher price, pushing it up rapidly. If there's a high absolute value of NOPE on said ticker, this should end up magnifying the positive move since:
a) If NOPE is high negative - This means a ton of put buying, which means a lot of those puts are now worthless (due to price decoherence). This means that to stay delta neutral, market makers need to close out their sold/shorted shares, buying them, and pushing the stock price up.
b) If NOPE is high positive - This means a ton of call buying, which means a lot of puts are now worthless (see a) but also a lot of calls are now worth more. This means that to stay delta neutral, market makers need to close out their sold/shorted shares AND also buy more shares to cover their calls, pushing the stock price up.
2) Stock Meets/Misses Market Expectations (aka price goes down) - Inversely to what I mentioned above, this should push to the stock price down, fairly immediately. If there's a high absolute value of NOPE on said ticker, this should end up magnifying the negative move since:
a) If NOPE is high negative - This means a ton of put buying, which means a lot of those puts are now worth more, and a lot of calls are now worth less/worth less (due to price decoherence). This means that to stay delta neutral, market makers need to sell/short more shares, pushing the stock price down.
b) If NOPE is high positive - This means a ton of call buying, which means a lot of calls are now worthless (see a) but also a lot of puts are now worth more. This means that to stay delta neutral, market makers need to sell even more shares to keep their calls and puts neutral, pushing the stock price down.
---
Based on the above two cases, it should be a bit more clear why NOPE is a measure of sensitivity to system perturbation. While we previously discussed it in the context of magnifying directional move, the truth is it also provides a directional bias to our "random" walk. This is because given a price move in the direction predicted by NOPE, we expect it to be magnified, especially in situations of price decoherence. If a stock price goes up right after an ER report drops, even based on one participant deciding to value the stock higher, this provides a runaway reaction which boosts the stock price (due to hedging factors as well as other participants' behavior) and inures it to drops.

NOPE and NOPE_MAD

I'm going to gloss over this section because this is more statistical methods than anything interesting. In general, if you have enough data, I recommend using NOPE_MAD over NOPE. While NOPE in theory represents a "real" quantity (net option delta over net share delta), NOPE_MAD (the median absolute deviation of NOPE) does not. NOPE_MAD simply answecompare the following:
  1. How exceptional is today's NOPE versus historic baseline (30 days prior)?
  2. How do I compare two tickers' NOPEs effectively (since some tickers, like TSLA, have a baseline positive NOPE, because Elon memes)? In the initial stages, we used just a straight numerical threshold (let's say NOPE >= 20), but that quickly broke down. NOPE_MAD aims to detect anomalies, because anomalies in general give you tendies.
I might add the formula later in Mathenese, but simply put, to find NOPE_MAD you do the following:
  1. Calculate today's NOPE score (this can be done end of day or intraday, with the true value being EOD of course)
  2. Calculate the end of day NOPE scores on the ticker for the previous 30 trading days
  3. Compute the median of the previous 30 trading days' NOPEs
  4. From the median, find the 30 days' median absolute deviation (https://en.wikipedia.org/wiki/Median_absolute_deviation)
  5. Find today's deviation as compared to the MAD calculated by: [(today's NOPE) - (median NOPE of last 30 days)] / (median absolute deviation of last 30 days)
This is usually reported as sigma (σ), and has a few interesting properties:
  1. The mean of NOPE_MAD for any ticker is almost exactly 0.
  2. [Lily's Speculation's Speculation] NOPE_MAD acts like a spring, and has a tendency to reverse direction as a function of its magnitude. No proof on this yet, but exploring it!

Using the NOPE to predict ER

So the last section was a lot of words and theory, and a lot of what I'm mentioning here is empirically derived (aka I've tested it out, versus just blabbered).
In general, the following holds true:
  1. 3 sigma NOPE_MAD tends to be "the threshold": For very low NOPE_MAD magnitudes (+- 1 sigma), it's effectively just noise, and directionality prediction is low, if not non-existent. It's not exactly like 3 sigma is a play and 2.9 sigma is not a play; NOPE_MAD accuracy increases as NOPE_MAD magnitude (either positive or negative) increases.
  2. NOPE_MAD is only useful on highly optioned tickers: In general, I introduce another parameter for sifting through "candidate" ERs to play: option volume * 100/share volume. When this ends up over let's say 0.4, NOPE_MAD provides a fairly good window into predicting earnings behavior.
  3. NOPE_MAD only predicts during the after-market/pre-market session: I also have no idea if this is true, but my hunch is that next day behavior is mostly random and driven by market movement versus earnings behavior. NOPE_MAD for now only predicts direction of price movements right between the release of the ER report (AH or PM) and the ending of that market session. This is why in general I recommend playing shares, not options for ER (since you can sell during the AH/PM).
  4. NOPE_MAD only predicts direction of price movement: This isn't exactly true, but it's all I feel comfortable stating given the data I have. On observation of ~2700 data points of ER-ticker events since Mar 2019 (SPY 500), I only so far feel comfortable predicting whether stock price goes up (>0 percent difference) or down (<0 price difference). This is +1 for why I usually play with shares.
Some statistics:
#0) As a baseline/null hypothesis, after ER on the SPY500 since Mar 2019, 50-51% price movements in the AH/PM are positive (>0) and ~46-47% are negative (<0).
#1) For NOPE_MAD >= +3 sigma, roughly 68% of price movements are positive after earnings.
#2) For NOPE_MAD <= -3 sigma, roughly 29% of price movements are positive after earnings.
#3) When using a logistic model of only data including NOPE_MAD >= +3 sigma or NOPE_MAD <= -3 sigma, and option/share vol >= 0.4 (around 25% of all ERs observed), I was able to achieve 78% predictive accuracy on direction.

Caveats/Read This

Like all models, NOPE is wrong, but perhaps useful. It's also fairly new (I started working on it around early August 2020), and in fact, my initial hypothesis was exactly incorrect (I thought the opposite would happen, actually). Similarly, as commenters have pointed out, the timeline of data I'm using is fairly compressed (since Mar 2019), and trends and models do change. In fact, I've noticed significantly lower accuracy since the coronavirus recession (when I measured it in early September), but I attribute this mostly to a smaller date range, more market volatility, and honestly, dumber option traders (~65% accuracy versus nearly 80%).
My advice so far if you do play ER with the NOPE method is to use it as following:
  1. Buy/short shares approximately right when the market closes before ER. Ideally even buying it right before the earnings report drops in the AH session is not a bad idea if you can.
  2. Sell/buy to close said shares at the first sign of major weakness (e.g. if the NOPE predicted outcome is incorrect).
  3. Sell/buy to close shares even if it is correct ideally before conference call, or by the end of the after-market/pre-market session.
  4. Only play tickers with high NOPE as well as high option/share vol.
---
In my next post, which may be in a few days, I'll talk about potential use cases for SPY and intraday trends, but I wanted to make sure this wasn't like 7000 words by itself.
Cheers.
- Lily
submitted by the_lilypad to thecorporation [link] [comments]

Subreddit Demographic Survey 2020 : The Results

2020 Childfree Subreddit Survey

1. Introduction

Once a year, this subreddit hosts a survey in order to get to know the community a little bit and in order to answer questions that are frequently asked here. Earlier this summer, several thousand of you participated in the 2020 Subreddit Demographic Survey. Only those participants who meet our wiki definition of being childfree's results were recorded and analysed.
Of these people, multiple areas of your life were reviewed. They are separated as follows:

2. Methodology

Our sample is redditors who saw that we had a survey currently active and were willing to complete the survey. A stickied post was used to advertise the survey to members.

3. Results

The raw data may be found via this link.
7305 people participated in the survey from July 2020 to October 2020. People who did not meet our wiki definition of being childfree were excluded from the survey. The results of 5134 responders, or 70.29% of those surveyed, were collated and analysed below. Percentages are derived from the respondents per question.

General Demographics

Age group

Age group Participants Percentage
18 or younger 309 6.02%
19 to 24 1388 27.05%
25 to 29 1435 27.96%
30 to 34 1089 21.22%
35 to 39 502 9.78%
40 to 44 223 4.35%
45 to 49 81 1.58%
50 to 54 58 1.13%
55 to 59 25 0.49%
60 to 64 13 0.25%
65 to 69 7 0.14%
70 to 74 2 0.04%
82.25% of the sub is under the age of 35.

