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[Travel] - American Airlines begins offering non-binary gender options during booking process | USA Today

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Today I took a survey in Catalan; it was the first one I've ever seen with the option "non-binary"!

I was taking a survey in Catalan (about linguistics). When I finished it, I saw that it was asking me my gender. I thought "Well, I will put 'other', as always". But then I saw that the options were male, female, non-binary and other! I felt so happy that I even said "Thanks for including non-binary identities" in the "other comments" section!
Just wanted to share, because it's the first time I see the term "non-binary" in my mother tongue in an official or public place :)
submitted by NeoMahler to NonBinary [link] [comments]

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It's been 4 Days since my Spouse Came Out as MTF - Here are Some Random Thoughts I've had!

I (cis-f, 33) have been a bit of a hot mess the past week and my mind has been all over the place. Because this is so new (and subject to change), we aren't telling anyone else at the moment, so I don't have a sounding board, so thank you, internet, for giving me an outlet to talk about my feelings thoughts. I am sorry if any of this is triggering. I'm new and still learning what this means.
  1. My spouse told me that it would be easier to buy them a Christmas gift this year (more options!). "Do you want Bath and Body Works Products? - That was like *the* default "girl" gift that I received when people started getting gifts when I was becoming a 'woman'." -- They said that they would be into that.
  2. If we stay together and they go through a full social-transition, I was thinking that it would be exciting to do a renewal of vows, like a small thing with both of us in dresses, with like a small beach ceremony and just super supportive people around us (I know I am WAY ahead of myself).
    1. This was immediately followed by fear about them being "prettier" than me and getting so many compliments and me being the ugly one. I am also really not interested in being masculine in any way and I have this weird insecurity about not being seen as feminine or "good enough" at being a girl.
    2. My spouse is good at a HUGE range of things. They are really remarkable in that regard and I am afraid that the more feminine they express, the more competition I will feel with them and they will beat me because they are going to be better at those things.
  3. "Maybe you should try one of my bras, it's not like *I've* worn one since the beginning of this quarantine." Haha
    1. I am a little insecure that we are similar size width-wise (they are definitely taller) but I've been struggling with my weight, so they can wear some of my dresses, for example, but they may be a little short. I wish I was small enough that we couldn't just interchange clothes so easily, but I guess we could both share double the wardrobe.
    2. It is nice that they can try on clothes that they don't have to buy right away. Definitely cheaper.
  4. My in-laws already hate me for other unrelated reasons and I just *know* that they will blame this situation on me. I am unsure how my parents would respond, but they have definitely expressed low-level homophobia. They are in the "I don't want to see it" camp. I am also fairly certain my mom will believe that this is a "mental health illness" and means that my spouse is a sexual deviant.
    1. This viewpoint scares me because it resonates with my internalized transphobia. That being "born in the wrong body" is an illness or some sick and twisted sexual fetish. If anyone has any ways to combat this initial reaction to this, I would love to know how to de-condition myself. Unfortunately, I associate transgenders as being a bit "weird" and now I'm having cognitive dissonance because I don't want to believe that my spouse is a weird sexual deviant.
    2. I also know that I have a hard time with emotional boundaries and self-doubt, so if someone comes at me with a strong opinion, I have a hard time not letting that get to me. Plus I'm a people-pleaser and I'm sure we will meet with some awful people along this journey.
    3. I'm afraid that this will reflect "poorly" on me and it gives me a sense of shame -- then I feel shame about the shame in a shame-spiral.
    4. If my in-laws disown them, I wonder if my spouse will change their last name. Should I change my last name? Should we pick a whole new name together? -- I do not feel "non-conformist" enough to do this.
  5. It's only been 4 days since they came out to me and they have already just skipped over the non-binary phase. Weirdly my spouse has expressed discomfort in the "in-between" space and has gone right to the feminine.
  6. I was super stressed about the election a week ago and now it is barely on my radar. The nice thing is I can hide my volatile emotions in election-stress, but for how long?
    1. I am like the worst secret-keeper in the world and this is definitely the biggest secret I have ever been asked to keep. I feel like it is written all over my face and I just hate it so much. I do NOT want to out them, but I am so scared I will CRACK under this pressure.
    2. This is interesting in that I have been working on healing an eating disorder. Today my nutritional coach called and asked how I was doing and that was hard for me. I don't want to completely derail my progress or really get into "this" with her, but I'd be lying if I said I haven't eaten/drank irresponsibly during the last week because of my strong emotions.
  7. Will *I* be accepted into the LGBTQ community? What IS my sexuality? I haven't really had to think about it before. Can I be a "real" bisexual/lesbian? Would I ever be viewed that way?
  8. Are we moving too fast? My spouse is like in a dress, one of my padded bras, makeup, and shaved their legs/chest already. They seem so happy. I feel happy that they are happy. I actually feel honored that they feel safe enough with me to explore so fully so quickly. It makes me feel like our marriage is stronger than I thought.
    1. They used some body spray and women's deodorant and now they smell different and that is unexpectedly disorienting for me.
  9. I don't like the rhetoric of "dead" name because I don't want to believe my spouse is "dead" -- their current name is one of those names that is generally used for a boy, but every once in a while is used for a girl (which is weirdly cool and hot and edgy to me). They aren't sure they want to actually change their first name, but I think I need something to call them so I can get more into the space of mentally viewing them the way they are presenting.
  10. I have this weird fear that when people find out they will be more upset about it than me. I haven't cried for example, but I just know someone else will, even though it won't affect them as much as it will affect me. That's weird and gate-keeping, I know, but I just feel like if I can "keep it together" so can they.
    1. I have some issues with emotions/emotional expression (especially sadness) and maybe this triggers me because it sometimes feels like I have "robot" feelings and that if I don't cry/mourn then "I don't care" as much. Believe me. I care. This intimately affects me.
  11. If they go on hormones will their sexuality change? Is that a common thing? If they start on hormones, how would that change their personality? They are one of the most chilled-out, contented, calm people I've ever met, but will hormones make them overly emotional?
  12. When I first thought about my sexuality, I thought/believed that the reason I could never be a lesbian would be 1) I want to be unequivocal 'the girl' and I was afraid of sharing that role and 2) I wouldn't want to deal with the over-emotionality of women. I have believed that I could probably be sexually attracted to women, but would be hesitant to be in a romantic relationship with them because it seems harder to be with a woman (both socially in society) and I am much more aligned with the "receiver" / the one who is cared for rather than the "provider" / the one who cares for the other. <-- I don't even know HOW to do that effectively.
    1. Let me clarify, I care for my spouse but it's generally the emotional care, not the "let me get rid of this spider" type of care. I can hold space for them to explore themselves, but I'm not gonna be able to protect them from a violent predator. I still want them to hold me.
So yeah, that's all pretty random. I'm very "heady" and just think a million-times a minute, so this is just the things that have been standing out to me. Thank you for listening.
submitted by meshsock to mypartneristrans [link] [comments]

