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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 truevalue (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:
Volatility reflects the uncertainty of the current price
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
I am not a top-100 player, as given the inevitable RNG of effects, matchups and draws in card games, and the lack of rewards for ranking up in LoR, I simply don't see the point in painstakingly grinding up to such a level. The highest I've climbed is low Diamond, but considering the above knowledge, I believe that at a certain skill level (perhaps at around Platinum), it's more about how much time one can put in than how skilled they are. HOWEVER, considering all this, I have the absolute conviction that this deck is a top-100 worthy deck.
This is the only deck that I've played since Day 1 of Call of the Mountain, with various modifications, and I believe that it is a completely undiscovered meta unicorn. I've never faced a similar deck on ladder, and my deckbuilding experiments with any other archtypes have left me completely unsatisfied with the lack of interaction and agency, as well as the sheer counterability of the vast majority of tools currently out there. A lot of people are frustrated with the current meta - a lot of points of which are covered by BruisedByGod in his recent video critique. To summarize his main points:
Most answers are completely outclassed by threats
Sheer lack of healing options locks out deckbuilding choices
Most top-tier strategies prey on lack of interactivity (Pirate Burn, Lee Sin OTK, Star Spring)
This is a Control deck which, while originally devised to prey on the inevitably popular Aurelion Sol and Troll Chant and abuse the broken, flexible toolbox of Invoke on Day 1, also manages to both answer all 3 of these problems efficiently.
Lunari Duskbringer x 3
Spacey Sketcher x 3
Lunari Shadestalker x1
Pale Cascade x 3
Unspeakable Horror x 2
Vile Feast x 3
Simply the best available early-game that an Invoke Targon deck could hope to muster - Diana functioning as both early game and late-game removal (we have just enough Nightfall Synergy) for practically no investment, Pale Cascade being legitimately one of the most broken cards currently in the game, and the ping cards also serving a modicum of uses at all stages of a match. Spacey Sketcher has been severely underrated so far - providing critical tools for certain matchups and/or providing early game minions without needing to actually run them (a fundamental weakness of faster decks top-decking late). Its 'discard-replace' synergy with our late-game, as well as Duskpetal Dust and meta-call flex cards is just icing on the cake. Finally, note how every early game card I've chosen scales well and still plays a role as the game goes later; as removal, Elusive blocking, tool-building, Burst-speed Nightfall, pings and cantrip Combat Tricks. This is an often overlooked but fundamental difference between Control early-drops, and aggro early-drops (such as Precious Pet). ~
Sunburst x 3
Vengeance x 3
These two cards, combined with any generated Obliterates, form the only proper removal this deck has - and were the catalyst for me creating this deck in the first place. All three of these removal types leave almost NO room for the opponent to interact with them, and I believe that is the sole condition for a high-cost removal spell to be playable in the current game state. NOTE: Ruination is easily and always played around at a high-level of play - and leaves the opponent with ALL of the agency/choice to play around it/bait it exactly how they wish, instead of you (whose only options are to play the card too early and get out-tempo'd afterward, use more than 3 mana elsewhere to catch-up at which point it becomes unplayable, or lose the game to a sudden-attack completely at your opponent's discretion) - the ultimate NO-NO for this deck: I never even considered putting it in. ~
Meta Call Flex Spots
Divergent Paths x 2
At times I feel as if this card could be cut to 1 copy, but right now 2 feels great against the current meta, and drawing into at least one is almost necessary in order to compete with Star Spring (Obliterate is conditional and too great a tempo loss early on). In other metas previously, I've experimented with 1 copy of Passage Unearned, as well as 2 extra copies of Lunari Shadestalker. ~
Literally Everything Else One Could Ever Hope to Need
Lunari Priestess x 2
Solari Priestess x 3
Mountain Scryer x 3
Moondreamer x 3
Starshaping x 3
I still believe that Invoke is one of the most broken mechanics currently in the game. This is one of the heaviest late-game decks I can possibly imaginable, yet the only cards above 5-mana we run are removal, and our mid-game minions and healing straight up provide whatever early OR late-game tools we might possibly need in any matchup - it's simply overly flexible (flexilibity in card games being a MUCH bigger deal than most people give it credit for) and not enough of a tempo/stat sacrifice IMO. I think that Invoke as a mechanic is even stronger when ran in bulk, and especially in a Control deck - as the game goes on slowly you generate a toolbox that can handle just about any dynamic situation that meta decks can throw your way. The spell-mana nerf to Living Legends has balanced it out quite a bit, however the same-nerf to Cosmic Inspiration still hasn't convinced me that it isn't in the top 5 least healthy effects that a game based on carefully stat-balanced of minion trading could ever have (hit me up with your Cosmic Inspiration hate!) - a large proportion our games are won by this disgusting effect. Solari Priestess and Starshaping need no introduction as some of the most popular, utilitarian Invoke cards, however Mountain Scryer and Moondreamer (not so much Lunari Priestess) really put in the work, and I've never seen anyone else play these cards. The former provides crazy mana-advantage as the game goes on given our huge focus on Celestials (it's a shame we can't afford to push its Invoke chances even higher), and the latter has juuussst the right stat distribution at 3/5 to blockade most midgame tempo plays out opponent might go for. NOTE: Aurelion Sol is straight up unnecessary to compete late-game, is always burdensome and clunky draw, ruins our surprise factor (though that doesn't exist anymore with this post being made), and we often outvalue decks running him anyway (don't forget that the original premise of this deck was 'How can I best remove Aurelion?'). ~
Matchups/Strategy (Order Based on Mobalytics Tier List)
Lee Sin (60/40)
A somewhat favored matchup - although more recent lists that have cut Bastion in favor of Nopify may be a bit more in their favor (a proper Ping Counter). Hard mulligan for Spacey Sketcher, Sunburst and our pings. Generating Silence (Equinox) for Mentor of the Stones/Zenith Blade is our main early game goal. Our Mid-to-Late game goal is removing all 3 Lee Sin's at the expense of practically everything else (the rest of their deck is pretty much completely irrelevant, but rushing them down is also pretty much impossible) - after which our win is basically guaranteed.
This matchup is sadly the most binary thing: Sunburst/Vengeance/Ping's VS Lee Sin/Spell Denial/Zenith Blade
The rest of both decks are basically irrelevant other than to slow down the level up/speed up the level up/Draw into above cards
Draw Draw Draw + Always save enough mana to Removal Spell + Ping if the opponent has 4 mana up late game
I believe that we are very, very heavily favored if played properly (although it's a VERY nuanced matchup to play right), and most of our losses come from bricking our early-game draws and/or not drawing/generating a single Starshaping/Golden Sister as their burn damage inevitably builds up. Hard mulligan for all 1/2 cost cards (only keep 1 Pale Cascade with a 1/2 cost minion).