Gender and Gender Identity

Age group Participants # Percentage
Agender 62 1.21%
Female 3747 73.04%
Male 1148 22.38%
Non-binary 173 3.37%

Sexual Orientation

Sexual Orientation Participants # Percentage
Asexual 379 7.39%
Bisexual 1177 22.93%
Heterosexual 2833 55.20%
Homosexual 264 5.14%
It's fluid 152 2.96%
Other 85 1.66%
Pansexual 242 4.72%

Birth Location

Because the list contains over 120 countries, we'll show the top 20 countries:
Country of birth Participants # Percentage
United States 2775 57.47%
United Kingdom 367 7.60%
Canada 346 7.17%
Australia 173 3.58%
Germany 105 2.17%
Netherlands 67 1.39%
India 63 1.30%
Poland 57 1.18%
France 47 0.97%
New Zealand 42 0.87%
Mexico 40 0.83%
Brazil 40 0.83%
Sweden 38 0.79%
Finland 31 0.64%
South Africa 30 0.62%
Denmark 28 0.58%
China 27 0.56%
Ireland 27 0.56%
Phillipines 24 0.50%
Russia 23 0.48%
90.08% of the participants were born in these countries.
These participants would describe their current city, town or neighborhood as:
Region Participants # Percentage
Rural 705 13.76
Suburban 2661 51.95
Urban 1756 34.28

Ethnicity

Ethnicity Participants # Percentage
African Descent/Black 157 3.07%
American Indian or Alaskan Native 18 0.35%
Arabic/Middle Eastern/Near Eastern 34 0.66%
Bi/Multiracial 300 5.86%
Caucasian/White 3946 77.09%
East Asian 105 2.05%
Hispanic/Latinx 271 5.29%
Indian/South Asian 116 2.27%
Indigenous Australian/Torres Straight IslandeMaori 8 0.16%
Jewish (the ethnicity, not religion) 50 0.98%
Other 32 0.63%
Pacific IslandeMelanesian 4 0.08%
South-East Asian 78 1.52%

Education

Highest Current Level of Education

Highest Current Level of Education Participants # Percentage
Associate's degree 233 4.55%
Bachelor's degree 1846 36.05%
Did not complete elementary school 2 0.04%
Did not complete high school 135 2.64%
Doctorate degree 121 2.36%
Graduated high school / GED 559 10.92%
Master's degree 714 13.95%
Post Doctorate 19 0.37%
Professional degree 107 2.09%
Some college / university 1170 22.85%
Trade / Technical / Vocational training 214 4.18%
Degree (Major) Participants # Percentage
Architecture 23 0.45%
Arts and Humanities 794 15.54%
Business and Economics 422 8.26%
Computer Science 498 9.75%
Education 166 3.25%
Engineering Technology 329 6.44%
I don't have a degree or a major 1028 20.12%
Law 124 2.43%
Life Sciences 295 5.77%
Medicine and Allied Health 352 6.89%
Other 450 8.81%
Physical Sciences 199 3.89%
Social Sciences 430 8.41%

Career and Finances

The top 10 industries our participants are working in are:
Industry Participants # Percentage
Information Technology 317 6.68%
Health Care 311 6.56%
Education - Teaching 209 4.41%
Engineering 203 4.28%
Retail 182 3.84%
Government 172 3.63%
Admin & Clerical 154 3.25%
Restaurant - Food Service 148 3.12%
Customer Service 129 2.72%
Design 127 2.68%
Note that "other", "I'm a student", "currently unemployed" and "I'm out of the work force for health or other reasons" have been disregarded for this part of the evaluation.
Out of the 3729 participants active in the workforce, the majority (1824 or 48.91%) work between 40-50 hours per week with 997 or 26.74% working 30-40 hours weekly. 6.62% work 50 hours or more per week, and 17.73% less than 30 hours.
513 or 10.13% are engaged in managerial responsibilities (ranging from Jr. to Sr. Management).
On a scale of 1 (lowest) to 10 (highest), the overwhelming majority (3340 or 70%) indicated that career plays a very important role in their lives, attributing a score of 7 and higher.
1065 participants decided not to disclose their income brackets. The remaining 4,849 are distributed as follows:
Income Participants # Percentage
$0 to $14,999 851 21.37%
$15,000 to $29,999 644 16.17%
$30,000 to $59,999 1331 33.42%
$60,000 to $89,999 673 16.90%
$90,000 to $119,999 253 6.35%
$120,000 to $149,999 114 2.86%
$150,000 to $179,999 51 1.28%
$180,000 to $209,999 25 0.63%
$210,000 to $239,999 9 0.23%
$240,000 to $269,999 10 0.25%
$270,000 to $299,999 7 0.18%
$300,000 or more 15 0.38%
87.85% earn under $90,000 USD a year.
65.82% of our childfree participants do not have a concrete retirement plan (savings, living will).

Religion and Spirituality

Faith Originally Raised In

There were more than 50 options of faith, so we aimed to show the top 10 most chosen beliefs.
Faith Participants # Percentage
Catholicism 1573 30.76%
None (≠ Atheism. Literally, no notion of spirituality or religion in the upbringing) 958 18.73%
Protestantism 920 17.99%
Other 431 8.43%
Atheism 318 6.22%
Agnosticism 254 4.97%
Anglicanism 186 3.64%
Judaism 77 1.51%
Hinduism 75 1.47%
Islam 71 1.39%
This top 10 amounts to 95.01% of the total participants.

Current Faith

There were more than 50 options of faith, so we aimed to show the top 10 most chosen beliefs:
Faith Participants # Percentage
Atheism 1849 36.23%
None (≠ Atheism. Literally, no notion of spirituality or religion currently) 1344 26.33%
Agnosticism 789 15.46%
Other 204 4.00%
Protestantism 159 3.12%
Paganism 131 2.57%
Spiritualism 101 1.98%
Catholicism 96 1.88%
Satanism 92 1.80%
Wicca 66 1.29%
This top 10 amounts to 94.65% of the participants.

Level of Current Religious Practice

Level Participants # Percentage
Wholly seculanon religious 3733 73.73%
Identify with religion, but don't practice strictly 557 11.00%
Lapsed/not serious/in name only 393 7.76%
Observant at home only 199 3.93%
Observant at home. Church/Temple/Mosque/etc. attendance 125 2.47%
Strictly observant, Church/Temple/Mosque/etc. attendance, religious practice/prayeworship impacting daily life 56 1.11%

Effect of Faith over Childfreedom

Figure 1

Effect of Childfreedom over Faith

Figure 2

Romantic and Sexual Life

Current Dating Situation

Status Participants # Percentage
Divorced 46 0.90%
Engaged 207 4.04%
Long term relationship, living together 1031 20.10%
Long term relationship, not living with together 512 9.98%
Married 1230 23.98%
Other 71 1.38%
Separated 18 0.35%
Short term relationship 107 2.09%
Single and dating around, but not looking for anything serious 213 4.15%
Single and dating around, looking for something serious 365 7.12%
Single and not looking 1324 25.81%
Widowed 5 0.10%

Childfree Partner

Is your partner childfree? If your partner wants children and/or has children of their own and/or are unsure about their position, please consider them "not childfree" for this question.
Partner Participants # Percentage
I don't have a partner 1922 37.56%
I have more than one partner and none are childfree 3 0.06%
I have more than one partner and some are childfree 35 0.68%
I have more than one partner and they are all childfree 50 0.98
No 474 9.26%
Yes 2633 51.46%

Dating a Single Parent

Would the childfree participants be willing to date a single parent?
Answer Participants # Percentage
No, I'm not interested in single parents and their ties to parenting life 4610 90.13%
Yes, but only if it's a short term arrangement of some sort 162 3.17%
Yes, whether for long term or short term, but with some conditions (must not have child custody, no kid talk, etc.), as long as I like them and long as we're compatible 199 3.89%
Yes, whether for long term or short term, with no conditions, as long as I like them and as long as we are compatible 144 2.82%

Childhood and Family Life

On a scale from 1 (very unhappy) to 10 (very happy), how would you rate your childhood?
Figure 3
Of the 5125 childfree people who responded to the question, 67.06% have a pet or are heavily involved in the care of someone else's pet.

Sterilisation

Sterilisation Status

Sterilisation Status Participants # Percentage
No, I am not sterilised and, for medical, practical or other reasons, I do not need to be 869 16.96%
No. However, I've been approved for the procedure and I'm waiting for the date to arrive 86 1.68%
No. I am not sterilised and don't want to be 634 12.37%
No. I want to be sterilised but I have started looking for a doctorequested the procedure 594 11.59%
No. I want to be sterilised but I haven't started looking for a doctorequested the procedure yet 2317 45.21%
Yes. I am sterilised 625 12.20%

Age when starting doctor shopping or addressing issue with doctor. Percentages exclude those who do not want to be sterilised and who have not discussed sterilisation with their doctor.

Age group Participants # Percentage
18 or younger 207 12.62%
19 to 24 588 35.85%
25 to 29 510 31.10%
30 to 34 242 14.76%
35 to 39 77 4.70%
40 to 44 9 0.55%
45 to 49 5 0.30%
50 to 54 1 0.06%
55 or older 1 0.06%

Age at the time of sterilisation. Percentages exclude those who have not and do not want to be sterilised.

Age group Participants # Percentage
18 or younger 5 0.79%
19 to 24 123 19.34%
25 to 29 241 37.89%
30 to 34 168 26.42%
35 to 39 74 11.64%
40 to 44 19 2.99%
45 to 49 1 0.16%
50 to 54 2 0.31%
55 or older 3 0.47%

Elapsed time between requesting procedure and undergoing procedure. Percentages exclude those who have not and do not want to be sterilised.

Time Participants # Percentage
Less than 3 months 330 50.46%
Between 3 and 6 months 111 16.97%
Between 6 and 9 months 33 5.05%
Between 9 and 12 months 20 3.06%
Between 12 and 18 months 22 3.36%
Between 18 and 24 months 15 2.29%
Between 24 and 30 months 6 0.92%
Between 30 and 36 months 2 0.31%
Between 3 and 5 years 40 6.12%
Between 5 and 7 years 25 3.82%
More than 7 years 50 7.65%

How many doctors refused at first, before finding one who would accept?

