The Most Important Technical Indicators For Binary Options

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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.
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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
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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]

I created a mathematically optimal team generator!

Hi all,

I've been playing FPL for a few years now, and by no means am I an expert. However, I like math and particularly optimization problems. And a few days ago I thought to use my math knowledge for something useful.

My goal was to start from some metric that predicts the amount of points a player will score (either in the next gameweek, or over the whole season). From that metric, I wanted to generate the mathematically optimal team, aka choose the 15 players that will give me the most points, while staying within budget. I realized this is a constrained knapsack problem, which can be solved by dedicated solvers as long as the optimization problem is properly defined. Note that while I make a big assumption by choosing some metric from which I start, the solver actually finds the most optimal team, without any prior assumptions about best formation, budget spread, etc!

(Warning: from this point onward it gets kinda math-y, so turn back or skip ahead to the results if that's not your thing)

MATH

So first, the optimization variable needed to be defined. For this purpose I introduced a binary variable x which is basically a vector of all players in the game, where a value of 1 indicates that player is part of our dream team and a 0 means it's not.

Secondly, an objective function needs to be defined, which is what we want to maximize. In our case, this is the total expected points our dreamteam will score. I included double captain points and reduced points for bench players here. The objective function is linear, which is nice since it is convex (an important property which makes solving the problem much easier, and is even required for most solvers).

Lastly are the constraints. Obviously, there is the 100M budget constraint. Then we also want the required amount of goalkeepers, defenders, midfielders and forwards. Then we need to keep in mind the formation constraints, and lastly are the max 3 players per club constraints. Luckily, these are all linear (so convex) constraints.

I solved this problem using CVX for MATLAB, particularly with the Gurobi solver since it allows mixed integer programs. It tries to find the optimal variable x* which maximizes the objective function while staying within the constraints. And amazingly, it actually comes up with solutions!

RESULTS
So like I said before, I need to start from some metric that indicates how many points a player will score (if you have any recommendations, let me know!). For a lack of better options, I chose two different metrics:

  1. The total points scored by the player last year
  2. The expected points scored by the player in the next gameweek (ep_next in the FPL API, for fellow nerds)

Obviously, both metrics are not perfect. The first one doesn't take into account transfers, promoted teams, injuries, fixtures, position changes etc. However, it should work decent for making a set-and-forget team with proven PL players.

The second metric seems to have a problem with overrating bench players of top PL teams such as Ozil, Minamino, etc. I'm not really sure why, but it's a metric taken directly from FPL with undisclosed underlying math so it's not my problem. Also, keep in mind that since the first gameweek does not feature City/Utd/Burnley/Villa players, this metric predicts them to score 0 points so they won't feature in the optimal team.

Team 1: Last year's dreamteam
Bench:

Team 2: Next week's dreamteam
Bench:

Both teams cost exactly 100M.

At first glance, there are some obvious flaws with both teams, but most of them are because the metric used as input is flawed, as I explained before. Lundstram is obviously a much worse choice this year due to various reasons, and Team 2 has some top 6 players which are very much not nailed.

However. What I think is interesting is that both teams have only 2 starting midfielders. This despite the trend of people stacking premium midfielders. On the other hand, premium defenders seem to be very good value, and the importance of TAA and Robertson is underlined. Similarly, near-premium forwards in the 7.5-10 price range seem to be a good choice.

CONCLUSION
I'm quite content with my optimal team generator. Using it, I don't need to use vague value metrics such as VAPM. The input can be any metric which relates simply to how many points a player will score. Choices about relative value of e.g. defenders against midfielders, formation, budget spread etc. are all taken out of my hands with this team generator. The team that is generated is only as good as the metric used as input. But given a certain input metric, you can be sure that the generated team is optimal.

I would gladly share my MATLAB code if there is any interest. Also, I'm open to suggestions on how to extend it. EDIT: Here it is.


(Tiny disclaimer: Remember when I said: "without any prior assumptions"? That is a lie. There is one tiny assumption I made, which is how often bench players are subbed on. I guesstimated this to happen approximately 10% of the time.)
submitted by nectri42 to FantasyPL [link] [comments]

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submitted by VFXALERT5 to u/VFXALERT5 [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.
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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.
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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.
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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.
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STOCK MARKET VIDEO: Stock Market Analysis Video for Week Ending June 26th, 2020

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STOCK MARKET VIDEO: ShadowTrader Video Weekly 6.28.20

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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
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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.

Monday 6.29.20 After Market Close:

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Tuesday 6.30.20 Before Market Open:

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Tuesday 6.30.20 After Market Close:

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Wednesday 7.1.20 Before Market Open:

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Wednesday 7.1.20 After Market Close:

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NONE.