NEVER, EVER play early minions proactively (e.g. NO turn 1 Lunari Duskbringer unless they play something) - only ever match however many minions the opponent has AND trade right away to minimise Make it Rain/TF value (For instance, if you proactively play a minion with nothing to trade it into, and then find yourself needing to play, say, Diana/Solari Priestess later - the opponent is basically guaranteed free additional AOE value: make EVERY chump blocker count)
ALWAYS open attack into Powder Keg's (usually with our single developed minion)
Take ANY trade you can get (even if somewhat unfavorable) to clear both sides of the board going into turn 8 - one of the ways we can lose is if Riptide Rex clears our heavy board and we only have time to develop one chump blocker before the onslaught - especially because Riptide is MUCH stronger against minions than the nexus > Late game, try to keep both sides of the board as empty as possible
If you find yourself with priority against their activated Plunder past turn 8, play small minions to bait out Rex without having to pass the turn OR play larger minions, especially with uneven health like Moondreamer to protect the rest of your board from potential cannons
ALWAYS try to find a NON-Rex'able position late game to develop Golden Sister, and save Pale Cascade if possible to protect her from Noxian Fervor and recover 6 previous health
ALWAYS have enough mana to remove Leviathan if the opponent has more than 8 mana on any given turn (prioritise Leviathan over Swain himself)
Sacrifice minions to TF attacks and remove Zap Sprayfin ASAP to minimise chip damage (which really builds up)
Be careful and make sure you always have a way to prevent Swain connecting with the Nexus (even if they develop him this turn and open attack the next); Pale Cascade is a good tool here
Pirate Aggro (55/45)
We are much more prone to bricking on draws here than Swain/TF, as we need quite a specific hand to deal with their onslaught - This is probably our most draw-dependent, low-agency matchup by far - as face-deck matchups tend to be. In addition - Captain Farron is much more effective against our removal strategy than the likes of Leviathan. Nonetheless, from my experience I think that we're still every-slightly-so favored in this matchup - often winning by the skin of our teeth. Starshaping/Golden Sister are mandatory late-game, and not bricking by not drawing/generating either is also basically a loss. Hard mulligan for all 1/2 drops, and keep a single Sunburst for Gangplank if your hand is already looking great.
There's nothing much to say here given the nature of their deck - pray your draws are good and take the obvious trades
A very unfavored and binary matchup (see below as to why) that has luckily become rarer recently. Mulligan for Removal/Invoke cards.
Save Starshaping for when you can actually make use of the heal (don't just play it on turn 3 because they're 'starting off slowly' - it's very important to maximise your leeway to survive Atrocity later on)
Try to remove Trundle on curve with Sunburst/Vengeance
Generate/Stockpile removal throughout the midgame
Sadly, none of these choices really matter in the end and the match comes down to luck - if Warmother's pulls a Level 1 Tryndamere on their attacking turn, the obvious open attack followed by a loss is all but guaranteed (Vengeance doesn't stop Atrocity in this case - leading to too great a health/tempo loss, and my previous Passage Unearned tech to deal with specifically this scenario simply wasn't worth the dead card in other matchups). We can also lose to a big levelled Trundle, or simply not generating/drawing into enough removal. Sadly these cases happen more often than not. Warmother's generated too much tempo if left unchecked by hard removal for even a single turn so there is little leeway for bad luck.
If Warmothers' timing and Invoke/draws are on our side, the matchup becomes pretty simple - Smartly use about a removal spell on their big guys for about 8 turns, play around Ruination and Atrocity, then cruise to victory.
This deck was basically created on Day 1 specifically to destroy Trundle/Asol. Sadly though, even at 75/25 the matchup is worse than it should be due to the nature of Invoke RNG - if one player draws into Cosmic Inspiration and the other didn't the match is over, full stop + the occasional shenanigans involving The Great Beyond uninteractibly going face and non-stop Living Legends value. Mulligan for Sunburst, Vengeance and pings.
Remove Trundle ASAP with Sunburst (Vengeance/Obliterates are best saved for Asol so getting Sunburst value while Trundle is still unleveled and 6 health is a big deal in terms of removal distribution)
Always try to remove Asol on the first turn he's played with Vengeance chaining into a ping to minimise the opponent's chance of getting game-winning Invoke RNG/matching your late-game value with free Celestials
If you still haven't drawn a ping late game, try to fish for Crescent Strike with Spacey Sketcher
Play around 7-mana Asol (Augur of the Old Ones) as much as possible
Pray you draw Cosmic Inspiration and the opponent doesn't
Discard Aggro (80/20)
I don't know why this deck is considered competitive - maybe because our matchup here is basically as favored as TF/Swain except without any gameplay nuance required on our part. Mulligan for 1-2 drops. Keep Solari Priestess/Sunburst if hand is good. Only necessary statistical losses to bad early draws against an aggro archtype.
Make obvious trades. Play around Mystic Shot on Diana. Chump block Draven/Jinx. Remove Draven/Jinx. Profit.
Another draw dependent, but quite favored matchup. Quite difficult to play though - you need to balance maintaining some modicum of tempo whilst also being able to deal with their crucial threats. Mulligan for 1-2 drops ESPECIALLY Pale Cascade/Pings, and Removal.
DON'T play ANY minion with less than 3 attack from turns 1-4 UNLESS you're getting tempo'd into the ground OR you have Pale Cascade (otherwise Fiora gets a free trade and the opponent gets to use their buffs reactively rather than proactively - giving you less leeway to remove her)
Save ping's for Fiora Barrier's, NOT Fleetfeather Tracker UNLESS you're getting tempo'd into the ground
Save a removal spell and mana for turn 3 Fiora, turn 4 Shen, turn 6 Genevieve and turn 9 Brightsteel UNLESS you're getting tempo'd into the ground
Basically the Pirate Aggro matchup but a tad bit slower and with no burn - giving you more leeway to make up for bad draws both early and late.
Make the obvious trades, pray to draw well and don't to let Genevieve get 2 attacks off
Basically the Trundle/Asol matchup except with no 'must remove ASAP' threats giving you more leeway to make up for bad draws. Celestial RNG and especially Cosmic Inspiration still give them a chance to win as usual. ~
Shyvana Dragons (50/50?)
I surprisingly, haven't faced too much of this deck yet personally, but looking at it's cards compared to ours, I think the matchup would be about 50/50 (an otherwise favourable looking matchup affected a bit by their high tempo removal and guaranteed Cosmic Inspiration in the form of Kadregrin). ~
This matchup is dependent on whether we draw removal for Ashe somewhat on curve, how much tempo they manage to build early on and whether we draw good enough to afford to play around Reckoning. Mulligan for Sunburst, Solari Priestess, Pings and Diana (only if you've already drawn support) as our other standard early drops are all pretty ineffective against theirs.
Remove Ashe ASAP
Try to Vengeance Sejuani on the attack if she directly attacks your Frostbitten minion in order to prevent the free value trade and maintain tempo on board.
Play around Reckoning as much as possible, especially if it wouldn't affect their own board too much compared to yours - maximise your 5+ attack minions to theirs if Reckoning begins to look more likely
Try to bait out an invested attack/Frostbite support for Trifarian Gloryseeker before pinging her - especially because Elixir of Iron is a bit rarer nowadays
Probably our most favored meta-deck matchup, and unfortunately rarer recently. Their win conditions - Kalista, Blighted Caretaker tempo, Neverglade Collector and They Who Endure simply don't stand a chance against our toolbox. Most losses come from unanswered Blighted Caretaker tempo. Mulligan for Spacey Sketcher, Sunburst and Pale Cascade.