Doctor # Participants # Percentage
None. The first doctor I asked said yes 604 71.73%
One. The second doctor I asked said yes 93 11.05%
Two. The third doctor I asked said yes 54 6.41%
Three. The fourth doctor I asked said yes 29 3.44%
Four. The fifth doctor I asked said yes 12 1.43%
Five. The sixth doctor I asked said yes 8 0.95%
Six. The seventh doctor I asked said yes 10 1.19%
Seven. The eighth doctor I asked said yes 4 0.48%
Eight. The ninth doctor I asked said yes 2 0.24%
I asked more than 10 doctors before finding one who said yes 26 3.09%

Childfreedom

Primary Reason to Not Have Children

Reason Participants # Percentage
Aversion towards children ("I don't like children") 1455 28.36%
Childhood trauma 135 2.63%
Current state of the world 110 2.14%
Environmental (including overpopulation) 158 3.08%
Eugenics ("I have 'bad genes'") 57 1.11%
Financial 175 3.41%
I already raised somebody else who isn't my child 83 1.62%
Lack of interest towards parenthood ("I don't want to raise children") 2293 44.69%
Maybe interested for parenthood, but not suited for parenthood 48 0.94%
Medical ("I have a condition that makes conceiving/bearing/birthing children difficult, dangerous or lethal") 65 1.27%
Other 68 1.33%
Philosophical / Moral (e.g. antinatalism) 193 3.76%
Tokophobia (aversion/fear of pregnancy and/or chidlbirth) 291 5.67%
95.50% of childfree people are pro-choice, however only 55.93% of childfree people support financial abortion.

Dislike Towards Children

Figure 4

Working With Children

Work Participants # Percentage
I'm a student and my future job/career will heavily makes me interact with children on a daily basis 67 1.30%
I'm retired, but I used to have a job that heavily makes me interact with children on a daily basis 6 0.12%
I'm unemployed, but I used to have a job that heavily makes me interact with children on a daily basis 112 2.19%
No, I do not have a job that makes me heavily interact with children on a daily basis 4493 87.81%
Other 148 2.89%
Yes, I do have a job that heavily makes me interact with children on a daily basis 291 5.69%

4. Discussion

Child Status

This section solely existed to sift the childfree from the fencesitters and the non childfree in order to get answers only from the childfree. Childfree, as it is defined in the subreddit, is "I do not have children nor want to have them in any capacity (biological, adopted, fostered, step- or other) at any point in the future." 70.29% of participants actually identify as childfree, slightly up from the 2019 survey, where 68.5% of participants identified as childfree. This is suprising in reflection of the overall reputation of the subreddit across reddit, where the subreddit is often described as an "echo chamber".

General Demographics

The demographics remain largely consistent with the 2019 survey. However, the 2019 survey collected demographic responses from all participants in the survey, removing those who did not identify as childfree when querying subreddit specific questions, while the 2020 survey only collected responses from people who identified as childfree. This must be considered when comparing results.
82.25% of the participants are under 35, compared with 85% of the subreddit in the 2019 survey. A slight downward trend is noted compared over the last two years suggesting the userbase may be getting older on average. 73.04% of the subreddit identify as female, compared with 71.54% in the 2019 survey. Again, when compared with the 2019 survey, this suggests a slight increase in the number of members who identify as female. This is in contrast to the overall membership of Reddit, estimated at 74% male according to Reddit's Wikipedia page [https://en.wikipedia.org/wiki/Reddit#Users_and_moderators]. The ratio of members who identify as heterosexual remained consistent, from 54.89% in the 2019 survey to 55.20% in the 2020 survey.
Ethnicity wise, 77% of members identified as primarily Caucasian, consistent with the 2019 results. While the ethnicities noted to be missing in the 2019 survey have been included in the 2020 survey, some users noted the difficulty of responding when fitting multiple ethnicities, and this will be addressed in the 2021 survey.

Education level

As it did in the 2019 survey, this section highlights the stereotype of childfree people as being well educated. 2.64% of participants did not complete high school, which is a slight decrease from the 2019 survey, where 4% of participants did not graduate high school. However, 6.02% of participants are under 18, compared with 8.22% in the 2019 survey. 55% of participants have a bachelors degree or higher, while an additional 23% have completed "some college or university".
At the 2020 survey, the highest percentage of responses under the: What is your degree/major? question fell under "I don't have a degree or a major" (20.12%). Arts and Humanities, and Computer Science have overtaken Health Sciences and Engineering as the two most popular majors. However, the list of majors was pared down to general fields of study rather than highly specific degree majors to account for the significant diversity in majors studied by the childfree community, which may account for the different results.

Career and Finances

The highest percentage of participants at 21.61% listed themselves as trained professionals.
One of the stereotypes of the childfree is of wealth. However this is not demonstrated in the survey results. 70.95% of participants earn under $60,000 USD per annum, while 87.85% earn under $90,000 per annum. 21.37% are earning under $15,000 per annum. 1065 participants, or 21.10% chose not to disclose this information. It is possible that this may have skewed the results if a significant proportion of these people were our high income earners, but impossible to explore.
A majority of our participants work between 30 and 50 hours per week (75.65%) which is slightly increased from the 2019 survey, where 71.2% of participants worked between 30 and 50 hours per week.

Location

The location responses are largely similar to the 2019 survey with a majority of participants living in a suburban and urban area. 86.24% of participants in the 2020 survey live in urban and suburban regions, with 86.7% of participants living in urban and suburban regions in the 2019 survey. There is likely a multifactorial reason for this, encompassing the younger, educated skew of participants and the easier access to universities and employment, and the fact that a majority of the population worldwide localises to urban centres. There may be an element of increased progressive social viewpoints and identities in urban regions, however this would need to be explored further from a sociological perspective to draw any definitive conclusions.
A majority of our participants (57.47%) were born in the USA. The United Kingdom (7.6%), Canada (7.17%), Australia (3.58%) and Germany (2.17%) encompass the next 4 most popular responses. This is largely consistent with the responses in the 2019 survey.

Religion and Spirituality

For the 2020 survey Christianity (the most popular result in 2019) was split into it's major denominations, Catholic, Protestant, Anglican, among others. This appears to be a linguistic/location difference that caused a lot of confusion among some participants. However, Catholicism at 30.76% remained the most popular choice for the religion participants were raised in. However, of our participant's current faith, Aetheism at 36.23% was the most popular choice. A majority of 78.02% listed their current religion as Aetheist, no religious or spiritual beliefs, or Agnostic.
A majority of participants (61%) rated religion as "not at all influential" to the childfree choice. This is consistent with the 2019 survey where 62.8% rated religion as "not at all influential". Despite the high percentage of participants who identify as aetheist or agnostic, this does not appear to be related to or have an impact on the childfree choice.

Romantic and Sexual Life

60.19% of our participants are in a relationship at the time of the survey. This is consistent with the 2019 survey, where 60.7% of our participants were in a relationship. A notable proportion of our participants are listed as single and not looking (25.81%) which is consistent with the 2019 survey. Considering the frequent posts seeking dating advice as a childfree person, it is surprising that such a high proportion of the participants are not actively seeking out a relationship. Unsurprisingly 90.13% of our participants would not consider dating someone with children. 84% of participants with partners of some kind have at least one childfree partner. This is consistent with the often irreconcilable element of one party desiring children and the other wishing to abstain from having children.

Childhood and Family Life

Overall, the participants skew towards a happier childhood.

Sterilisation

While just under half of our participants wish to be sterilised, 45.21%, only 12.2% have been successful in achieving sterilisation. This is likely due to overarching resistance from the medical profession however other factors such as the logistical elements of surgery and the cost may also contribute. There is a slight increase from the percentage of participants sterilised in the 2019 survey (11.7%). 29.33% of participants do not wish to be or need to be sterilised suggesting a partial element of satisfaction from temporary birth control methods or non-necessity of contraception due to their current lifestyle practices. Participants who indicated that they do not wish to be sterilised or haven't achieved sterilisation were excluded from the percentages where necessary in this section.
Of the participants who did achieve sterilisation, a majority began the search between 19 and 29, with the highest proportion being in the 19-24 age group (35.85%) This is a marked increase from the 2019 survey where 27.3% of people who started the search were between 19-24. This may be due to increased education about permanent contraception or possibly due to an increase in instability around world events.
The majority of participants who sought out and were successful at achieving sterilisation, were however in the 25-29 age group (37.9%). This is consistent with the 2019 survey results.
The time taken between seeking out sterilisation and achieving it continues to increase, with only 50.46% of participants achieving sterilisation in under 3 months. This is a decline from the number of participants who achieved sterilisation in 3 months in the 2019 survey (58.5%). A potential cause of this decrease is to Covid-19 shutdowns in the medical industry leading to an increase in procedure wait times. The proportion of participants who have had one or more doctors refuse to perform the procedure has stayed consistent between the two surveys.