Thursday 7.2.20 Before Market Open:

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Thursday 7.2.20 After Market Close:

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NONE.

Friday 7.3.20 Before Market Open:

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NONE.

Friday 7.3.20 After Market Close:

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NONE.

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.

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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.
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vfxAlert - Signals for binary options

vfxAlert - Signals for binary options
vfxAlert it's a tool for a binary options traders which they will use in their own trading strategies. Using vfxAlert assumes that the users are conversant in the essential principles of the forex market. and that they understand the principles of technical analysis and statistical methods. There are two main ways the way to use vfxAlert:
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Signals for binary options
!Important: vfxAlert don't offer trading strategies. vfxAlert offer signals and real-time statistics counting on current indicators values. See below:
The trading strategy may be a system of rules, on the idea of which the trader makes his own decisions. Such a system is made only on the idea of individual trading experience, gleaned knowledge and purchased skills. The strategy allows a deep understanding of the structure of the market and therefore the mechanisms of its operation, therefore, the exchange player makes decisions supported the present situation. On the idea of a private strategy, a trader can develop several trading systems and use them counting on market conditions. The strategy always takes under consideration fundamental factors, statistical data, also because the basic postulates of risk and money management.
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VfxAlert signals and candlestick patterns

VfxAlert signals and candlestick patterns
All how to make on binary options strategies should take into account all market analysis options. You cannot make a decision on only one instrument, even if these are candlestick analysis patterns.
Let's start with trend signals, see examples of vfxAlert binary signals.
Currency pair GBP/USD and a strong signal on PUT-option signal. Let's look at the price chart - confirmation by the "Three Method" candlestick pattern and you can open an option with an expiration of 5-10 minutes.

https://preview.redd.it/gwn6hg5fs8p51.png?width=1100&format=png&auto=webp&s=f67cae8d8fde0e38a27318f8eadea0e2c3cad495
The signal appeared at the intersection of the moving average ("MA" on the signal panel). Traders see this. The option opens on a reversal, but then there are also candlestick patterns, and new PUT-signals with the “MA” label open the next options with a large volume.
The next signal on the CCI indicator shows the dynamics of the current trend. Created for the stock market, where trends are long and easier to find. On Forex, volatility is higher and there may be strong corrections and pullbacks that "break" the indicator. In the figure, binary options trading signals is confirmed by a strong candle pattern – the price goes towards the gap and you can open a CALL-option.
Reversal real binary options signals vfxAlert.
More reliable than trendy ones, beginners should start with them. It is easier to see and understand: "Bulling engulfing" pattern, which means the "bulls" managed to shift the balance of power to themselves and start an uptend on EUR / GBP. The vfxAlert signal confirms this by technical analysis of the RSI indicator.

https://preview.redd.it/gpikbe6js8p51.png?width=1100&format=png&auto=webp&s=8581ebe0a59f665b78891996f23d95c289972250
Doji candlestick appeared on EUUSD. In candlestick analysis, this is the strongest reversal pattern. The vfxAlert binary options signal according to Parabolic SAR trend confirms the beginning of the downtrend. After one candlestick, the trend started you can open the PUT-option.
The trader looks at «Power» value first, the market may be sideways, and candlestick patterns are false:

https://preview.redd.it/efwtnupms8p51.png?width=1100&format=png&auto=webp&s=1170e6526704d44ec1a0ee936de5797f41e61d31
We always start testing combination "vfxAlert live binary signals + candlestick patterns" on a demo account. You only receive recommendations and must make sure that they fit your strategy, trading session and trading style.
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Signals for binary options | Binary Options Signals

Signals for binary options | Binary Options Signals
Adaptive - The adaptive algorithm uses statistical analysis of historical data. In contrast to the classical signals where the signal is given by certain conditions, within the adaptive algorithm were analyzed each candle in history is evaluated, this is often an equivalent if the signals got every minute or 5 minutes counting on the expiration time. Thus, the adaptive strategy shows the foremost favourable moment for entering the market.
Trending - the subsequent technical indicators are wont to generate signals
It is possible to use any conditions for the formation of signals, except for the foremost part, all of them give signals on the brink of one another . If you've got interesting suggestions on adding signal algorithms, write to [email protected]. For us, it doesn't matter how the signal is made - signal power and heatmaps are going to be calculated automatically as soon as enough statistical data is acquired (at least 2000 signals)
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https://preview.redd.it/cyooh3bzzvp51.png?width=785&format=png&auto=webp&s=57ac3f7dbda59828496f7bc88b9f58289005f9a5
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System Programming Language Ideas