ALWAYS pick Silence (For They Who Endure) or Stun (For Blighted Caretaker) off Spacey Sketcher
Try to hold a minion to play on turn 3/4 to kill an attacking Kalista with Pale Cascade AND get the Nightfall card draw
Play as reactively as possible with your pings - playing them proactively will almost always be answered by Glimpse Beyond, and when they run out of gas later on they will be forced to play their Glipmse proactively - your chance to strike!
Silence/Sunburst Blighted Caretaker as it comes down
SAVE Vengeance for They Who Endure - going into the late game, stockpile Silence/Sunburst and Vengeance and maintain enough mana (usually open-attacking) if necessary (IF can still afford to play They Who Endure that turn) to use one of the former followed by Vengeance to counter into their Atrocity: with this line of play, it's basically impossible to lose the combo
The biggest downside and sheer impossible matchup of this archtype. Maokai manages to pack even less interactivity/inevitability than we do, and the nature of our deck gives us no chance of out-tempoing Deep early OR late. Auto-concede. ~
A simpler aggro matchup than the others. Mulligan for 1-2 drops - especially Spacey Sketcher and Diana, as well as Sunburst.
ALWAYS pick the Stun spell off Spacey Sketcher, and save it for Diana, or of lesser priority, Nocturne/Ephemerals off Stalking Shadows
Removing Nocturne ASAP with either Sunburst or Vengeance is a HUGE priority
ALWAYS play around Pale Cascade
Play around Atrocity and Doombeast damage later on in the match
Another matchup that I haven't faced too much of just yet. Mulligan hard for Divergent Paths and Solari Priestess - Once we remove their uninteractive element trump-card in the Landmark win-condition, if we can survive their early tempo, the rest of the match should be a cinch given our heal/health-ignoring conditionless removal for their Champions. ~
Thanks for reading up to this point, and pardon my formatting, the ridiculous length and the sheer pomposity of it all. I still think Invoke is flexible to the point of being broken and the only reason the matchup spread is so good. I also think that with the release of this guide - more people will come to recognise this archtype and the element of surprise affecting enemy mulligans against an assumed more aggro, Nightfall-focused Diana archtype will be lost. People will also know to play around less common cards such as Sunburst, and I expect winrates to fall somewhat across the board. To conclude this guide, I'd like to say that this is this is not a healthy deck. At the deepest level, this deck is fundamentally about removing agency from your opponent and giving it to yourself, as well as securing the critical boon of having inevitability over your opponent in a game with the nature of LoR. If all decks were like this, LoR would completely cease to be fun. What else do I think is unhealthy right now? - Simple: anything removing interactivity from your opponent - ESPECIALLY as a win condition; Maokai, Star Spring, Cosmic Inspiration, Lee Sin. The avenues through which these cards can be interacted with are way too limited right now. A lot of the metagame nowadays is about having an uninteractable win condition, or focusing damage to face so fast the opponent has no chance to react - another form of non-interactivity. Here's hoping that the meta in the near future heads back in the direction of the close but fair midrange board battles we all came to love back in vanilla LoR. ~ (slinx4)
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:
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.
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:
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).
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):
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.
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) = 24,000net 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:
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:
How exceptional is today's NOPE versus historic baseline (30 days prior)?
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:
Calculate today's NOPE score (this can be done end of day or intraday, with the true value being EOD of course)
Calculate the end of day NOPE scores on the ticker for the previous 30 trading days
Compute the median of the previous 30 trading days' NOPEs
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:
The mean of NOPE_MAD for any ticker is almost exactly 0.
[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:
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.
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.
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).
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.
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:
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.
Sell/buy to close said shares at the first sign of major weakness (e.g. if the NOPE predicted outcome is incorrect).
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.
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
Going to keep this simple. EDIT: this isn’t simple and I should write a short story on this. I am generally risk averse. I hate losing $100 at the casino, I hate paying extra for guac at chipotles, I will return something or price match an item for a few dollars of savings. I am generally frugal. But, I somehow had no issues losing 10k in options... How I started I remember my first trades like they were yesterday. I was trading the first hydrogen run-up in 2014 (FCEL, BLDP, PLUG) and made a few hundred dollars over a couple weeks. I quickly progressed to penny stocks / biotech binary events and general stock market gambling mid-2014. I was making a few % here and there but the trend was down in total account value. I was the king of buying the peak in run-ups. I managed to make it out of 2014 close to break-even to slightly down. WSB Era March 2015 was my first option trade. It was an AXP - American Express - monthly option trade. I saw one of the regular option traders/services post a block of 10,000 calls that had been bought for 1.3 and I followed the trade with 10 call options for a total of $1300. I woke up the next day to an analyst upgrade on AXP and was up 50% on my position. I was addicted! I day-dreamed for days about my AXP over night success. I think around that time there was some sort of Buffet buyout of Heinz and an option trade that was up a ridiculous amount of %%%. I wanted to hit it BIG. I came up with the idea that all I needed to reach my goal was a few 100% over night gains/ 1k>2k>4k>8k> etc. I convinced myself that I would have no problems being patient for the exact criteria that I had set and worked on some other trades. Remember, the first win is always free. I was trading options pretty regularly from March 2015 until August 2016. During my best week I was up 20k and could feel the milli within reach. I can remember the exact option trade (HTZ) and I was trading weeklies on it. For those who have been in the market long enough, you will remember the huge drawdown of August 2015. I lost half my account value on QCOM calls (100 of them) that I followed at the beginning of July and never materialized. I watched them eventually go to 0. It was another 10,000 block that was probably a hedge or sold. In August 2015 there were some issues with China and all of us woke up to stocks gapping down huge. Unfortunately my idea of buying far dated calls during the following days/weeks after the crash went sideways. I quickly learned that an increase in volatility causes a rise in option prices and I was paying a premium for calls that were going to lose value very quickly (the infamous IV crush). I kept trading options into the end of 2015 and managed to maintain my account value positive but the trading fees for the year amounted to $30,000+. My broker was loving it. I tried all the services, all the strategies. I created rules for my option plays: 1. No earnings 2. Only follow the big buys at a discount (10,000 blocks or more). 