Childfreedom

The main reasons for people choosing the childfree lifestyle are a lack of interest towards parenthood and an aversion towards children which is consistent with the 2019 survey. Of the people surveyed 67.06% are pet owners or involved in a pet's care, suggesting that this lack of interest towards parenthood does not necessarily mean a lack of interest in all forms of caretaking. The community skews towards a dislike of children overall which correlates well with the 87.81% of users choosing "no, I do not have, did not use to have and will not have a job that makes me heavily interact with children on a daily basis" in answer to, "do you have a job that heavily makes you interact with children on a daily basis?". This is an increase from the 2019 survey.
A vast majority of the subreddit identifes as pro-choice (95.5%), a slight increase from the 2019 results. This is likely due to a high level of concern about bodily autonomy and forced birth/parenthood. However only 55.93% support financial abortion, aka for the non-pregnant person in a relationship to sever all financial and parental ties with a child. This is a marked decrease from the 2019 results, where 70% of participants supported financial abortion.
Most of our users realised that did not want children young. 58.72% of participants knew they did not want children by the age of 18, with 95.37% of users realising this by age 30. This correlates well with the age distribution of participants. Despite this early realisation of our childfree stance, 80.59% of participants have been "bingoed" at some stage in their lives.

The Subreddit

Participants who identify as childfree were asked about their interaction with and preferences with regards to the subreddit at large. Participants who do not meet our definition of being childfree were excluded from these questions.
By and large our participants were lurkers (72.32%). Our participants were divided on their favourite flairs with 38.92% selecting "I have no favourite". The next most favourite flair was "Rant", at 16.35%. Our participants were similarly divided on their least favourite flair, with 63.40% selecting "I have no least favourite". In light of these results the flairs on offer will remain as they have been through 2019.
With regards to "lecturing" posts, this is defined as a post which seeks to re-educate the childfree on the practices, attitudes and values of the community, particularly with regards to attitudes towards parenting and children, whether at home or in the community. A commonly used descriptor is "tone policing". A small minority of the survey participants (3.36%) selected "yes" to allowing all lectures, however 33.54% responded "yes" to allowing polite, respectful lectures only. In addition, 45.10% of participants indicated that they were not sure if lectures should be allowed. Due to the ambiguity of responses, lectures will continue to be not allowed and removed.
Many of our participants (36.87%) support the use of terms such as breeder, mombie/moo, daddict/duh on the subreddit, with a further 32.63% supporting use of these terms in context of bad parents only. This is a slight drop from the 2019 survey. In response to this use of the above and similar terms to describe parents remains permitted on this subreddit. However, we encourage users to keep the use of these terms to bad parents only.
44.33% of users support the use of terms to describe children such as crotchfruit on the subreddit, a drop from 55.3% last year. A further 25.80% of users supporting the use of this and similar terms in context of bad children only, an increase from 17.42% last year. In response to this use of the above and similar terms to describe children remains permitted on this subreddit.
69.17% of participants answered yes to allowing parents to post, provided they stay respectful. In response to this, parent posts will continue to be allowed on the subreddit. As for regret posts, which were to be revisited in this year's survey, only 9.5% of participants regarded them as their least favourite post. As such they will continue to stay allowed.
64% of participants support under 18's who are childfree participating in the subreddit with a further 19.59% allowing under 18's to post dependent on context. Therefore we will continue to allow under 18's that stay within the overall Reddit age requirement.
There was divide among participants as to whether "newbie" questions should be removed. An even spread was noted among participants who selected remove and those who selected to leave them as is. We have therefore decided to leave them as is. 73.80% of users selected "yes, in their own post, with their own "Leisure" flair" to the question, "Should posts about pets, travel, jetskis, etc be allowed on the sub?" Therefore we will continue to allow these posts provided they are appropriately flaired.

5. Conclusion

Thank you to our participants who contributed to the survey. This has been an unusual and difficult year for many people. Stay safe, and stay childfree.

submitted by Mellenoire to childfree [link] [comments]

Wall Street Week Ahead for the trading week beginning June 29th, 2020

Good Saturday afternoon to all of you here on StockMarket. I hope everyone on this sub made out pretty nicely in the market this past week, and is ready for the new trading week ahead.
Here is everything you need to know to get you ready for the trading week beginning June 29th, 2020.

Fragile economic recovery faces first big test with June jobs report in the week ahead - (Source)

The second half of 2020 is nearly here, and now it’s up to the economy to prove that the stock market was right about a sharp comeback in growth.
The first big test will be the June jobs report, out on Thursday instead of its usual Friday release due to the July 4 holiday. According to Refinitiv, economists expect 3 million jobs were created, after May’s surprise gain of 2.5 million payrolls beat forecasts by a whopping 10 million jobs.
“If it’s stronger, it will suggest that the improvement is quicker, and that’s kind of what we saw in May with better retail sales, confidence was coming back a little and auto sales were better,” said Kevin Cummins, chief U.S. economist at NatWest Markets.
The second quarter winds down in the week ahead as investors are hopeful about the recovery but warily eyeing rising cases of Covid-19 in a number of states.
Stocks were lower for the week, as markets reacted to rising cases in Texas, Florida and other states. Investors worry about the threat to the economic rebound as those states move to curb some activities. The S&P 500 is up more than 16% so far for the second quarter, and it is down nearly 7% for the year. Friday’s losses wiped out the last of the index’s June gains.
“I think the stock market is looking beyond the valley. It is expecting a V-shaped economic recovery and a solid 2021 earnings picture,” said Sam Stovall, chief investment strategist at CFRA. He expects large-cap company earnings to be up 30% next year, and small-cap profits to bounce back by 140%.
“I think the second half needs to be a ‘show me’ period, proving that our optimism was justified, and we’ll need to see continued improvement in the economic data, and I think we need to see upward revisions to earnings estimates,” Stovall said.
Liz Ann Sonders, chief investment strategist at Charles Schwab, said she expects the recovery will not be as smooth as some expect, particularly considering the resurgence of virus outbreaks in sunbelt states and California.
“Now as I watch what’s happening I think it’s more likely to be rolling Ws,” rather than a V, she said. “It’s not just predicated on a second wave. I’m not sure we ever exited the first wave.”
Even without actual state shutdowns, the virus could slow economic activity. “That doesn’t mean businesses won’t shut themselves down, or consumers won’t back down more,” she said.

Election ahead

In the second half of the year, the market should turn its attention to the election, but Sonders does not expect much reaction to it until after Labor Day. RealClearPolitics average of polls shows Democrat Joe Biden leading President Donald Trump by 10 percentage points, and the odds of a Democratic sweep have been rising.
Biden has said he would raise corporate taxes, and some strategists say a sweep would be bad for business, due to increased regulation and higher taxes. Trump is expected to continue using tariffs, which unsettles the market, though both candidates are expected to take a tough stance on China.
“If it looks like the Senate stays Republican than there’s less to worry about in terms of policy changes,” Sonders said. “I don’t think it’s ever as binary as some people think.”
Stovall said a quick study shows that in the four presidential election years back to 1960, where the first quarter was negative, and the second quarter positive, stocks made gains in the second half.
Those were 1960 when John Kennedy took office, 1968, when Richard Nixon won; 1980 when Ronald Reagan’s was elected to his first term; and 1992, the first win by Bill Clinton. Coincidentally, in all of those years, the opposing party gained control of the White House.

Stimulus

The stocks market’s strong second-quarter showing came after the Fed and Congress moved quickly to inject the economy with trillions in stimulus. That unlocked credit markets and triggered a stampede by companies to restructure or issue debt. About $2 trillion in fiscal spending was aimed at consumers and businesses, who were in sudden need of cash after the abrupt shutdown of the economy.
Fed Chairman Jerome Powell and Treasury Secretary Steven Mnuchin both testify before the House Financial Services Committee Tuesday on the response to the virus. That will be important as markets look ahead to another fiscal package from Congress this summer, which is expected to provide aid to states and local governments; extend some enhanced benefits for unemployment, and provide more support for businesses.
“So much of it is still so fluid. There are a bunch of fiscal items that are rolling off. There’s talk about another fiscal stimulus payment like they did last time with a $1,200 check,” said Cummins.
Strategists expect Congress to bicker about the size and content of the stimulus package but ultimately come to an agreement before enhanced unemployment benefits run out at the end of July. Cummins said state budgets begin a new year July 1, and states with a critical need for funds may have to start letting workers go, as they cut expenses.
The Trump administration has indicated the jobs report Thursday could help shape the fiscal package, depending on what it shows. The federal supplement to state unemployment benefits has been $600 a week, but there is opposition to extending that, and strategists expect it to be at least cut in half.
The unemployment rate is expected to fall to 12.2% from 13.3% in May. Cummins said he had expected 7.2 million jobs, well above the consensus, and an unemployment rate of 11.8%.
As of last week, nearly 20 million people were collecting state unemployment benefits, and millions more were collecting under a federal pandemic aid program.
“The magnitude here and whether it’s 3 million or 7 million is kind of hard to handicap to begin with,” Cummins said. Economists have preferred to look at unemployment claims as a better real time read of employment, but they now say those numbers could be impacted by slow reporting or double filing.
“There’s no clarity on how you define the unemployed in the Covid 19 environment,” said Chris Rupkey, chief financial economist at MUFG Union Bank. “If there’s 30 million people receiving insurance, unemployment should be above 20%.

This past week saw the following moves in the S&P:

(CLICK HERE FOR THE FULL S&P TREE MAP FOR THE PAST WEEK!)

Major Indices for this past week:

(CLICK HERE FOR THE MAJOR INDICES FOR THE PAST WEEK!)