I am an embedded electronics guy who has several years of experience in the industry, mainly with writing embedded software in C at the high level and the low level. My goal is to start fresh with some projects in terms of software platforms, so I have been looking at whether to use existing programming languages. I want my electronics / software to be open, but therein lies part of the problem. I have experience using and evaluating many compilers during my experience such as the proprietary stuff (IAR) and open source stuff (clang , gcc, etc.). I have nothing against the open source stuff; however, the companies I have worked for (and I) always come crawling back to IAR. Why? Its not a matter of the compiler believe it or not! Its a matter of the linker.
I took a cursory look at the latest gnu / clang linkers and I do not think that have fixed the major issue we always had with these linkers: memory flood fill. Specifying where each object or section is in the memory is fine for small projects or very small teams (1 to 2 people). However, when you have a bigger team (> 2) and you are using microcontrollers with segmented memory (all memory blocks are not contiguous), memory flood fill becomes a requirement of the linker. Often is the case that the MCUs I and others work on do not have megabytes of memory, but kilobytes. The MCU is chosen for the project and if we are lucky to get one with lots of memory, then you know why such a chip was chosen - there is a large memory requirement in the software.. we would not choose a large memory part if we did not need it due to cost. Imagine a developer is writing a library or piece of code whose memory requirement is going to change by single or tens kilobytes each (added or subtracted) commit. Now imagine having to have this developer manually manage the linker script for their particular dev station each time to make sure the linker doesn't cough based on what everybody else has put it in there. On top of that, they need to manually manage the script if it needs to be changed when they commit and hope that nobody else needed to change it as well for whatever they were developing. For even a small amount of developers, manually managing the script has way too many moving parts to be efficient. Memory flood fill solves this problem. IAR (in addition to a few other linkers like Segger's) allow me to just say: "Here are the ten memory blocks on the device. I have a .text section. You figure out how to spread out all the data across those blocks." No manual script modifications required by each developer for their current dev or requirement to sync at the end when committing. It just works.
Now.. what's the next problem? I don't want to use IAR (or Segger)! Why? If my stuff is going to be open to the public on my repositories.. don't you think it sends the wrong message if I say: "Well, here is the source code everybody! But Oh sorry, you need to get a seat of IAR if you want to build it the way I am or figure out how to build it yourself with your own tool chain". In addition, let's say that we go with Segger's free stuff to get by the linker problem. Well, what if I want to make a sellable product based on the open software? Still need to buy a seat, because Segger only allows non commercial usage of their free stuff. This leaves me with using an open compiler.
To me, memory flood fill for the linker is a requirement. I will not use a C tool chain that does not have this feature. My compiler options are clang, gcc, etc. I can either implement a linker script generator or a linker itself. Since I do not need to support dynamic link libraries or any complicated virtual memory stuff in the linker, I think implementing a linker is easily doable. The linker script generator is the simple option, but its a hack and therefore I would not want to partake in it. Basically before the linker (LD / LLD) is invoked, I would go into all the object files and analyze all of their memory requirements and generate a linker script that implements the flood fill as a pre step. Breaking open ELF files and analyzing them is pretty easy - I have done it in the past. The pre step would have my own linker script format that includes provisions for memory flood fill. Since this is like invoking the linker twice.. its a hack and speed detriment for something that I think should have been a feature of LD / LLD decades ago. "Everybody is using gnu / clang with LD / LLD! Why do you think you need flood fill?" To that I respond with: "People who are using gnu / clang and LD / LLD are either on small teams (embedded) OR they are working with systems that have contiguous memory and don't have to worry about segmented memory. Case and point Phones, Laptops, Desktops, anything with external RAM" Pick one reason. I am sure there are other reasons beyond those two in which segmented memory is not an issue. Maybe the segmented memory blocks are so large that you can ignore most of them for one program - early Visual GDB had this issue.. you would go into the linker scripts to find that for chips like the old NXP 4000 series that they were only choosing a single RAM block for data memory because of the linker limitation. This actually horrendously turned off my company from using gnu / clang at the time. In embedded systems where MCUs are chosen based on cost, the amount of memory is specifically chosen to meet that cost. You can't just "ignore" a memory block due to linker limitations. This would require either to buy a different chip or more expensive chip that meets the memory requirements.
ANYWAYS.. long winded prelude to what has led me to looking at making my own programming language. TLDR: I want my software to be open.. I want people to be able to easily build it without shelling out an arm and a leg, and I am a person who is not fond of hacks because of, what I believe, are oversights in the design of existing software.
Why not use Rust, Nim, Go, Zig, any of those languages? No. Period. No. I work with small embedded systems running with small memory microcontrollers as well as a massive number of other companies / developers. Small embedded systems are what make most of the world turn. I want a systems programming language that is as simple as C with certain modern developer "niceties". This does not mean adding the kitchen sink.. generics, closures, classes ................ 50 other things because the rest of the software industry has been using these for years on higher level languages. It is my opinion that the reason that nothing has (or will) displace C in the past, present, or near future is because C is stupid simple. Its basically structures, functions, and pointers... that's it! Does it have its problems? Sure! However, at the end of the day developers can pick up a C program and go without a huge hassle. Why can't we have a language that sticks to this small subset or "core" functionality instead of trying to add the kitchen sink with all these features of other languages? Just give me my functions and structures, and iterate on that. Let's fix some of the developer productivity issues while we are at it.. and no I don't mean by adding generics and classes. I mean more of getting rid of header files and allowing CTFE. "D is what you want." No.. no it's not. That is a prime example of kitchen sink and the kitchen sink of 50 large corporations across the the block.
What are the problems I think need to be solved in a C replacement?
  1. Header files.
  2. Implementation hiding. Don't know the size of that structure without having to manually manage the size of that structure in a header or exposing all the fields of that structure in a header. Every change of the library containing that structure causes a recompile all the way up the chain on all dependencies.
  3. CTFE (compile time function execution). I want to be able to assign type safe constants to things on initialization.
  4. Pointers replaced with references? I am on the fence with this one. I love the power of pointers, but I realize after research where the industry is trying to go.
These are the things I think that need to be solved. Make my life easier as a developer, but also give me something as stupid simple as C.
I have some ideas of how to solve some of these problems. Disclaimer: some things may be hypocritical based on the prelude discussion; however, as often is the case, not 'every' discussion point is black and white.