3. No weekly options 4. Take profit right away 5. Take losses quickly 6. etc. I had a whole note book of option plays that I was writing down and following. I was paying for option services that all of you know about - remember, they make money on the services and not trading. I even figured out a loop-hole with my broker: if I didn’t have enough money in my account, I could change my ask price to .01 and then change it to market buy and I would only need to accept a warning ⚠️ for the order to go through. I was able to day trade the option and make money, who cares if I didnt have enough? After a few months of this, I got a call from my broker that told me to stop and that I would be suspended if I continued with this. By the way, I was always able to satisfy the debit on the account - so it wasn’t an issue of lack of funds. Lost it all. Started taking money from lines of credits, every penny that I earned and losing it quicker and quicker. I was a full on gambler but I was convinced that 8 trades would offset all the losses. I kept getting drawn in to the idea that I could hit a homerun and make it out a hero. I eventually hit rock bottom on some weekly expiring FSLR options that I bought hours before expiration and said to myself - what the f are you doing? I resolved to invest for the long term and stop throwing tendies away. The feeling was reinforced during the birth of my first born and I thought - what a loser this kid will think of me if he knew how much I was gambling and wasting my life. It was a really powerful moment looking at my kid and reflecting on this idea. I decided at that point I was going to save every penny I had and invest it on new issues with potential. Fall 2016 TTD, COUP and NTNX IPO ‘ed I decided I was going to throw every dollar at these and did so for the next few months. I eventually started using margin (up to 215%) and buying these for the next 6 months. They paid out and managed to make it over 100k within the year. The first 100k was hard but once I crossed it, I never fell below this magic number. 2017 - I did some day trading but it was mostly obsessing over the above issues. I did gamble on a few options here and there but never more than 1k. 2018 - SFIX was my big winner, I bought a gap up in June 2018 and my combined account value had crossed 400k by August 2018. I was really struggling at crossing the 500k account value and experienced 3 x 30-40% drawdowns over the next 2 years before I finally crossed the 500k barrier and have never looked back. I still made some mistakes over the next few months - AKAO & GSUM come to mind. Both of these resulted in 20k+ losses. Fortunately my winners were much bigger than my losers. I thought about giving up and moving to index funds - but i was doing well - just experiencing large drawdowns because of leverage. 2019 big winners were CRON SWAV STNE. 2017 / 2018 / 2019 all had six digit capital gains on my tax returns. At the beginning of 2020 I was still day trading on margin (180-220%) and got a call from my broker that they were tightening up my margin as my account was analyzed by the risk department and deemed too risky. Believe it or not this was right before the covid crash. I brought my margin down to 100-110% of account value and even though the drawdown from covid hit hard, I wasn’t wiped out. I stayed the course and bought FSLY / RH during the big march drawdown and this resulted in some nice gains over the next few months. I am constantly changing and testing my investment strategy but let me tell you that obsessing over 1 or 2 ideas and throwing every penny at it and holding for a few years is the best strategy. It may not work at some point but right now it does. I still day trade but I trade with 10k or less on each individual position. It allows me minimize my losses and my winners are 1-7%. I am able to consistently make between 3-700$/ a day on day trades using the above strategy. I still take losses and still dream about hitting it big with an option trade but dont feel the need to put it all on the line every month / week. I finally crossed into the two , club. I know people are going to ask for proof or ban but I am not earning anything for posting and the details about some of the trades should be proof enough that I kept a detailed journal of it all. I have way more to write but these are the highlights. Eventually I will share how I build a position in a story I love. I still sell buy and sell to early but I am working on improving. TL:DR - I gambled, lost it all and gambled some more lost more. I made it out alive. I have only sold calls/puts lately. The one common denominator in all successful people is how much they obsess over 1 or 2 ideas. Do the same. All the winners on this sub have gone all in on one idea (FSLY / TSLA ). Stick with new stories or ones that are changing and go all in...wait a second, I didnt learn anything.
i'm new in this forex stuff (not even starting yet) & first time visiting Forex. But i've read that forex basically gambling (guessing either it goes up or down, and you got previous data as reference). I'm also read about foolproof gambling tricks that works in real life roulette. Basically it goes like this :
bet $1 on red - if you win, repeat step 1.
if you lose, bet $3. if you win, repeat step 1.
if you lose again, bet $6. if you win, repeat step 1.
if you lose again, bet $14. if you win repeat step 1.
if you lose again, bet $31. if you win, repeat step 1
so, can this be apply on forex trading? (there's lot ads about forex trading apps, thinking to try it) can't profit big, but seem cant lose either. might be a good strategy. any thought? edit 1 : what i mean in this forex is binary options, which some forex trading apps operates. edit 2 : it takes 5 unlucky trading before $55 account blown off. is that really common to get 5 unlucky trading in a row? edit 3 : here's the math (cnp from reply) some forex apps (like expert option or olymp trade) operate on binary option (this is unregulated securities?) where usually they give 80% return on trade. the math goes like this :
$1 trade and win = $0.80 profit
lose then $3 trade and win = $2.4 - $1 (lose) = $1.4 profit
lose then $6 trade and win = $4.8 - $4 (lose) = $0.8 profit
lose then $14 trade and win = $11.2 - $10 (lose) = $1.2 profit
lose then $31 trade and win = $24.8 - $24 (lose) = $0.8 profit
profit means got back your initial too
edit 4 : some reply said **binary options type forex trading apps** are scam & fraud. bummer. maybe trading via smartphone isnt easy as i thought. edit 5 : still, add some ability to reading indicator & chart could help avoiding 5 unlucky trading in a row. damn, if i'm a programmer, i'll make a trading bots based on this idea xD
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Wall Street Week Ahead for the trading week beginning August 17th, 2020
Good Saturday morning to all of you here on stocks. 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 August 17th, 2020.
Stocks are ignoring the lack of a stimulus package from Congress, but that could change - (Source)
Stocks could hang at record levels but gains may be capped until Congress agrees to a new stimulus package to help the economy and the millions of unemployed Americans. Stocks were higher in the past week, and the S&P 500 flirted with record levels it set in February. In the coming week, there are some major retailers reporting earnings, including Walmart, Home Depot and Target, but the season is mostly over and the market is entering a quiet period. There are minutes from the Fed’s last meeting, released Wednesday, and housing data, including starts Tuesday and existing sales Friday. Investors had been watching efforts by Congress to agree to a new stimulus package, but talks have failed and the Senate has gone on recess. There is a concern that Congress will not be convinced to provide a big enough package when it does get to work again on the next stimulus round because recent economic reports look stronger. July’s retail sales, for example, climbed to a record level and recovered to pre-pandemic levels. “The juxtaposition of getting more fiscal stimulus and better data has paralyzed us in our tracks … we’ve seen this sideways [market] action,” said Art Hogan, chief market strategist at National Alliance. “It feels like we need more action from Congress, and the concern is the longer we wait, the better the data gets and the less impactful the next round of stimulus will be.” Some technical analysts say the market may pull back around the high, to allow it to consolidate gains before moving higher into the end of the year. The S&P 500 reached an all-time high of 3,393 on Feb. 19. Hogan said he expects stocks to tread sideways during the dog days of August, but they could begin to react negatively to the election in September. He also said it is important that progress continue against the spread of Covid-19, as the economy continues to reopen. Peter Boockvar, chief investment strategist at Bleakley Advisory Group, said the market could have a wakeup call at some point that the stimulus package has not been approved. “I think it will cross over a line where they care,” he said. “I think the market is in suspended animation of believing there will be a magical deal.” Boockvar said he expects a deal ultimately, but the impact is not likely to be as big as the last round of funding. “What they’re not grasping is any deal, any extension of unemployment benefits, is going to be smaller than it was, and the rate of change should be the most important thing investors focus on,” he said. “Not the binary outcome of whether there’s a deal or no deal. There’s going to be less air going into the balloon.”