Major Futures Markets as of Friday's close:

(CLICK HERE FOR THE MAJOR FUTURES INDICES AS OF FRIDAY!)

Economic Calendar for the Week Ahead:

(CLICK HERE FOR THE FULL ECONOMIC CALENDAR FOR THE WEEK AHEAD!)

Percentage Changes for the Major Indices, WTD, MTD, QTD, YTD as of Friday's close:

(CLICK HERE FOR THE CHART!)

S&P Sectors for the Past Week:

(CLICK HERE FOR THE CHART!)

Major Indices Pullback/Correction Levels as of Friday's close:

(CLICK HERE FOR THE CHART!

Major Indices Rally Levels as of Friday's close:

(CLICK HERE FOR THE CHART!)

Most Anticipated Earnings Releases for this week:

(CLICK HERE FOR THE CHART!)

Here are the upcoming IPO's for this week:

(CLICK HERE FOR THE CHART!)

Friday's Stock Analyst Upgrades & Downgrades:

(CLICK HERE FOR THE CHART LINK #1!)
(CLICK HERE FOR THE CHART LINK #2!)

When Will The Economy Recover?

The economy is moving in the right direction, as many economic data points are coming in substantially better than what the economists expected. From May job gains coming in more than 10 million higher than expected and retail sales soaring a record 18%, how quickly the economy is bouncing back has surprised nearly everyone.
“As good as the recent economic data has been, we want to make it clear, it could still take years for the economy to fully come back,” explained LPL Financial Senior Market Strategist Ryan Detrick. “Think of it like building a house. You get all the big stuff done early, then some of the small things take so much longer to finish; I’m looking at you crown molding.”
Here’s the hard truth; it might take years for all of the jobs that were lost to fully recover. In fact, during the 10 recessions since 1950, it took an average of 30 months for lost jobs to finally come back. As the LPL Chart of the Day shows, recoveries have taken much longer lately. In fact, it took four years for the jobs lost during the tech bubble recession of the early 2000s to come back and more than six years for all the jobs lost to come back after the Great Recession. Given many more jobs were lost during this recession, it could takes many years before all of them indeed come back.
(CLICK HERE FOR THE CHART!)
The economy is going the right direction, and if there is no major second wave outbreak it could surprise to the upside. Importantly, this economic recovery will still be a long and bumpy road.

Nasdaq - Russell Spread Pulling the Rubber Band Tight

The Nasdaq has been outperforming every other US-based equity index over the last year, and nowhere has the disparity been wider than with small caps. The chart below compares the performance of the Nasdaq and Russell 2000 over the last 12 months. While the performance disparity is wide now, through last summer, the two indices were tracking each other nearly step for step. Then last fall, the Nasdaq started to steadily pull ahead before really separating itself in the bounce off the March lows. Just to illustrate how wide the gap between the two indices has become, over the last six months, the Nasdaq is up 11.9% compared to a decline of 15.8% for the Russell 2000. That's wide!
(CLICK HERE FOR THE CHART!)
In order to put the recent performance disparity between the two indices into perspective, the chart below shows the rolling six-month performance spread between the two indices going back to 1980. With a current spread of 27.7 percentage points, the gap between the two indices hasn't been this wide since the days of the dot-com boom. Back in February 2000, the spread between the two indices widened out to more than 50 percentage points. Not only was that period extreme, but ten months before that extreme reading, the spread also widened out to more than 51 percentage points. The current spread is wide, but with two separate periods in 1999 and 2000 where the performance gap between the two indices was nearly double the current level, that was a period where the Nasdaq REALLY outperformed small caps.
(CLICK HERE FOR THE CHART!)
To illustrate the magnitude of the Nasdaq's outperformance over the Russell 2000 from late 1998 through early 2000, the chart below shows the performance of the two indices beginning in October 1998. From that point right on through March of 2000 when the Nasdaq peaked, the Nasdaq rallied more than 200% compared to the Russell 2000 which was up a relatively meager 64%. In any other environment, a 64% gain in less than a year and a half would be excellent, but when it was under the shadow of the surging Nasdaq, it seemed like a pittance.
(CLICK HERE FOR THE CHART!)

Share Price Performance

The US equity market made its most recent peak on June 8th. From the March 23rd low through June 8th, the average stock in the large-cap Russell 1,000 was up more than 65%! Since June 8th, the average stock in the index is down more than 11%. Below we have broken the index into deciles (10 groups of 100 stocks each) based on simple share price as of June 8th. Decile 1 (marked "Highest" in the chart) contains the 10% of stocks with the highest share prices. Decile 10 (marked "Lowest" in the chart) contains the 10% of stocks with the lowest share prices. As shown, the highest priced decile of stocks are down an average of just 4.8% since June 8th, while the lowest priced decile of stocks are down an average of 21.5%. It's pretty remarkable how performance gets weaker and weaker the lower the share price gets.
(CLICK HERE FOR THE CHART!)

Nasdaq 2% Pullbacks From Record Highs

It's hard to believe that sentiment can change so fast in the market that one day investors and traders are bidding up stocks to record highs, but then the next day sell them so much that it takes the market down over 2%. That's exactly what happened not only in the last two days but also two weeks ago. While the 5% pullback from a record high back on June 10th took the Nasdaq back below its February high, this time around, the Nasdaq has been able to hold above those February highs.
(CLICK HERE FOR THE CHART!)
In the entire history of the Nasdaq, there have only been 12 periods prior to this week where the Nasdaq closed at an all-time high on one day but dropped more than 2% the next day. Those occurrences are highlighted in the table below along with the index's performance over the following week, month, three months, six months, and one year. We have also highlighted each occurrence that followed a prior one by less than three months in gray. What immediately stands out in the table is how much gray shading there is. In other words, these types of events tend to happen in bunches, and if you count the original occurrence in each of the bunches, the only two occurrences that didn't come within three months of another occurrence (either before or after) were July 1986 and May 2017.
In terms of market performance following prior occurrences, the Nasdaq's average and median returns were generally below average, but there is a pretty big caveat. While the average one-year performance was a gain of 1.0% and a decline of 23.6% on a median basis, the six occurrences that came between December 1999 and March 2000 all essentially cover the same period (which was very bad) and skew the results. Likewise, the three occurrences in the two-month stretch from late November 1998 through January 1999 where the Nasdaq saw strong gains also involves a degree of double-counting. As a result of these performances at either end of the extreme, it's hard to draw any trends from the prior occurrences except to say that they are typically followed by big moves in either direction. The only time the Nasdaq wasn't either 20% higher or lower one year later was in 1986.
(CLICK HERE FOR THE CHART!)

Christmas in July: NASDAQ’s Mid-Year Rally

In the mid-1980s the market began to evolve into a tech-driven market and the market’s focus in early summer shifted to the outlook for second quarter earnings of technology companies. Over the last three trading days of June and the first nine trading days in July, NASDAQ typically enjoys a rally. This 12-day run has been up 27 of the past 35 years with an average historical gain of 2.5%. This year the rally may have begun a day early, today and could last until on or around July 14.
After the bursting of the tech bubble in 2000, NASDAQ’s mid-year rally had a spotty track record from 2002 until 2009 with three appearances and five no-shows in those years. However, it has been quite solid over the last ten years, up nine times with a single mild 0.1% loss in 2015. Last year, NASDAQ advanced a solid 4.6% during the 12-day span.
(CLICK HERE FOR THE CHART!)

Tech Historically Leads Market Higher Until Q3 of Election Years

As of yesterday’s close DJIA was down 8.8% year-to-date. S&P 500 was down 3.5% and NASDAQ was up 12.1%. Compared to the typical election year, DJIA and S&P 500 are below historical average performance while NASDAQ is above average. However this year has not been a typical election year. Due to the covid-19, the market suffered the damage of the shortest bear market on record and a new bull market all before the first half of the year has come to an end.
In the surrounding Seasonal Patten Charts of DJIA, S&P 500 and NASDAQ, we compare 2020 (as of yesterday’s close) to All Years and Election Years. This year’s performance has been plotted on the right vertical axis in each chart. This year certainly has been unlike any other however some notable observations can be made. For DJIA and S&P 500, January, February and approximately half of March have historically been weak, on average, in election years. This year the bear market ended on March 23. Following those past weak starts, DJIA and S&P 500 historically enjoyed strength lasting into September before experiencing any significant pullback followed by a nice yearend rally. NASDAQ’s election year pattern differs somewhat with six fewer years of data, but it does hint to a possible late Q3 peak.
(CLICK HERE FOR THE CHART!)
(CLICK HERE FOR THE CHART!)
(CLICK HERE FOR THE CHART!)

STOCK MARKET VIDEO: Stock Market Analysis Video for Week Ending June 26th, 2020

(CLICK HERE FOR THE YOUTUBE VIDEO!