  1. Header Files
Replace with a module / package system. There exists a project folder wherein there lies a .build script. The compiler runs the build script and builds the project. Building is part of the language / compiler, but dependency and versioning is not. People will be on both sides of the camp.. for or against this. However, it appears that most module type languages require specifying all of the input files up front instead of being able to "dumb compile" like C / C++ due to the fact that all source files are "truly" dumbly independent. Such a module build system would be harder to make parallel due to module dependencies; however, in total, required build "computation" (not necessarily time) is less. This is because the compiler knows everything up front that makes a library and doesn't have to spawn a million processes (each taking its own time) for each source file.
  1. Implementation hiding
What if it was possible to make a custom library format for the language? Libraries use this custom format and contain "deferrals" for a lot of things that need to be resolved. During packaging time, the final output stage, link time, whatever you want to call it (the executable output), the build tool resolves all of the deferrals because it now knows all parts of input "source" objects. What this means is that the last stage of the build process will most likely take the longest because it is also the stage that generates the code.
What is a deferral? Libraries are built with type information and IR like code for each of the functions. The IR code is a representation that can be either executed by interpreter (for CTFE) or converted to binary instructions at the last output stage. A deferral is a node within the library that requires to be resolved at the last stage. Think of it like an unresolved symbol but for mostly constants and structures.
Inside my library A I have a structure that has a bunch of fields. Those fields may be public or private. Another library B wants to derive from that structure. It knows the structure type exists and it has these public fields. The library can make usage of those public fields. Now at the link stage the size of the structure and all derivative structures and fields are resolved. A year down the road library A changes to add a private field to the structure. Library B doesn't care as long as the type name of the structure or its public members that it is using are not changed. Pull in the new library into the link stage and everything is resolved at that time.
I am an advocate for just having plain old C structures but having the ability to "derive" sub structures. Structures would act the same exact way as in C. Let's say you have one structure and then in a second structure you put the first field as the "base" field. This is what I want to have the ability to do in a language.. but built in support for it through derivation and implementation hiding. Memory layout would be exactly like in C. The structures are not classes or anything else.
I have an array of I2C ports in a library; however, I have no idea how many I2C ports there should be until link time. What to do!? I define a deferred constant for the size of the array that needs to be resolved at link time. At link time the build file passes the constant into the library. Or it gets passed as a command line argument.
What this also allows me to do is to provide a single library that can be built using any architecture at link time.
  1. CTFE
Having safe type checked ways to define constants or whatever, filled in by the compiler, I think is a very good mechanism. Since all of the code in libraries is some sort of IR, it can be interpreted at link time to fill in all the blanks. The compiler would have a massive emphasis on analyzing which things are constants in the source code and can be filled in at link time.
There would exist "conditional compilation" in that all of the code exists in the library; however, at link time the conditional compilation is evaluated and only the areas that are "true" are included in the final output.
  1. Pointers & References & Type safety
I like pointers, but I can see the industry trend to move away from them in newer languages. Newer languages seem to kneecap them compared to what you can do in C. I have an idea of a potential fix.
Pointers or some way is needed to be able to access hardware registers. What if the language had support for references and pointers, but pointers are limited to constants that are filled in by the build system? For example, I know hardware registers A, B, and C are at these locations (maybe filled in by CTFE) so I can declare them as constants. Their values can never be changed at runtime; however, what a pointer does is indicate to the compiler to access a piece of memory using indirection.
There would be no way to convert a pointer to a reference or vise versa. There is no way to assign a pointer to a different value or have it point anything that exists (variables, byte arrays, etc..). Then how do we perform a UART write with a block of data? I said there would be no way to convert a reference ( a byte array for example) to a pointer, but I did not say you could not take the address of a reference! I can take the address of a reference (which points to a block of variable memory) and convert to it to an integer. You can perform any math you want with that integer but you can't actually convert that integer back into a reference! As far as the compiler is concerned, the address of a reference is just integer data. Now I can pass that integer into a module that contains a pointer and write data to memory using indirection.
As far as the compiler is concerned, pointers are just a way to tell the compiler to indirectly read and write memory. It would treat pointers as a way to read and write integer data to memory by using indirection. There exists no mechanism to convert a pointer to a reference. Since pointers are essentially constants, and we have deferrals and CTFE, the compiler knows what all those pointers are and where they point to. Therefore it can assure that no variables are ever in a "pointed to range". Additionally, for functions that use pointers - let's say I have a block of memory where you write to each 1K boundary and it acts as a FIFO - the compiler could check to make sure you are not performing any funny business by trying to write outside a range of memory.
What are references? References are variables that consist of say 8 bytes of data. The first 4 bytes are an address and the next 4 bytes is type information. There exists a reference type (any) that be used for assigning any type to it (think void*). The compiler will determine if casts are safe via the type information and for casts it can't determine at build time, it will insert code to check the cast using the type information.
Functions would take parameters as ByVal or ByRef. For example DoSomething(ByRef ref uint8 val, uint8 val2, uint8[] arr). The first parameter is passing by reference a reference to a uint8 (think double pointer). Assigning to val assigns to the reference. The second parameter is passed by value. The third parameter (array type) is passed by reference implicitly.
  1. Other Notes
This is not an exhaustive list of all features I am thinking of. For example visibility modifiers - public, private, module for variables, constants, and functions. Additionally, things could have attributes like in C# to tell the compiler what to do with a function or structure. For example, a structure or field could have a volatile attribute.
I want integration into the language for inline assembly for the architecture. So you could place a function attribute like [Assembly(armv7)]. This could tell the compiler that the function is all armv7 assembly and the compiler will verify it. Having assembly integrated also allows all the language features to be available to the assembly like constants. Does this go against having an IR representation of the library? No. functions have weak or strong linkage. Additionally, there could be a function attribute to tell the compiler: "Hey when the link stage is using an armv7 target, build this function in". There could also be a mechanism for inline assembly and intrinsics.
Please keep in mind that my hope is not to see another C systems language for larger systems (desktop, phones, laptops, etc.) Its solely to see it for small embedded systems and microcontrollers. I think this is why many of the newer languages (Go, Nim, Zig, etc..) have not been adopted in embedded - they started large and certain things were tacked on to "maybe" support smaller devices. I also don't want to have a runtime with my embedded microcontroller; however, I am not averse to the compiler putting bounds checks and casting checks into the assembly when it needs to. For example, if a cast fails, the compiler could just trap in a "hook" defined by the user that includes the module and line number of where the cast failed. It doesn't even matter that the system hangs or locks up as long as I know where to look to fix the bug. I can't tell you how many times something like this would be invaluable for debugging. In embedded, many of us say that its better for the system to crash hard than limp along because of an array out of bounds or whatever. Maybe it would be possible to restart the system in the event of such a crash or do "something" (like for a cruise missile :)).
This is intended to be a discussion and not so much a religious war or to state I am doing this or that. I just wanted to "blurt out" some stuff I have had on my mind for awhile.
submitted by LostTime77 to ProgrammingLanguages [link] [comments]