It’s the economy
Still, economists expect to see a strong rebound in the third quarter, and are anticipating about about a 20% jump in third-quarter growth. But they also say that could be threatened if Congress does not help with another stimulus package. Mark Zandi, chief economist at Moody’s Analytics, described the July retail sales as a perfect V-shaped recovery, but cautioned it would not last unless more aid gets to individuals and cities and states. Democrats have sought a $3 trillion spending package, and Republicans in the Senate offered a $1 trillion package. They could not reach a compromise, including on a $600 weekly payment to individuals on unemployment which expired July 31. President Donald Trump has tried to fill the gap with executive orders to provide extra benefits to those on unemployment, but the $300 federal payment and $100 from states may take some time to reach individuals, as the processing varies by state. He has also issued an order instructing the Treasury to temporarily defer collection of payroll taxes from individuals making up to $104,000. “I think in August and September, there will be a lot of Ws, if there’s not more help here,” said Zandi, referring to an economic recovery that retrenches from a V shape before heading higher again. “It’s clearly perplexing. It may take the stock market to say we’re not going to get what we expect, and sell off and light a fire.” Zandi said it could come to a situation like 2008, where the stock market sold off sharply before Congress would agree to a program that helped financial companies. “We need a TARP moment to get these guys to help. Maybe if the claims tick higher and the August employment numbers are soft, given the president is focused on the stock market, that might be what it takes to get them back to the table in earnest,” he said, referring to the Troubled Asset Relief Program that helped rescue banks during the financial crisis. He ultimately expects a package of about $1.5 trillion to be approved in September. The lack of funding for state and local governments could result in more layoffs, as they struggle with their current 2021 budgets, Zandi said. Already 1.3 million public sector jobs have been lost since February, and there will be more layoffs and more programs and projects cancelled. The impact will hit contractors and other businesses that provide services to local governments. “The multipliers on state and local government are among the highest of any form of support, so if you don’t provide it, it’s going to ripple through the economy pretty fast,” he said. Economists expect to see a softening in consumer spending in August with the more than 28 million Americans on unemployment benefits as of mid-July no longer receiving any supplemental pay. “The real irony is things are shaping up that September is going to be a bad month, and that’s going to show up in all the data in October,” Zandi said. “They are really taking a chance on this election by not acting.”
This past week saw the following moves in the S&P:
The S&P 500 Index is a few points away from a new all-time high, completing one of the fastest recoveries from a bear market ever. But this will also seal the deal on the shortest bear market ever. Remember, the S&P 500 Index lost 20% from an all-time high in only 16 trading days back in February and March, so it makes sense that this recovery could be one of the fastest ever. From the lows on March 23, the S&P 500 has now added more than 50%. Many have been calling this a bear market rally for months, while we have been in the camp this is something more. It’s easy to see why this rally is different based on where it stands versus other bear market rallies:
They say the stock market is the only place where things go on sale, yet everyone runs out of the store screaming. We absolutely saw that back in March and now with stocks near new highs, many have missed this record run. Here we show how stocks have been usually higher a year or two after corrections.
After a historic drop in March, the S&P 500 has closed higher in April, May, June, and July. This rare event has happened only 11 other times, with stocks gaining the final five months of the year a very impressive 10 times. Only 2018 and the nearly 20% collapse in December saw a loss those final five months.
As shown in the LPL Chart of the Day, this bear market will go down as the fastest ever, at just over one month. The recovery back to new highs will be five months if we get there by August 23, making this one of the fastest recoveries ever. Not surprisingly, it usually takes longer for bear markets in a recession to recover; only adding to the impressiveness of this rally.
“It normally takes 30 months for bear markets during a recession to recover their losses, which makes this recovery all the more amazing,” said LPL Financial Chief Market Strateigst Ryan Detrick.. “Then again, there has been nothing normal about this recession, so maybe we shouldn’t be shocked about yet another record going down in 2020.”
When a Few Basis Points Packs a Punch
US Treasury yields have been on the rise this week with the 10-year yield rising 13 basis points (bps) from 0.56% up to 0.69% after getting as high as 0.72% on Thursday. A 13 bps move higher in interest rates may not seem like a whole lot, but with rates already at such low levels, a small move can have a pretty big impact on the prices of longer-term maturities.
Starting with longer-term US Treasuries, TLT, which measures the performance of maturities greater than 20 years, has declined 3.5% this week. Now, for a growth stock, 3.5% is par for the course, but that kind of move in the Treasury market is no small thing. The latest pullback for TLT also coincides with another failed attempt by the ETF to trade and stay above $170 for more than a day.
The further out the maturity window you go in the fixed income market, the bigger the impact of the move higher in interest rates. The Republic of Austria issued a 100-year bond in 2017, and its movements exemplify the wild moves that small changes in interest rates (from a low base) can have on prices. Just this week, the Austrian 100-year was down over 5%, which is a painful move no matter what type of asset class you are talking about. This week's move, though, was nothing compared to the stomach-churning swings from earlier this year. When Covid was first hitting the fan, the 100-year rallied 57% in the span of less than two months. That kind of move usually occurs over years rather than days, but in less than a third of that time, all those gains disintegrated in a two-and-a-half week span from early to late March. Easy come, easy go. Ironically enough, despite all the big up and down moves in this bond over the last year, as we type this, the bond's price is the same now as it was on this same day last year.
At the headline level, July’s Retail Sales report disappointed as the reading missed expectations by nearly a full percentage point. Just as soon as the report was released, we saw a number of stories pounce on the disappointment as a sign that the economy was losing steam. Looked at in more detail, though, the July report wasn’t all that bad. While the headline reading rose less than expected (1.2% vs 2.1%), Ex Autos and Ex Autos and Gas, the results were much better than expected. Not only that, but June’s original readings were all revised higher by around a full percentage point. Besides the fact that this month’s report was better underneath the surface and June’s reading was revised higher, it was also notable as the seasonally-adjusted annualized rate of sales in July hit a new record high. After the last record high back in January, only five months passed until American consumers were back to their pre-Covid spending ways. For the sake of comparison, back during the Financial Crisis, 40 months passed between the original high in Retail Sales in November 2007 and the next record high in April 2011. 5 months versus 40? Never underestimate the power of the US consumer!
While the monthly pace of retail sales is back at all-time highs, the characteristics behind the total level of sales have changed markedly in the post COVID world. In our just released B.I.G. Tips report we looked at these changing dynamics to highlight the groups that have been the biggest winners and losers from the shifts.
100 Days of Gains
Today marked 100 trading days since the Nasdaq 100's March 20th COVID Crash closing low. Below is a chart showing the rolling 100-trading day percentage change of the Nasdaq 100 since 1985. The 59.8% gain over the last 100 trading days ranks as the 3rd strongest run on record. The only two stronger 100-day rallies ended in January 1999 and March 2000.
While the Nasdaq 100 bottomed on Friday, March 20th, the S&P 500 bottomed the following Monday (3/23). This means tomorrow will mark 100 trading days since the S&P 500's COVID Crash closing low. Right now the rolling 100-day percentage change for the S&P 500 sits at +46.7%. But if the S&P manages to trade at current levels tomorrow, the 100-day gain will jump above 50%. It has been 87 years (1933) since we've seen a 100-day gain of more than 50%!
Whether you want to look at it from the perspective of closing prices or intraday levels, the S&P 500 is doing what just about everybody thought would be impossible less than five months ago - approaching record highs. Relative to its closing high of 3,386.15, the S&P 500 is just 0.27% lower, while it's within half of a percent from its record intraday high of 3,393.52. Through today, the S&P 500 has gone 120 trading days without a record high, and as shown in the chart below, the current streak is barely even visible when viewed in the perspective of all streaks since 1928. Even if we zoom in on just the last five years, the current streak of 120 trading days only ranks as the fourth-longest streak without a new high. While the S&P 500's 120-trading day streak without a new high isn't extreme by historical standards, the turnaround off the lows has been extraordinary. In the S&P 500's history, there have been ten prior declines of at least 20% from a record closing high. Of those ten prior periods, the shortest gap between the original record high and the next one was 309 trading days, and the shortest gap between highs that had a pullback of at least 30% was 484 tradings days (or more than four times the current gap of 120 trading days). For all ten streaks without a record high, the median drought was 680 trading days.