STOCK MARKET VIDEO: ShadowTrader Video Weekly 6.28.20

(CLICK HERE FOR THE YOUTUBE VIDEO!)
Here are the most notable companies (tickers) reporting earnings in this upcoming trading week ahead-
  • $MU
  • $GIS
  • $FDX
  • $CAG
  • $STZ
  • $CPRI
  • $XYF
  • $AYI
  • $MEI
  • $UNF
  • $CDMO
  • $SCHN
  • $LNN
  • $CULP
  • $XELA
  • $KFY
  • $RTIX
  • $JRSH
(CLICK HERE FOR NEXT WEEK'S MOST NOTABLE EARNINGS RELEASES!)
(CLICK HERE FOR NEXT WEEK'S HIGHEST VOLATILITY EARNINGS RELEASES!)
(CLICK HERE FOR MOST NOTABLE EARNINGS RELEASES FOR THE NEXT 4 WEEKS!)
Below are some of the notable companies coming out with earnings releases this upcoming trading week ahead which includes the date/time of release & consensus estimates courtesy of Earnings Whispers:

Monday 6.29.20 Before Market Open:

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NONE.

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Micron Technology, Inc. $48.49

Micron Technology, Inc. (MU) is confirmed to report earnings at approximately 4:00 PM ET on Monday, June 29, 2020. The consensus earnings estimate is $0.71 per share on revenue of $5.27 billion and the Earnings Whisper ® number is $0.70 per share. Investor sentiment going into the company's earnings release has 71% expecting an earnings beat The company's guidance was for earnings of $0.40 to $0.70 per share. Consensus estimates are for earnings to decline year-over-year by 29.00% with revenue increasing by 10.07%. Short interest has increased by 7.6% since the company's last earnings release while the stock has drifted higher by 8.0% from its open following the earnings release to be 0.9% below its 200 day moving average of $48.94. Overall earnings estimates have been revised lower since the company's last earnings release. On Thursday, June 11, 2020 there was some notable buying of 46,037 contracts of the $60.00 call expiring on Friday, July 17, 2020. Option traders are pricing in a 4.6% move on earnings and the stock has averaged a 8.4% move in recent quarters.

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General Mills, Inc. $59.21

General Mills, Inc. (GIS) is confirmed to report earnings at approximately 7:00 AM ET on Wednesday, July 1, 2020. The consensus earnings estimate is $1.04 per share on revenue of $4.89 billion and the Earnings Whisper ® number is $1.10 per share. Investor sentiment going into the company's earnings release has 69% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 25.30% with revenue increasing by 17.50%. Short interest has decreased by 9.4% since the company's last earnings release while the stock has drifted higher by 2.7% from its open following the earnings release to be 7.8% above its 200 day moving average of $54.91. Overall earnings estimates have been revised higher since the company's last earnings release. On Wednesday, June 24, 2020 there was some notable buying of 8,573 contracts of the $60.00 call expiring on Friday, July 17, 2020. Option traders are pricing in a 6.6% move on earnings and the stock has averaged a 3.0% move in recent quarters.

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FedEx Corp. $130.08

FedEx Corp. (FDX) is confirmed to report earnings at approximately 4:00 PM ET on Tuesday, June 30, 2020. The consensus earnings estimate is $1.42 per share on revenue of $16.31 billion and the Earnings Whisper ® number is $1.65 per share. Investor sentiment going into the company's earnings release has 61% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 71.66% with revenue decreasing by 8.41%. Short interest has increased by 10.4% since the company's last earnings release while the stock has drifted higher by 43.9% from its open following the earnings release to be 7.6% below its 200 day moving average of $140.75. Overall earnings estimates have been revised lower since the company's last earnings release. On Thursday, June 25, 2020 there was some notable buying of 1,768 contracts of the $145.00 call expiring on Thursday, July 2, 2020. Option traders are pricing in a 4.6% move on earnings and the stock has averaged a 7.7% move in recent quarters.

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Conagra Brands, Inc. $32.64

Conagra Brands, Inc. (CAG) is confirmed to report earnings at approximately 7:30 AM ET on Tuesday, June 30, 2020. The consensus earnings estimate is $0.66 per share on revenue of $3.24 billion and the Earnings Whisper ® number is $0.69 per share. Investor sentiment going into the company's earnings release has 66% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 83.33% with revenue increasing by 23.99%. Short interest has decreased by 38.3% since the company's last earnings release while the stock has drifted higher by 6.3% from its open following the earnings release to be 6.4% above its 200 day moving average of $30.68. Overall earnings estimates have been revised higher since the company's last earnings release. On Thursday, June 11, 2020 there was some notable buying of 3,239 contracts of the $29.00 put expiring on Thursday, July 2, 2020. Option traders are pricing in a 4.7% move on earnings and the stock has averaged a 10.8% move in recent quarters.

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Constellation Brands, Inc. $168.99

Constellation Brands, Inc. (STZ) is confirmed to report earnings at approximately 7:30 AM ET on Wednesday, July 1, 2020. The consensus earnings estimate is $1.91 per share on revenue of $1.97 billion and the Earnings Whisper ® number is $2.12 per share. Investor sentiment going into the company's earnings release has 53% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 13.57% with revenue decreasing by 13.69%. Short interest has increased by 20.8% since the company's last earnings release while the stock has drifted higher by 25.2% from its open following the earnings release to be 5.2% below its 200 day moving average of $178.34. Overall earnings estimates have been revised lower since the company's last earnings release. On Tuesday, June 9, 2020 there was some notable buying of 888 contracts of the $195.00 call expiring on Friday, October 16, 2020. Option traders are pricing in a 3.1% move on earnings and the stock has averaged a 5.7% move in recent quarters.

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Capri Holdings Limited $14.37

Capri Holdings Limited (CPRI) is confirmed to report earnings at approximately 6:30 AM ET on Wednesday, July 1, 2020. The consensus earnings estimate is $0.32 per share on revenue of $1.18 billion and the Earnings Whisper ® number is $0.34 per share. Investor sentiment going into the company's earnings release has 39% expecting an earnings beat The company's guidance was for earnings of $0.68 to $0.73 per share. Consensus estimates are for earnings to decline year-over-year by 49.21% with revenue decreasing by 12.20%. Short interest has increased by 35.1% since the company's last earnings release while the stock has drifted lower by 56.7% from its open following the earnings release to be 44.0% below its 200 day moving average of $25.67. Overall earnings estimates have been revised lower since the company's last earnings release. On Thursday, June 4, 2020 there was some notable buying of 11,042 contracts of the $17.50 put expiring on Friday, August 21, 2020. Option traders are pricing in a 10.8% move on earnings and the stock has averaged a 6.7% move in recent quarters.

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X Financial $0.92

X Financial (XYF) is confirmed to report earnings at approximately 5:00 PM ET on Tuesday, June 30, 2020. The consensus earnings estimate is $0.09 per share. Investor sentiment going into the company's earnings release has 25% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 55.00% with revenue increasing by 763.52%. Short interest has increased by 1.0% since the company's last earnings release while the stock has drifted lower by 1.2% from its open following the earnings release to be 37.7% below its 200 day moving average of $1.47. Overall earnings estimates have been unchanged since the company's last earnings release. The stock has averaged a 4.9% move on earnings in recent quarters.

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Acuity Brands, Inc. $84.45

Acuity Brands, Inc. (AYI) is confirmed to report earnings at approximately 8:40 AM ET on Tuesday, June 30, 2020. The consensus earnings estimate is $1.14 per share on revenue of $809.25 million and the Earnings Whisper ® number is $1.09 per share. Investor sentiment going into the company's earnings release has 42% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 51.90% with revenue decreasing by 14.60%. Short interest has increased by 48.5% since the company's last earnings release while the stock has drifted higher by 2.4% from its open following the earnings release to be 23.4% below its 200 day moving average of $110.25. Overall earnings estimates have been revised lower since the company's last earnings release. Option traders are pricing in a 9.2% move on earnings and the stock has averaged a 8.2% move in recent quarters.

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Methode Electronics, Inc. $30.02

Methode Electronics, Inc. (MEI) is confirmed to report earnings at approximately 7:00 AM ET on Tuesday, June 30, 2020. The consensus earnings estimate is $0.77 per share on revenue of $211.39 million. Investor sentiment going into the company's earnings release has 45% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 24.19% with revenue decreasing by 20.53%. Short interest has increased by 6.2% since the company's last earnings release while the stock has drifted lower by 1.7% from its open following the earnings release to be 9.0% below its 200 day moving average of $32.97. Overall earnings estimates have been revised lower since the company's last earnings release. Option traders are pricing in a 18.4% move on earnings and the stock has averaged a 8.1% move in recent quarters.

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UniFirst Corporation $170.54

UniFirst Corporation (UNF) is confirmed to report earnings at approximately 8:00 AM ET on Wednesday, July 1, 2020. The consensus earnings estimate is $1.17 per share on revenue of $378.28 million and the Earnings Whisper ® number is $1.25 per share. Investor sentiment going into the company's earnings release has 44% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 52.44% with revenue decreasing by 16.63%. Short interest has decreased by 2.7% since the company's last earnings release while the stock has drifted higher by 14.1% from its open following the earnings release to be 8.4% below its 200 day moving average of $186.14. Overall earnings estimates have been revised lower since the company's last earnings release. The stock has averaged a 7.0% move on earnings in recent quarters.

(CLICK HERE FOR THE CHART!)

DISCUSS!