The Sun Rises as Usual: My thoughts on the enactment of the national security law in Hong Kong (Author: Simon Shen 沈旭暉)

The below essay by Simon Shen (沈旭暉), a Hong Kong-based political scientist and columnist.
Link to original essay: Facebook
YouTube channel (Cantonese)
His videos and articles has been on this sub a few times (See https://redd.it/hmttfa https://redd.it/gn5j83), so I thought this one is also worth a read and discuss, whether we agree or not.

The Sun Rises as Usual: My thoughts on the enactment of the national security law in Hong Kong

July 1st, 2020 shall be remembered as the day Hong Kong completed its second Handover to China. A strong sense of despair clouds over the city as Beijing nuked us with the National Security Law (NSL). The thought of losing the authenticity of Hong Kong forever is ingrained in many of us.
The same day, the sun rises in the east as usual.The rule of thumb to survive this era of turmoil is to maintain control of your mental state. Remain unflappable by the ongoing absurdity. You live your life at your own pace with no restrictions. And that is how you win in society, at the workplace, on campus, and in marriage.
As to how we could achieve that, I hope my two-cents would give you some ideas.
The officials expected us to be overwhelmed, terrified, and occupied by NSL. Nevertheless, the clauses of the law have never been the main course of this extravagant meal. What truly awaits for us is the complete makeover of the Hong Kong ruling. Abolishing the standard procedure inherited from British Hong Kong, rationality and logical decision-making are soon replaced by the ambiguity of the authoritarian “rule of law” of China. Hong Kong has lost its place in the globe at the mercy of NSL; that is, to show a lucid message: Beijing could withdraw the “One Country, Two Systems” principle however it sees fit. Moreover, it is the re-education training CCP set up for Hongkongers to make them know their place and accept the “Mainland ideology,” which includes tolerating laws and regulations that are more “lenient” to serve the Chinese political agenda. Placing the national interests in heart, it is farewell to “Rule of Law,” and the common understanding of right and wrong and dos and don’ts.
This is the textbook example of authoritarian ruling. Perhaps people would be seeing some form of democracy and freedom; however, those were merely decoys in which the supreme power vested afar.
23 years after the Handover, pro-Beijing population remains small by default. The young generation rebukes Chinese identity even more than before. The enactment of NSL indicates the failure of CCP’s strategic approaches to entice Hongkongers. If the regular and United Front approaches failed through, they might as well execute eradication instead. It may appear as China is calling for enticement, but the underlying measures/gimmicks are showing something else. The grand Unity of Mainland and Hong Kong is nothing more than a hoax.
In this new Hong Kong, measurements taken to appease public backlash or allow people to express their frustration toward politicians or policies are stored in the past. Furthermore, the Hong Kong government has adopted more extreme approaches—severing Hong Kong into the pro-democracy camp and the pro-Beijing camp; bringing back Cultural Revolution tactics to effectively counteract dissentance; and activating 24/7 monitorization of the population. The propaganda of the CCP regime is to increasingly disintegrate the mutual trust between people by ratting and spying. Building the new norm where the civil society crumbles and espionage is normalized. People with malicious intent may find this new world rather exciting. Without the checks and balances or supervision in the system, the escalating waves of purging the “impure” in the next 2 years are anticipated.
The hostile public opinion of Hong Kong toward Beijing’s decisions have always been a throne in the flesh for the ruling party which led to it prioritizing the disunification of the Hong Kong civil society in the following 2 years—gathering the elites from all professions, alternating the policies of media regulations, reforming education to be more CCP-interests-oriented, and emphasizing the governmental compliance of all departments for effective executions of the new laws. The small population that is most affected by NSL would be those who are in the “Four Black Categories,” including the influencers and KOLs. The two major key points for Hong Kong government’s guidelines are “rule by law” and “always have the national interests at heart.” Regardless of NSL, Public Order Ordinance(POO) per se or any other laws could be used to incriminate the dissidents. Even a world-renowned Chinese artist such as Ai Weiwei was accused of Tax Evasion. Apolitical celebrities with millions of fans and could also be targeted; e.g. Fan Bingbing. Over time, people would adapt to self-censorship. As their minds slowly die of a thousand cuts to circumvent trespassing the political “bottom-line”, it includes avoiding dissenting the propaganda and minimizing exposure that may attract unwanted attention.
Oddly enough, if you were to be a tourist, you probably would not be able to capture the post-NSL nuances of this hollow Hong Kong. You would see all business continue, stock market arises, and the real estate market thrives as usual. It is as if the script written for the second Handover would play out successfully, as long as the basic needs of Hongkongers are satisfied.