Whenever the S&P 500 does take out its 2/19 high, the question is whether the new high represents a breakout where the S&P 500 keeps rallying into evergreen territory, or does it run out of gas after finally reaching a new milestone? To shed some light on this question, we looked at the S&P 500's performance following each prior streak of similar duration without a new high.
STOCK MARKET VIDEO: Stock Market Analysis Video for Week Ending August 14th, 2020
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STOCK MARKET VIDEO: ShadowTrader Video Weekly 8.16.20
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(VIDEO NOT YET POSTED!) Here are the most notable companies (tickers) reporting earnings in this upcoming trading week ahead-
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Walmart Inc. $132.60
Walmart Inc. (WMT) is confirmed to report earnings at approximately 7:00 AM ET on Tuesday, August 18, 2020. The consensus earnings estimate is $1.20 per share on revenue of $134.28 billion and the Earnings Whisper ® number is $1.29 per share. Investor sentiment going into the company's earnings release has 81% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 5.51% with revenue increasing by 2.99%. Short interest has decreased by 12.5% since the company's last earnings release while the stock has drifted higher by 0.6% from its open following the earnings release to be 9.9% above its 200 day moving average of $120.64. Overall earnings estimates have been revised higher since the company's last earnings release. On Tuesday, August 11, 2020 there was some notable buying of 12,381 contracts of the $135.00 put expiring on Friday, August 21, 2020. Option traders are pricing in a 4.9% move on earnings and the stock has averaged a 2.3% move in recent quarters.
NVIDIA Corp. (NVDA) is confirmed to report earnings at approximately 4:20 PM ET on Wednesday, August 19, 2020. The consensus earnings estimate is $1.95 per share on revenue of $3.65 billion and the Earnings Whisper ® number is $2.01 per share. Investor sentiment going into the company's earnings release has 84% expecting an earnings beat The company's guidance was for earnings of $1.83 to $2.06 per share. Consensus estimates are for year-over-year earnings growth of 65.25% with revenue increasing by 41.53%. The stock has drifted higher by 31.0% from its open following the earnings release to be 57.7% above its 200 day moving average of $293.24. Overall earnings estimates have been revised higher since the company's last earnings release. On Friday, August 14, 2020 there was some notable buying of 3,787 contracts of the $460.00 call expiring on Friday, August 21, 2020. Option traders are pricing in a 7.7% move on earnings and the stock has averaged a 4.0% move in recent quarters.
Alibaba Group Holding Ltd. (BABA) is confirmed to report earnings at approximately 7:10 AM ET on Thursday, August 20, 2020. The consensus earnings estimate is $1.99 per share on revenue of $21.13 billion and the Earnings Whisper ® number is $2.11 per share. Investor sentiment going into the company's earnings release has 83% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 8.74% with revenue increasing by 26.22%. Short interest has increased by 30.1% since the company's last earnings release while the stock has drifted higher by 25.0% from its open following the earnings release to be 20.0% above its 200 day moving average of $211.59. Overall earnings estimates have been revised lower since the company's last earnings release. On Friday, August 7, 2020 there was some notable buying of 12,935 contracts of the $300.00 call expiring on Friday, November 20, 2020. Option traders are pricing in a 6.2% move on earnings and the stock has averaged a 3.1% move in recent quarters.
JD.com, Inc. (JD) is confirmed to report earnings at approximately 5:50 AM ET on Monday, August 17, 2020. The consensus earnings estimate is $0.38 per share on revenue of $26.98 billion and the Earnings Whisper ® number is $0.46 per share. Investor sentiment going into the company's earnings release has 78% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 52.00% with revenue increasing by 23.25%. Short interest has increased by 16.7% since the company's last earnings release while the stock has drifted higher by 24.1% from its open following the earnings release to be 36.9% above its 200 day moving average of $45.34. Overall earnings estimates have been revised higher since the company's last earnings release. On Friday, August 14, 2020 there was some notable buying of 12,799 contracts of the $62.00 call expiring on Friday, August 21, 2020. Option traders are pricing in a 8.0% move on earnings and the stock has averaged a 6.4% move in recent quarters.
Home Depot, Inc. (HD) is confirmed to report earnings at approximately 6:00 AM ET on Tuesday, August 18, 2020. The consensus earnings estimate is $3.71 per share on revenue of $31.67 billion and the Earnings Whisper ® number is $3.75 per share. Investor sentiment going into the company's earnings release has 78% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 17.03% with revenue increasing by 2.69%. Short interest has decreased by 39.8% since the company's last earnings release while the stock has drifted higher by 16.7% from its open following the earnings release to be 22.4% above its 200 day moving average of $229.20. Overall earnings estimates have been revised higher since the company's last earnings release. On Friday, August 14, 2020 there was some notable buying of 3,323 contracts of the $300.00 call expiring on Friday, August 28, 2020. Option traders are pricing in a 4.2% move on earnings and the stock has averaged a 2.5% move in recent quarters.
Lowe's Companies, Inc. (LOW) is confirmed to report earnings at approximately 6:00 AM ET on Wednesday, August 19, 2020. The consensus earnings estimate is $2.93 per share on revenue of $21.29 billion and the Earnings Whisper ® number is $2.97 per share. Investor sentiment going into the company's earnings release has 78% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 36.28% with revenue increasing by 1.42%. Short interest has decreased by 19.2% since the company's last earnings release while the stock has drifted higher by 25.9% from its open following the earnings release to be 31.2% above its 200 day moving average of $117.67. Overall earnings estimates have been revised higher since the company's last earnings release. On Friday, August 7, 2020 there was some notable buying of 1,994 contracts of the $170.00 call expiring on Friday, August 21, 2020. Option traders are pricing in a 6.0% move on earnings and the stock has averaged a 5.8% move in recent quarters.
Target Corp. (TGT) is confirmed to report earnings at approximately 6:30 AM ET on Wednesday, August 19, 2020. The consensus earnings estimate is $1.56 per share on revenue of $19.30 billion and the Earnings Whisper ® number is $1.64 per share. Investor sentiment going into the company's earnings release has 75% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 14.29% with revenue increasing by 4.77%. Short interest has decreased by 36.8% since the company's last earnings release while the stock has drifted higher by 10.0% from its open following the earnings release to be 18.0% above its 200 day moving average of $115.73. Overall earnings estimates have been revised higher since the company's last earnings release. On Monday, August 10, 2020 there was some notable buying of 4,479 contracts of the $135.00 call expiring on Friday, September 18, 2020. Option traders are pricing in a 6.3% move on earnings and the stock has averaged a 7.7% move in recent quarters.