What are you all watching for in this upcoming trading week?
I hope you all have a wonderful weekend and a great trading week ahead StockMarket.
submitted by bigbear0083 to StockMarket [link] [comments]

A proposal to eliminate the spread of COVID-19 in Ireland

This is a long one. There is no TL;DR, but Google tells me it should take about 10 minutes to read. Or, you can skip to The Plan - Summary if you want the bullet points.
But why should you give this any time at all?
My background is in data analysis. Making sense of numbers is what I do for a living. I have been studying COVID-19 since I was locked down in March and the experience has been frustrating in equal measure. The difference between what was happening on the ground, and the story that the media told was genuinely alarming. The government / NPHET never even tried to stop the virus getting into the country, and no one held them to account for their (non)decisions. The disastrous consequences are all around us, and much of it was preventable.
Six months later, and the country has barely moved on. The ‘experts’ have no goals and little control over the virus. The media frame every issue as a crass binary choice between more or less restrictions and are otherwise happy just to have people to point their fingers at. The government / NPHET has nothing to offer the people, other than admonishments to do better and repeated cycle of restrictions.
Meanwhile students, artists, the over 70s, small business owners, the entire events and hospitality industries, and regular people who cannot WFH have been left swinging in the wind. Some have been evicted, others are relying on drugs to get by. This situation is not just a problem for one or two parts of our society: this is a widespread degradation of our quality of life. If I can do anything to help, I feel obliged to try.

Context
As I see it, we have three choices:
I won’t argue over technocratic definitions like ‘elimination’, ‘eradication’ or ‘suppression’. These distinctions are semantic in an environment of oppressive civic restrictions, mass unemployment, waves of business closures, and general misery. Whatever gets us to a place where we can live our lives as normal (or close enough), and the public health infrastructure can take care of the virus, that’s what I’m aiming for.
This proposal cannot work without public support. No proposal can work without public support. Public adherence is the single most important variable in the equation, yet it is the one that the politicians and the media and the ‘experts’ have ignored. FG burned through a lot of goodwill in the first lockdown (and money, and resources, and lives…). Instead of vilifying people who aren’t adhering to the rules, policymakers need to recognise the sacrifices that the people made (which were subsequently squandered) and they need to earn that trust back.
This proposal cannot work without support from the North. That doesn’t mean that we need to convince them to adopt our plan. It means we need to convince them that the goal is worthwhile and achievable. From there we can work together to coordinate our policies. Managing our own affairs with competence, would be a good start. Picking up the phone to talk to them, instead of trying to browbeat them through the media, would also help.
Irrespective of your goals or beliefs, some facts are certain: there will be lockdowns, there will be government spending to support the economy, and the virus will demand public health resources. All of that will happen in the coming months and years, whether we have a plan or not. The question is whether those resources are used to solve the problem, or whether they are wasted on a plan that keeps us going around in circles.
So yes, there will be lockdowns in this proposal, but they will not be FG lockdowns i.e. lock them down and throw away the key. Through intelligent policies and a greater mobilisation of resources, we can do so much more with our lockdowns to reduce the burden on the people and make their experience more tolerable. Indeed, that trade-off always exists in public policy: better policymaking = happier people. Which is why the politicians usually get the blame, and rightly so.
We need to move to a more ‘war time’ mindset. Not because we need a shared enemy to unite us, but because we need to mobilise every possible resource at our disposal and focus it on the single most important issue affecting us all. We need more tests, we need vehicles for mobile testing units, we need facilities for quarantines. Wherever there is spare capacity, we need to find a way to put it to good use. We need to take most of the power away from the narrow-minded medics, and get the rest of our society and our civic infrastructure involved in planning e.g. community representatives, legal experts, business leaders, An Garda, the army etc.
People want to invest in their communities, they want to help their friends and neighbours. There are people all over the country who would rather be volunteering as part of a national plan to get rid of COVID-19, than to be sitting at home on the PUP, going crazy listening to the ‘experts’ – who failed to prevent this – talk about more lockdowns. We need to harness that latent energy and build it into the plan.
One of the most important factors that is within our control, is the degree to which policymakers communicate with the people. And I mean real communication, not press releases or attention-seeking speeches from the other side of the world. We need to talk to the people, listen to them, answer their questions, take their feedback on board. The people aren’t stupid. They know a good plan when they see it – which is why few are paying attention to the ‘Living With The Virus’ stuff – and they have valuable information that can help make that plan work.
Underlying these points is a need to create intelligent rules, and to enforce them strictly. Strict does not mean harsh. Strict enforcement is not authoritarianism, and it is not an invitation to a fight; it is simply administrative competence. In the context of a contagious outbreak, administrative competence is the difference between life and death.
I’ll finish this section with the caveat that all parameters are suggestions or placeholders. The exact numbers will depend on resources, on more data and further analysis, and on input from communities and other stakeholders – all of which is within our control.

The Plan – Summary
Like any problem in life, if you can’t solve it directly, you break it down into smaller, less complex parts.
Instead of putting the whole country into lockdown and trying to eradicate the virus from the whole island at the same time – a miserable experience for all – we should go county by county until the job is done. We seal off a county, flood it with resources, clear it of COVID-19, and then let it reopen as normal. We repeat the process for neighbouring counties and then combine them when they are cleared, to create a larger ‘Cleared Zone’. The process continues and the Cleared Zone keeps growing until it covers the whole island.
This approach allows us to focus our resources on one area at a time (nurses, doctors, tests, volunteers etc) instead of spreading them over the whole country. We can be more comprehensive in our testing and quarantining measures, and more confident in our plans. Short, sharp, strict lockdowns work best.
By maximising the ratio of resources to population, we also lower the burden on the people. In particular, we minimise the amount of time that people spend in lockdown, and the less time they spend in lockdown, the more likely the plan is to work.
This structured approach also makes it easier for us to measure our progress and make reliable forecasts. We can allocate our resources more efficiently and plan our responses more effectively. Observers can watch our progress and judge for themselves whether it is a good idea (i.e. politicians in the North and / or protestors in Dublin).
Perhaps most important of all, the structure makes it easier to explain the idea to the people and get buy-in before anything happens. We can outline the plan, explain how it works, explain how it compares to the alternatives, and then give them realistic estimates of what would be required and how long it would take. Then we can hear their feedback and take the conversation and planning from there.
I have heard any people talking about elimination and ZeroCovid, but do any of them have a plan for getting to zero? Or a plan to get the people on board?
Step 1: More structure and responsibility from leaders
Step 2: Less uncertainty, easier decisions, better outcomes, less stress for everyone
Step 3: Profit. Elimination.

The Plan – Implementation
We isolate a county and lock it down for an initial 3 weeks. An Garda man the county borders. They are supported by the army, who provide boots on the ground so that An Garda aren’t stretched. Most routes are closed off so that all essential travel goes through a few well-manned checkpoints. If we do a good job with planning and communication, there won’t be much work to do.
We test systemically high-risk households and high-risk individuals early and often i.e. large households and essential workers. With help from local volunteers, medics screen as many people as possible every day. We use multiple measures and repeated applications to improve the quality of our results. We want to identify and remove cases at the earliest possible point, both to reduce the chance of further infection, and to protect the individual’s health.
Low risk confirmed cases (young / healthy) go to a safe and comfortable quarantine. Local hotels and guest houses could be used, ideally before we invest in building quarantine facilities. Local taxis, kitted out with extra protective equipment, could take them there. High risk confirmed cases (older / comorbidities) go by ambulance to local medical facilities as required.
During this period, we work with local politicians, community leaders, residence associations etc to ensure that everyone is looked after (in reality, these conversations will have started weeks before). We get our neighbourhoods communicating, looking out for each other, making sure they’ve got enough food or heating or whatever else they need. Local volunteers and taxi drivers can do odd jobs like sending packages, collecting prescriptions, lifting heavy stuff, or just checking in on people. If it is feasible, we can even invite local artists to play gigs for people in their streets or apartments.
Towards the end of the second week, we begin a mass testing program with the ultimate goal of testing every person in the county (scale depends on resources). Once we have completed the tests and cleared the confirmed cases into quarantine, we can begin a slow, staggered opening process. We must be especially conservative at this point to ensure no slippage.
When one county is clear, we move to the next one, and repeat the process. When we have cleared two bordering counties, we can join them together in a bigger Cleared Zone and the process continues from there. Eventually the Cleared Zone covers the whole country, except Dublin (or more realistically, the Pale).
What would the other counties do while they wait for their turn? I’m assuming that, they would be doing whatever the ‘Living With The Virus’ plan dictates. This proposal succeeds in line with what happens in the sealed off zones, so I am more concerned with them. However, it would speed up the process if the bordering counties could be encouraged to get a head start. If the plan is going successfully, I’m confident they would.
With its population density and its complexity, Dublin / the Pale will be the last county to be cleared. However, given that every other county would be cleared by that point, and with so much effort having been put in, it might make more sense just to burn Dublin down. We could go with a concrete mausoleum as per Chernobyl, but it might be easier and quicker if we just raised the city and started from scratch. The country needs to rebalance, so it’d be two birds with one stone.
Or maybe we call that plan B. Dublin’s plan A would follow the same principles as for the rest of the country. Break it into smaller parts, focus resources on one area at a time, use layers of risk measures where precision isn’t an option, and get cases as early as possible, using whatever resources available. By that stage the rest of the country would be clear and the demand for medical resources low. We would have learned a lot along the way, and we would have plenty of ammo to throw at the problem.
In general, the more resources we have, the faster we can move. The county by county approach that I have outlined above is too slow. With greater resources, we can increase the number of counties that are being cleared at any one time. One option is to work by province. Another would be to define the zones with respect to observed travel routes, in order to reduce the risk of leakage and reduce the inconvenience on local communities.
At the end of the day, lines have to be drawn somewhere, and some people will inevitably lose out. The better we communicate with people in advance, the lower the burden on the people and the more of these problems we can avoid.
Following on from that, one of the skills we need to take from this crisis is the ability to isolate and quarantine regions. Whether it is a city, a town, a county, a specific building, or even the entire country, we need to be able to seal it off and control movement in and out. This is an essential tool for outbreak management – whatever the outbreak and whatever the disease.
The same goes for individuals. We need to be able to create and operate safe, comfortable, and effective quarantines, and to do so at short notice. It should be a matter of national embarrassment that FG and NPHET couldn’t even organise a quarantine in a pandemic.
The whole process might take 3 to 4 months. That means we would have cut off all non-essential air travel for that time, but it doesn’t mean the whole country is in lockdown for 3 or 4 months. The lockdown is staggered, and the individual’s experience will depend on their location and their place in the ‘queue’.
The first group of counties to go into lockdown will also be the first to come out. Once they have eliminated the spread of the virus, they will return to a normal, although somewhat isolated, society. The experience steadily improves as more and more counties join them in the Cleared Zone (or steadily deteriorates, depending on your county pride).
While the first group is in lockdown, the rest of the country continues as normal i.e. living with the virus. Everyone watches as the first group goes through its lockdown (just think of the #banter). Several weeks later, as the first group is opening up, the second group is preparing to go in to lockdown. As the second group comes out, the third group goes in etc etc and the staggered lockdowns roll like a wave across the country.
Every county goes from Living With The Virus -> intelligent lockdown (needs a better name) -> Cleared Zone. The earlier you are in the queue, the less time you spend Living With The Virus and the more time you spend in the Cleared Zone. The individual would only be in a strict lockdown for a matter of weeks, maybe 3-6 depending on the complexity of the region and the resources available. For counties with smaller populations that have shown that they can do a good lockdown, it will be quicker. For Dublin, it will be slower.