Amidst of this turmoil, Hongkongers wouldn’t need me to elaborate more; however, we should ask ourselves if there is something else that we could do. Do you still remember how we were like before all of these occur? What are the options we have aside from obeying to the laws, immigrating out of our homeland, or starting riots? How should we live in the middle of this mess?
From the anti-extradition law protest to the ongoing movement we have today—disregarding the variations in the slogans—we are a part of the global transformation which is beyond politics and may very well be a segment of the fourth industrial revolution. Moving forward from now, with AI replacing brain-power taxing positions, it would be unlikely for anyone to have a stable job and their retirement secured. With that being said, we are facing a tomorrow where people could no longer rely on a singular path for career planning. The younglings are determined and flexible about making chances. They are independent individuals who seek for autonomy in life without relying on governmental entities, pro-establishment units, and consortiums, for their survival which tie into a global trend. The “ultrastable system” of the good old times Hong Kong is in the past. The young generation is calling for “Laam Chau.” (self-destruction to counterbalance Hong Kong government) Acknowledging the fact that enduring injustice would not secure any job positions, the young generation tends to take on entrepreneurship and minimizing their political dependency.
Many friends started talking about immigration. A decade ago, the media were hyping the topic regarding whether or not I would be immigrating to Singapore. I have been repeating myself—the concept of immigration is obsolete. Over the past year, would you say that the overseas Hongkongers contributed more to the movement or the apolitical Hongkongers? Even if we hold multiple citizenships, travel around the world, send our children to study abroad, or hold investments in another country, what would it matter? Any of those would not affect our Hongkonger identity. When online classes are given remotely on Zoom, would it matter if you are in Hong Kong or in Congo? The physical location of Hong Kong shouldn’t tie us down. We should sever ourselves from the idea of leaving or staying and make the world our home. By stitching the virtual world to the real world, we are undefeated by constant change. To me, that is what Hong Kong really is.
All censorship from the authoritarian regime have one in common; that is, the oppressions could never be reasoned with the Common Law. If the pro-democracy anthem, “Glory to Hong Kong,” is prohibited to be sung on campuses, what about the 80’s Cantopop hit, “Boundless Oceans, Vast Skies” or “Blowing in the Wind” which both hint liberation in the lyrics? As the movement slogan, “Five Demands, Not One Less,” was banned, could the protesters express their dissent by raising their hands to point out 5 and 1 or having the number 5 and 1 written over their tops? Does everything related to the number 5 and 1 need to be a politically sensitive topic? Could we still talk about the Labor Day that falls on May 1st? The rebellious ideology is embedded in the mind of Hong Kong protesters, as people have witnessed the incompetence of our government on a daily basis. This movement has been embodying innovation in various ways. No extra commentaries are needed. This is the true essence of “be water.”
Similarly, Poland and the Czech Republic in the 60s were under greater oppression than what we have been seeing in recent Hong Kong; however, “life always finds a way.” We now live in a globalized world where “colluding foreign forces” is unnecessary, with the help of our overseas brothers and sisters to amplify the pro-democracy messages to the international community. We shall acknowledge the fact that dwelling on the past does no one any good for sustaining this movement.
You could be someone who lacks the courage to venture out of the comfort zone, refuses to adapt to having multiple careers, resists leaving the physical location of Hong Kong, fears to put on a yellow helmet (a pro-democracy symbol), and chooses to be enslaved by the ruling party. Even if you are a Blue Ribbon ( pro-established or pro-Beijing person), as long as you are not a part of the most extreme 20% of the deep Blue Ribbon community, I say you are still a very valuable asset to Hong Kong. In this NSL-enacted Hong Kong, you should give it some thoughts about what advantages you hold that the “new Hongkongers” cannot offer. If you cannot answer this question, then no matter how patriotic you are, you will be eliminated in the next wave of selection. “Survival the fittest.” Even in Chinese companies, they still need Hongkongers to do the due diligence for them. In bureaucratic institutions, the Chinese would still need someone with a creative spirit and an international perspective while putting on a nationalist front.