Sea Limited (SE) is confirmed to report earnings at approximately 6:30 AM ET on Tuesday, August 18, 2020. The consensus estimate is for a loss of $0.47 per share on revenue of $1.03 billion and the Earnings Whisper ® number is ($0.36) per share. Investor sentiment going into the company's earnings release has 74% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 34.29% with revenue increasing by 136.16%. Short interest has decreased by 8.5% since the company's last earnings release while the stock has drifted higher by 91.7% from its open following the earnings release to be 98.1% above its 200 day moving average of $63.87. Overall earnings estimates have been revised lower since the company's last earnings release. On Tuesday, August 4, 2020 there was some notable buying of 4,000 contracts of the $110.00 put expiring on Friday, January 15, 2021. Option traders are pricing in a 12.9% move on earnings and the stock has averaged a 16.7% move in recent quarters.
Niu Technologies (NIU) is confirmed to report earnings at approximately 3:00 AM ET on Monday, August 17, 2020. The consensus earnings estimate is $0.07 per share on revenue of $88.07 million and the Earnings Whisper ® number is $0.11 per share. Investor sentiment going into the company's earnings release has 57% expecting an earnings beat. Consensus estimates are for earnings to decline year-over-year by 30.00% with revenue increasing by 13.97%. Short interest has increased by 18.9% since the company's last earnings release while the stock has drifted higher by 129.8% from its open following the earnings release to be 90.3% above its 200 day moving average of $10.94. Overall earnings estimates have been revised higher since the company's last earnings release. The stock has averaged a 3.7% move on earnings in recent quarters.
BJ's Wholesale Club, Inc. (BJ) is confirmed to report earnings at approximately 6:45 AM ET on Thursday, August 20, 2020. The consensus earnings estimate is $0.57 per share on revenue of $3.64 billion and the Earnings Whisper ® number is $0.60 per share. Investor sentiment going into the company's earnings release has 73% expecting an earnings beat. Consensus estimates are for year-over-year earnings growth of 46.15% with revenue increasing by 8.79%. Short interest has decreased by 3.2% since the company's last earnings release while the stock has drifted higher by 33.8% from its open following the earnings release to be 46.7% above its 200 day moving average of $28.27. Overall earnings estimates have been revised higher since the company's last earnings release. On Wednesday, August 12, 2020 there was some notable buying of 2,119 contracts of the $50.00 call expiring on Friday, September 18, 2020. Option traders are pricing in a 12.4% move on earnings and the stock has averaged a 10.0% move in recent quarters.
What's up all you fucking Autists, Degenerates, and Lurkers??? Real Autism I'm one of the truly faithful degenerates. Below is my story... TLDR- I'm a degenerate gambler. Buy AMD 82.00C 11/14 I began the journey in college by gambling thousands of dollars on student loans on daily binary options. This of course was retarted and I lost close to 5k pretty quickly. I even chased losses by taken advances from my credit card. I stopped after I maxed one of my cards out. After doing much more research and taking a couple years off, I got back into the game in March with a $10k dollar personal loan. After carefully placed medium risk trades everything went to hell with the virus. I quickly switched to puts only to chase too hard and got absolutely blown up. Account was wiped out. I vowed I would be back. In September with another loan and some savings I got back in with $4,500. This quickly went to 8k and I actually went to cash right before the big drop in early September. I got back in too early, and nearly got wiped out. Careful diligence and some luck saw my account go to nearly $10k just a few days ago when I placed a very risky trade with the vaccine news. The drop on Monday afternoon caught me, and again destroyed my account. I'm a Degenerate with my account down now 75% in two days, and the panic I used to feel is only replaced by an urge to place an even risker trade to make up for it. Right now, all I really care about is AMD going to the moon tomorrow so I can make it all back and feel that good sweet dopamine rush before I'm back at it again. If this somehow pays, I'll donate 5% of the gains to charity. Position- AMD 82.00C 11/13 (28 Contracts)
Hi everyone, I've been passionate about sandbox games and how they are designed into a functioning coherent environment. I developed most of this passion in Eve and served as a CSM last year. I'm hopeful that DU will be the future of sandbox sci-fi games. I wanted to note down how I think NQ can better some of the game's most important aspects. Some of their staff probably read here too. The forums have this "one idea per thread" rule, so I decided to put them here. Here are some problems, and how I would solve them. PvP 1) Cube Meta: Need viability for non-cubes.
By small changes in the math, it should be possible to make drag matter more in atmo, not for small cross sectioned ships, but for the ones with bigger CS.
A developmentally costlier option would be letting players edit the "area" that a core unit provides. PvP rewards smaller core units so it becomes important to cram all the elements into small areas. That promotes the cubes. If we could edit the area into a 3d rectangle (total area remains the same, just changes shape), that'd let us to make ships that aren't cubes and cram the same amount of stuff.
The best option would be making cross section matter in PvP. Ideally (not sure if servers can handle this), weapons should miss more if target ships have a narrow cross section from the attacker's POV. If servers can't calculate relative POV's, then an easier way to implement cross section into PvP is using the smallest CS of a ship as a coefficient in the miss chance.
2) Small vs Big Ships: Need drastic balance.
The lock range differentiation wrt target core unit size needs to go. It's keeping everyone from even thinking about M or L core PvP ships. Eve has this mechanic entirely right. Larger ships should be able to lock and fire at longer ranges. They should just miss more.
Small ships should have tracking and lock time advantages. Tracking should matter to the extent that if I am going 90 degrees wrt a big ship in a smaller core, even at ranges like 100km, that should make me easier to miss. After all those are the ranges most of the combat happens.
Some sort of limitation to cramming L guns to small constructs is needed. If "power" isn't going toward that direction, NQ should just make M/L gun models way larger (and make them slower-turning too that'd align with the above recommendation).
More tanking advantage to larger ships is needed. Perhaps weapons tear through too many voxels at the same time. Or voxels should be overall less heavy so we can use more of them.
Instead, the larger cores actually have speed advantage where they shouldn't. This is because you can cram way more Delta V in an M/L core compared to how much you can cram in an S/XS core. Sure the reactivation time is a good balancing factor but it's not enough if the large ships can accelerate and decelerate at way higher Gs. Again, one easy option would be drastically increasing the size of L/XL engine models to match the proportions of area differences among cores.
3) Non-Consensual PvP: The current non-consensual PvP is very binary and unsustainable. If you can find some people careless enough to go in a direct path between two planets with no radars, you kill them. People will wake up (or they already did) to this very fast, plus warp drives will become abundant, and pretty soon no such PvP will be possible. Meanwhile, if you are a new player with no knowledge and you get caught to pirates like this, you basically have zero options to protect yourself.
For Offense: Steal warp bubbles (disrupts your warp path), webs (slows down your target ship), combat probes (detects position of a target ship) from Eve. They'll be great additions.
Create rewards in space for which people will be willing to take risks. Asteroids/asteroid mining is supposed to function like this. But depending on implementation they can either become monopolized or just too abundant/wide to go and find any targets in.
Hope eventually stealth gets added. It's easy to imagine it as radar immunity (until close proximity). But it should have drastic downsides.
For Defense: Combat probes can actually be used defensively too.
Some sort of "evasive maneuver". Perhaps a module that provides a quick random change in the ship's direction but not the speed that the offender needs to adapt.
Some sort of temporary damage mitigation solution.
Economy 1) There is no need to trade.