Strengths
I think this proposal has a lot of strengths. It’s a plan, for a start. We haven’t had a plan since this thing began (the FG lockdown wasn’t a plan – it was the inevitable consequence of not having a plan). The leaders take more responsibility to lower the burden on the people, it mobilises idle resources, and it fosters communication and community across the country.
These are three strengths that I want to emphasise.
1 It provides clarity
This might be the most important point.
Uncertainty is painful. Uncertainty is a cost. Even if the bad thing is unlikely to happen, just the fact that it is a risk, or that it could happen means that you live with a cloud over your head. Suffering is bad enough on its own, but suffering for an unknown length of time is torture. And if that period is determined at the whim of a politician or an ‘expert’, that is a recipe for society-wide anger and even civil disorder.
With this proposal, we can forecast the length of the period of lockdown with greater accuracy. The people will be able to understand what is being asked of them. We can make plans around resources required versus those available. The economists can make forecasts. Businesses can plan their finances. The people can plan their weddings, book their holidays, get back to training, sign up for courses, and have things to look forward to.
At the end of the day, any successful proposal must remove the uncertainty and provide meaningful clarity to households and businesses.
2 Never let a crisis go to waste
This plan will require tools and capabilities like rapid local testing, safe quarantines, rapid isolation of towns and regions, emergency decision-making frameworks etc. If we don’t have a capability, then we need to build it. When people say ‘never let a crisis go to waste’ this is what they mean: you build the tools in the crisis that will help you protect yourself from the next one.
Nature works the same way. You lift weights until the muscle fibres tear, then they grow back stronger. We build aerobic endurance by pushing ourselves to a limit, then our body naturally reacts to increase the limit. A vaccine works similarly by stimulating antibodies for the disease. Well, we need a civic emergency vaccine for Ireland. These tools are the antibodies that will protect us next time. The sooner we build them, the better. Now is the time, not later.
3 It's the only way we can protect the economy
The risk to the economy isn’t the next few months of revenue. We can borrow to cover lost income in the short run. The real risk is a wave of defaults that precipitates a financial crisis.
As more individuals and businesses are put under financial pressure, more borrowers will default on their debts. But one man’s debt is another man’s asset, so as the borrowers default, the lender’s financial situation also deteriorates. Defaults are contagious, and if a wave of defaults threatens a major lender, the entire financial system will be at risk.
Only an elimination plan can protect the economy. Along with the virus and the uncertainty it creates, we need to eliminate the risk of financial contagion.

Weaknesses
Could ya be arsed

The End Goal
Think about what’s on the other side of this…
This is a massive challenge – the kind that defines a nation. However you think of your community, this would give you something to be proud of for generations. It would be like Italia ’90, except 10 times bigger, because we would be the players, we would be the ones making it happen.
We’d become the first country in Europe to eliminate the virus. And of all the countries in the world, we’d be doing it from the largest deficit too. Those Taiwanese and Kiwis made it easy for themselves with their preparation and their travel restrictions and their competent leaders. Our challenge is much greater than theirs, but they show us what is possible.
Have you ever wanted to scoff at the Germans for being disorganised? Wouldn’t you love to have a reason to mock the Danes? Aren’t you sick of hearing about New Zealand? Let’s make the Kiwis sick of hearing about the Irish!
If we take this challenge on, the world’s media will be on us. The FT, the Economist, the NYT, the Guardian, Monacle, Wired, the New Scientist, China Daily, RT, Good Housekeeping, Horse and Hound, PornHub… all of these international media empires would be tracking our progress, interviewing key people, reporting daily, willing us on. The world is desperate for good news, and we can be the ones to give it to them.
We would become a model for other nations to follow. They would take the Irish model and adapt it to their own situation. Instead of us copying other nations, they would be copying us. Instead of a pat on the head for the diddy little Irish fellas, we would be literally LEADING THE WORLD.
Back at home, we get our lives back, and society can breathe again, free of restrictions. The over 70s come out of hibernation. The students go back to university. The protests stop because people go back to work and we announce an inquiry into what exactly happened in February and March. The pubs go back to being pubs. Our hospitality industry is taken off life support. The tidal wave of bankruptcies is avoided. We can play sport and celebrate the wins. We stop talking about things we can or can't do. Just imagine that first session... And imagine how good it would feel knowing that you had worked for it, and knowing that you had set the nation on a better path for generations to come...
I think it’s worth a lash! Don’t you?
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Binary options trading has gained immense popularity around the globe since 2008. Investors and other traders who want to invest in equities, shares, commodities or currencies have taken to practicing binary options trading largely. A ‘binary’ trade is so-called as there are only two options available to the investor to choose from. In a binary trade, the investor places a trade that holds ... Binary Option Define if you put all your eggs in one basket, you run the risk of losing everything. Thus, as with everything else, you should spread Binary Option Define your risk over a number of Binary Option Robots, to maximise potential profit and prevent loss. Each one of the Binary Option Robot suggested in Binary Option Define Binary Options Range Trading Strategy All markets and all time frames see price ranges occurring, and this makes range trading one of the most popular methods in binary options trading. A price range occurs when sellers and buyers experience indecision, with neither group being able to push an asset’s price past a certain low and a certain high point. Payout: In Binary Options trading, Payout refers to the profit defined for a winning trade. It is regularly shown with percentages. For example 80% and it means that we receive the profit equal to 80% of our initial bet size if our prediction is correct. Consider that the payout is paid on top of the initial investment. In other words, a winner will receive 100% of the initial investment+ 80% ... Options Trading Define minutes/hours after the start (if less than one day in duration), or at the end of the trading Options Trading Define day (if one day or more in duration). Read Review. Pamela L. 2020-02-04 02:28:52 GMT. More Charts. AUD/JPY 5 Min; AUD/USD 5 Min; BTC/USD 5 Min; EUR/USD 5 Min ; USD/CHF 5 Min; Reply. You Must Be Logged In To Vote 0 You Must Be Logged In To Vote Reply. Log ... Are you going to trade binary options, stocks, forex, futures, or a combination? Each has advantages and disadvantages; pick your markets(s) so you can create a plan for that market(s). What are your objectives? Why are you trading? Simple saying you want to make more money isn’t clear enough. Define what you want to make, and why–buy a car, buy a house, pay for kids school, etc. Your ... People have been trading binary options for decades, but this unique type of trading became available to the public thanks to the Internets development. Nowadays, anyone who has enough knowledge and money to invest can start trading binary options in order to turn their knowledge into profit. Many of you have probably only recently heard of the term ‘binary options trading’ and this ... Binary options trading is a high risk investment tool. It may not be suitable for every investor. None of the information on these pages should be considered as financial advice. It may not be suitable for every investor. Binary Options Trading Binary options trading is a method of earning money that became available for everyone through the help of information technologies, particularly the Internet. Among other types of income in the global Internet, financial trading can be allocated, because it is trading on the stock exchange. This kind of financial trading favorably differs from... Are you also still doubting whether binary options trading is gambling or not? Let us answer all your questions in this article. Binary options trading is a hot discussion topic anywhere in the world. There is a lot of information out there and it is difficult to make sense of it all. And the truth

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Nadex Binary Options Strategies - How To Define Reversals ...

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