Many have expressed their concerns toward the implementation of “Indoctrination” in Hong Kong, including some of the pro-Beijing parents. By sending their children to non-state-owned schools, their actions speak louder than their words. The new trend of education has confirmed that the traditional classroom model inherited from the 19th century Prussian teaching is outdated. Through big data, the teaching materials are personalized for individuals; moreover, students may build up their unique libraries of knowledge via their personal experience and curiosity. Regretfully, the new Hong Kong under authoritarian ruling embraces a rigid education system where syllabi and marking scheme is key to grooming the next generation of nationalists. The instructors would be under surveillance, school principals would bend to state-interests policies, and households would monitor each other for anti-government speeches or actions. Apparently, CCP would not succeed in brainwashing anyone with these educational reformations. Perhaps, Tik Tok may be more effective. Personalized education is an irreversible global trend. The authoritarian Hong Kong could butcher education but it could not prevent people from adapting to other alternatives. I would like to believe that the younger generations would harness the power of the internet and seize the opportunities given by an international community that has become more amiable to Hong Kong.
NSL’s main target is those who are “in collusion with foreign forces. How ironic is it to see how the strong connections between Hong Kong and the global community came back to bite per se? I recall reading from a research report, stating that on average every 1 out of 3 to 4 Hongkongers have connections overseas—overseas relatives, holding foreign qualifications or degrees, overseas working experience, having international investments, or having work contacts with foreign employees. Hongkongers have been colluding with the foreign forces before NSL made it a crime. The 2020 Hong Kong is suffering from cultural discontinuity created by the conflicts between the Chinese authoritarian system and the Western democracy system. Soon enough, “mass surveillance enabled by Big Data” vs. “A.I. regulated by privacy concerns” could be a multiple choice question for all Hongkongers. As long as Hongkongers are connected to the global network, we shall not lose our resilience against oppression.
To sum it up, Hongkongers have incorporated the world into “the revolution of our time.” March on and be water. The world we are facing is no longer black and white or binary of any sort. We may not reap what we sow. This is a long-term fight that requires us to be resourceful, as well as being mentally and physically prepared.
You may ask if I have ever wanted to leave Hong Kong. Ironically, since my 18th birthday, I have never stayed in Hong Kong for so long. The past 6 months, aside from pandemic, I have been sentimental toward this land. My profession and residences require me to travel a lot of places. I hardly stayed in Hong Kong for long as I made that decision deliberately 10 years ago. Now you may understand where I am coming from. Thus, I would not change for this NSL-enacted Hong Kong. I would not stay to make a statement, nor would I leave this land to make a stance. To my dear friends out there, my piece of advice has been the same—live like a digital nomad and have your footstep stamped locally and globally. No need to start from scratch. You may join a community that is well-established.
Should I self-censor for my safety? I’ve never been an editorial writer. My rationally words and videos are merely personal expressions of a Hongkonger. I honestly can’t get any more cautious. I am the same Simon Shen, now and always. We should not take any form of harassment or attacks personally.
Before the extradition law and the NSL, CCP had been effectively silencing dissents by sending them on one-way trips to Mainland China (i.e. Causeway Bay Books disappearances). The regime needed no bills to aid its attempt of kidnapping those who dare to voice up. Hong Kong has fallen too fast that no one bothers to attack or criticize the kidnaps. There is no such thing as making something less absurd by talking about it more. The systematic oppression of Hong Kong’s civil freedom does not only come from the without but also the within; especially when nowadays all we could talk about is “safety” and “survival.” It is exactly what CCP wanted for us to believe—we are trapped and our lives depends on our compliance. Hongkongers are being tested for our resilience. If we couldn’t pass this challenge together, how could we stand up tall as proud Hongkongers?
As to making ends meet, I’ve always believed that the global Hongkonger network is a large enough of encomany to support, expand, and give back to Hong Kong. We are all at its mercy, including me becoming a KOL. Within the Hongkonger community, I wish to be more practical and strategic; especially, in terms of elevating our quality of living. CCP is extremely calculative and different from us. It is my deepest belief that when the world sees how irreplaceable Hongkongers are that is the day when we can anticipate change. Before then, we will keep a low profile and prepare for this long battle.
Do expect the next two years to be a long rollercoaster ride with plenty of ups and downs. Hongkongers will only thrive through the hardships. Buckle up, winter is coming.
submitted by baylearn to HongKong [link] [comments]