People don't use the markets too much. Every org has a mining/industry wing and everything is made in-house. I think this problem arises from the fact that the only scalable and reliable way to make money is mining/industry (maybe add logistics but that's dependent on the first two). Sure you got some people with eccentric ventures and ship developers but you can't scale that across hundreds of people. Since you have to have a factory to earn money, why wouldn't you scale it so you make everything and are self-sufficient? Now, if there was a plethora of other moneymaking activities in the game, then we'd see a way more an Eve-like market and specialization of activities. Imho this is hard to achieve without NPCs. It's really hard to imagine a functioning sandbox without the bottom layer of the ecosystem. NPCs to a sandbox MMO are what grass/vegetation is to an ecosystem. Without them there are no missions, nothing to kill and earn money from in a multitude of ways. No reward that people in adequate ships can go and chase, and become prey to other people like pirates. I kinda just wish NQ had 3 more years/funding to develop the game. The Minecraft/Factoria will be attractive for only so long if there is no meaningful economy, trade, differentiation, and things to do with things you make. Talents seem to be made in a way to foster differentiation, so maybe that's where we'll see some improvement. But game design needs to change.
2) Resource Hexes are too disposable.
The game has a great digging system. We create these elaborate mines. We could voxelize them and make wonders with them. Instead, we abandon them in 2 hours. With the territory warfare, under current ore system, the only place that'll be worth attacking is the HQ of a corp with the stashes and factories. And I'm pretty sure most people will move those to the Sanctuary once the territory warfare hits. Resource hexes would have been great places to fight over. But even meganodes last just a day as of this point.
In an ideal design, ore should have been way less scattered across different hexes. And once it's found in a hex, it should have lasted a long time, so there are these valuable resource mines to fight over. The pace of mining is actually perhaps fine. But there are lots of other ways to achieve "long lasting resource mines". Like going deeper could "destabilize" a hex so people would have to put down units that take a week to anchor. And bettemore abundant ore could have been found in deeper attitudes. This is just one way on top off my head.
3) No mining robots please.
Ditch this idea that was mentioned months ago if it's still in the cooking. You don't want to delegitimize the human time spent on the only meaningful resource gathering activity in the game.
Overall I have great hopes but also concerns about the game. One major concern/test was whether the server tech will hold. It has improved a lot and that's great news for NQ. The next concern is whether NQ is spread too thin. The game's development was probably too early to commit to a non-wipe environment, and NQ might be underestimating how much it lacks vs an actually functioning ecosystem. Not to mention customer support is pretty nonexistent (god forbid you have a problem that's beyond the Discord staff's abilities). People will get bored of cool looking handcrafted ships pretty fast unless they have meaningful stuff to do in them very soon. Let's see how things develop. o7
I did not think we'd get here. COVID cases are in the single digits, and many cases are off-campus (https://health.gatech.edu/coronavirus/health-alerts). Test positivity rates are incredibly low (https://gatech-covid-tracker.com/). I think we can say that Georgia Tech has navigated through it's first wave of COVID cases. How did this happen? I'm not an epidemiologist, and even Dr. Fauci himself wouldn't be able to give you a 100% correct answer, because nobody can give you a 100% correct answer - there are too many unknowns. But, we can look at a few factors. 1.) Modified herd immunity threshold. Immunity is likely a real phenomena with COVID-19. Yes, there are now 7 confirmed cases of reinfection, but immunity is not a binary thing. It is not as if every person infected with COVID will either be immune, or they will be as unprotected as the rest of us. It's likely that the majority of COVID cases will gain some sort of immunity, and some will gain no immunity. For the sake of simplicity, let's just assume everyone infected with COVID at our campus has immunity. Georgia Tech has, in total, around 900 positive COVID cases. There are ~14,000 people on campus if you wildly extrapolate from a few surveys taken on this subreddit - if anyone could find where the actual number is, it would be helpful. Additionally, around 5-10% of the US was probably infected in the original Feb-March surge, which would be 700-1400 people. This brings us to 1600-2300 immune people in a population of 14000. The herd immunity threshold is given by (1-1/R0). Uncontrolled, the R0 for SARS-CoV2 is ~4. This means roughly 75% of the populace must be infected to gain "true immunity" - IE, you can do whatever you want, no distancing, no masking, etc. Obviously this is a bad idea. But, we aren't letting SARS-Cov2 spread uncontrollably. Mask compliance is high, people are trying to distance, people are washing their hands more often, etc. R0 is a function of environmental parameters as well - increasing distancing and hygiene decrease your R0. So what is the R0 with distancing and masking? That's a big question, but estimates from New York and Western Europe say it was somewhere around 0.8-1.1. A college campus will have a higher R0 than a typical state or nation, so we'll shift this up to 1.1-1.3. This brings our herd immunity threshold to anywhere between 9-23%. We currently have in the range of 11.5%-16%, and some cases on campus may have gone totally undetected. Here's a twitter thread by an MIT data scientist if you want to read more about the "modified herd immunity" phenomena. 2.) The people who took the most risks have already gotten COVID. Anecdotally, and logically, this makes sense. People going to bars, frat parties, etc have already been infected, and that was our "first wave". Unfortunately, I don't know how to quantify this in any meaningful way, but it is probably a factor. 3.) Behavior change. People could've seen the surge in cases and decided to be more careful - get tested weekly, avoid indoor dining, go to the CRC early in the morning when it's less crowded rather than in the middle of the day, etc. This would lower R0 as well and aid with point 1, although again, I don't know how to meaningfully quantify this. But it is a possible factor. ____________________________________________________________________________________________________________ If you made it through the above, congratulations. The question now is what Tech should do. Frankly, I feel like I am wasting both money and time this semester. This is unavoidable, and not Tech's fault or USG's fault - just a virus doing it's thing. But, just as governments - those of New York, China, South Korea, Germany, etc - gradually eased back on restrictions as the first curve was crushed, I believe Tech can and should do the same. We should not throw the floodgates open and let all hell break loose - but I think we can slowly loosen the screws in a manner that improves educational experiences, and in a way that avoids a second wave. Remote learning sucks. At least for intro classes, there is far better free material on Coursera - made by people who know how to deliver content online and who have been doing it for years - as opposed to professors who were thrown into this a few months ago. As we all know, many "hybrid" courses are pretty much all online. I'd suggest the OPTION - for both professors and students, mandates are a god awful idea - to have more in-person hybrid sections. This won't give me my money's worth - but it'll give us something. As of now, I have three hybrid classes - and yet have not had a single in person class. These classes can be conducted in a safe, distanced/masked manner, as to keep our R0 low and keep reaping the rewards of the "modified herd immunity" discussed above. This might be difficult to implement in the middle of this semester, but I think it can be implemented next semester, in the absence of mass vaccination until (in the most optimistic case) February-March. Other things include opening up lounges in dorms. Also, I know visiting other dorms is technically banned, but everyone I know is ignoring that rule. Many people aren't even aware of that rule - might as well just get rid of it if compliance is close to nil. But, I'd prefer more in-person classes above all else. This was a long post. Ultimately, COVID is a game of trades - we could lock everyone in their homes until there's a vaccine, but that would destroy our society. We could let everyone run wild until there's a vaccine - again, that would destroy our society. It's a multivariate optimization problem, where we are trying to maximize safety, education, and the student experience. I'm just a dude trying to help us find that maximum. TLDR: COVID-19 first wave beaten due to number of factors. More in-person classes would be nice.
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