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

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

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

[OC] Punt Rank 2020: Week 5 - Brett Kern Appreciation Club, the continued painful existence of Kevin Huber, PUNTERS THROWING TDs and the birth of Air Townsend. All this and the best video highlights of the week...

Welcome back, Punt Fans, to your slightly later than usual but there's no Thursday Night Football so what else are you going to be doing edition of our weekly hunt for the King of Punt – it’s /NFL’s own Punt Rank. If you haven’t been here with me before, the concept is both simple and fantastically over-engineered. Lemme break it down:
Each punter’s performance against five vital punting metrics is ranked against every other punter in the league.
Those rankings are combined into a weighted average ranking – the 2020 NFL Punt Rank.
Punt Heroes rise to the top; Punt Zeros sink to the bottom. Last week’s post and Week 4 standings are available here for the archivists, and all of this week’s stats analysis and highlights and lowlights in video form are just moments away.
As always I’m excited to get your perspectives on your team’s punter, and you can point me to things that I may have missed or overlooked, so please hit me with your feedback and questions in the comments!

Punt Rank Standings

Punt Rank 2020: Week 5 Overall Standings
2020 Week 5: Punt Performance Summary

Good Week for

Brett Kern (TEN, +1 to #3). Eh what do you want to know. If you’re reading this it means you like punting. If you like punting, you know that Brett Kern is a really, really great punter. And, Q.E.D – Brett was demonstrably great against the Bills on (the other) TNF. His three punts this week for the no-longer-significantly-infectious-Titans pinned Josh Allen and his shorts at the 9, 9 and 3 yard lines – covering 86% of Average Available Field which is GOAT tier punting. Here’s the pick of the bunch (his 41 yard precisiobomb corralled at the 3 yard line by Chris Milton) covering 93% of Available Field, and measuring in 7.6 yards better than an average punt from the opposing 44 yard line. Tidy.
In addition to his really really really great punting, the Kerninator also wrangled at least two uttely horrible snaps into decent holds for Gostkowski to continue his kicking renaissance tour, which is a majorly underrated part of the punter job description...
Logan Cooke (JAX, +12 to #13). SPEAKING OF PUNTER HOLDS AND THE EFFECT IT HAS ON KICKERS. Now I’m not saying that Chef had anything to do with the end of Stephen Hauschka’s NFL career on Sunday (0 for 2 within less than two minutes at the end of the first half, not called upon again, then cut PDQ after the weekend), but then I’m not not saying that either. Luckily for Logan (shoot I think I used that joke last week as well) the punting element of his game was without such ugly question marks. 100% of his three punts ended inside the Houston 20 yard line, covering 73%, 83% and 89% of Available Field, sneaking him up to 13th overall. Now let’s see if he can hold onto it. Geddit? Hold?! Pah.