[Results] Do you like ice-cream? (all about names)

Now, for anyone who didn't take part in this survey, let me briefly explain. This survey wasn't actually about ice-cream. What I set out to investigate was how willing people are to give out their own name online on a survey. To do this I put together a seemingly innocent survey purporting to be about ice-cream. Respondents were first asked for some demographic information, with a question asking for their name included, before being asked the "actual" question of Do you like ice-cream? on the next page. On the final page the ruse was revealed and respondents were asked how they responded to the name question: with their real name, another name, or something that's not a name at all, i.e. a non-name.
I got 915 responses from over 60 countries, which I was very pleased with. So thank you very much to everyone who took part!
Although the ice-cream question wasn't actually the main focus of the survey, I've put together the results of that question too for anyone who's interested, which I'll post in a comment below.
Without further ado, the results:
Just over half of respondents gave their real name. Interestingly, for the first few hours of the survey, the three options were consistently roughly even, at about a third each (and so the majority were not giving their real name). It was quite a bit later on that the real name preference started to show. This is probably a reflection of the different demographics of people on SampleSize at different times of day.
There isn't much difference across gender, with a similar percentage giving their real name for all three options. However, non-binary people were the most likely to give a non-name and the least likely to give a fake name while women were at the opposite end, being the least likely to give a non-name and the most likely to give a fake name, with men in the middle.
There is a very clear trend of younger people being more likely to give their own name and older people being less likely to. It's worth noting that a suspiciously high number of people in their 60s were 69, which may explain the high proportion of 'joke' non-name responses.
Canada and Australia had a notably lower proportion giving their real name than other countries. The Netherlands had the smallest proportion to give a fake name.
And just for fun:
It seems people who don't like ice-cream are less willing to give their real name but quite unlikely to give a fake name, much preferring a non-name. This could indicate some of these are joke responses.
A couple of things to bear in mind:
Last points:
Most people who gave their real name gave only their first name. A small minority gave their full name.
About three quarters of 'another name' responses seem feasible while a quarter did not (e.g. names like Ben Dover or Jennifer Lopez).
Some favourite responses to What is your name?:
Edit: Link to original thread.
submitted by tg3y to SampleSize [link] [comments]

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