Bad Week for

Kevin Huber (CIN, -8 to #24). On a game where the Bengals only managed the paltry total of 12 first downs (an average of one, yes ONE first down on their 12 offensive drives), K-Hub’s Bad Day was at least somewhat salvaged by the first half holy trinity of Turnover on Downs, INT and Fumble on consecutive drives (2, 3 and 4 – if you’re counting). Without that magical offensive incompetence, he could have been looking at double figure punts (I see you, Tress Way in Washington). As it was, he escaped with just the seven (!), but he takes a slide in the Punt Rank rankings as two of those (admittedly 57 and 60 yard boots) snuck for touchbacks, taking his season touchback percentage total to 26.1% which is second last in the league, just behind Tommy Townsend (more on him later). None of the magnificent seven made it inside the 20, wiping 13% off his season long percentage. However, in Kev’s defence, the first of his two end-zone-botherers this week was another case of coulda woulda shoulda from his coverage team. Alex Erikson heroically made up all the ground to reach the ball as it took a hop into the end zone, but his flailing scoopitty-scoop only managed to floopitty-floop the ball into the wrong side of the pylon.
Bengals bungle.
Football is a game of inches, and those couple cost Kev. And, after last week’s feature in Egregious Touchback of the Week where basically exactly the same thing happened, it’s entirely possible that Kevin Huber is stuck in some kind of awful groundhog day based time loop. That would at least explain this instagram account.
Ty Long (LAC, -5 to #23). Ty Long was the victim of the binary brain of Saints rookie receivereturnerobot automaton Marquez Callaway this week. In Marquez’s awesome little computer mind, he’s going:
IF
punt_catch_loc > 15 THEN SELECT Return_Like_Craycray FROM Return.Options
ELSE Fair_Catch_That_MF
Unfortunately for Ty, six of his seven punts were outside that 15 yard threshold and the big red light on Robot Marquez's head went off like WOO WOO, and he went HAM on bringing those suckers back. 69 (nice) return yards on the day with a long of 19 wiped almost ten yards off Long's Gross Average for the day and left him at just 53% of Average Available Field covered. The Chargers have now leaked 149 return yards for the season which is second worst in the league (behind those irrepressibly awful Jets) and almost three times the league average of 56 through five weeks. Ty will be hoping that they can turn that around before… long. Sorry.

Punt of the week – Week 5

Corey Bojorquez (BUF) continues his wild oscillation between the sublime and the ridiculous. It’s an odd-week so I guess this week it’s Sublime Corey, whose 71 yard scud missile from his own ten yard line in the second quarter of this week’s edition of Tuesday Night Football Bought To You By COVID-19 was an astonishing 28.3 yards longer than my Expected Net Gain model for an average punt from that spot. Look at this baby fly!
Bojorquez booms one.

Punters doin’ shit – Week 5

Hey, it’s Corey Bojorquez again! Guess he can do sublime AND ridiculous in a single week now. It’s Puntception. Corey’s first punt of the day was coming alllll the way back for 6 until he decided to put his face on the line to put an end to Kalif Raymond’s 40 yard return. BLOOF. Look at him putting on his cap all swag afterwards like yeah I blew that dude up
Yeah I think tackling with your head is good form?
But that’s not all for Punters Doin’ Shit in Week 5, oh no. We have a bonus double edition! and I include this clip with great enjoyment but also great sadness. Gentlemen and Gentlemen (just being real here), this week Riley Dixon (NYG) threw a Touchdown pass! For Giants fans reading this is when someone on your team throws the ball into the big painted area at the end of the field and a player (also on your team) catches it. I know this sounds strange and unusual, but it can happen. And it did happen for Riley on this awesome fake field goal toss to Evan Engram, brilliantly narrated by the incomparable Tony Romo in the clip below. Seriously, this call is outstanding…
Nobody look at me, doo doo do, you cant see me... Jim Nantz, don't talK to.. IM OPEN, THROW IT
Unfortunately, the play itself was called back due to a player not lined up on the line of scrimmage and the Giants had to settle for a 50 yard field goal. For Chargers and Jags fans reading, this is when your kicker kicks the ball and it goes between the two big tall standy uppy line things. I know this sounds strange and unusual, but it can happen. No TD for Riley, but we have the memories…

Egregious touchback of the week – Week 5

I might start calling this the Kevin Huber Touchback Memorial Column, after ANOTHER narrow miss by the Bengals coverage left Kev high and dry this week against the Ravens (see Bad Week).
Outside of that shambles, there were only 6 touchbacks on the other 102 punts in Week 5, and most of them were fairly ordinary so there isn’t much egregiousity (not a word but I’m going with it) to discuss. Instead today we’re going to take some time to appreciate Tommy Townsend (KC) who has apparently got some kind of nuclear powered leg and is playing a game called “look how far away I can kick a touchback from”. For those who haven’t been paying close attention, here’s how Tommy’s rookie season has gone so far in touchback terms.
Week 1 – 44 yards, modest.
Week 2 – 55 yards, expressive.
Week 3 – only punted once so gave myself a week off from this.
Week 4 – fucken LOLs this is, how about a 60 AND a 65!
Week 5 – hold my beer…
Oh my god Becky, look at this punt.
67 yards! SIXTY SEVEN! And that’s from the line of scrimmage - that sucker went almost EIGHTY YARDS in the AIR. It bounced at the two and I think the returner just never even saw it. He probably thought it went into orbit or something. Absolutely ludicrous distance and hangtime here from Tommy. And, thus, I think we have our new moniker for the lad: Air Townsend. Which is also funny because it sounds like hair and he has got long hair.
I’m wasted doing this.

Future of Punt Rank: desperate data plea

So part of my data collection for this analysis used to come from the brilliant Pro Football Reference gameplay finder. Which, as of this week, appears to have been absorbed into Stathead. And they’re now charging $8 a month for access to these individual play description tables, which is a massive punt in the balls.
Without this data, I’ve got no way to calculate Average Available Field coverage, no plus/minus performance against the Punt Expected Net Gain, and no data on punts inside the 5 and 10 yard lines – all of which come from that analysis of the individual punt plays. Whilst this data doesn’t feed the actual rankings (which come from free NFL.com data tables), they are all metrics that really help add context to the basic stats, and are things that people reading have commented on in the past and said they found interesting.
So, if anyone knows of anywhere else where I can access and download these play descriptions for each individual punt (without manually sifting the ESPN play by play reports!!), then please please let me know in the comments below. Alternatively if the eight people who read this each wanna chip in a buck a month on an ongoing basis so we can pay Stathead then that’d be cool too.
A sad day for punt stat fans to be sure. Fucken big corporate…
And on that note, all that's left is to say I will see you again next week for a likely more analytically constrained but still enthusiastically trying my bestest edition of Punt Rank.
Yours,
Eyebrows.
submitted by erictaylorseyebrows to nfl [link] [comments]

M532 - Passports and Gender Humble Address - Division

Passports and Gender Humble Address

That a humble Address be presented to Her Majesty, that she will be graciously pleased to instruct her Ministers to end the inclusion of a gender marker on British passports issued under her hand.
This motion is moved by the Rt Hon. Dame lily-irl, MP for the East of England, on behalf of the Official Opposition, and is co-sponsored by Solidarity, the Greens, the Progessive Party UK, and the Liberal Democrats.

Opening Speech

Mr Speaker,
I am pleased to move this motion in this House today. I ask honourable and right honourable members: what good, truly, does identifying gender on a passport do? A border force officer inspecting a passport has a person’s name, age, and photograph in front of them. A gender marker is unnecessary.
I came across this idea whilst brainstorming ways to best accommodate LGBTQ+ and gender nonconforming individuals. And the solution that seems to most readily present itself is to add an ‘X’, or third gender option to passports, for those whose gender identity does not fall within the typical male-female binary. But the fact is that for those people travelling to countries that are not accepting of, or even actively persecuting, gender nonconforming individuals, having an X on their passport would just make them a target for those regimes.
The solution is simple, Mr Speaker. Including gender on passports does not assist border protection efforts in any substantial manner. It is extraneous information that also happens to serve as a barrier for gender nonconforming individuals from expressing their gender identity on government documents. As a result I think it best to simply remove it.
British passports are issued under the Royal Prerogative and not any Act of Parliament, which is why I have moved this Humble Address for this to take effect. I hope honourable and right honourable members will join me in the Aye lobbies and I commend this motion to the House.
This division will end at 10pm on Sunday 25th October.
submitted by NukeMaus to MHOCMP [link] [comments]

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

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

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

Winding and Unwinding

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

NOPE and Earnings

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

NOPE and NOPE_MAD

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

Using the NOPE to predict ER

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

Caveats/Read This

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

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